Geomaster, Lda - User contributions [en]

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2021-03-07T20:11:05Z

Jgrocha: /* Open Data Day, 2018 */

= Apresentação =

A formação e a disponibilização de conteúdos faz parte do ADN da Geomaster. Neste espaço, estamos a juntar todos os conteúdos das nossas formações, que ainda estão dispersos por vários sítios.

== Onde e como pedir ajuda? ==

[https://lists.osgeo.org/mailman/listinfo/portugal Lista portuguesa da OSGeo]

[https://lists.osgeo.org/mailman/listinfo/qgis-user Lista internacional do QGIS]

https://gis.stackexchange.com/

A Geomaster está oferecer suporte ao QGIS, de forma gratuita. Use o centro de suporte disponível em [https://ticket.geomaster.pt/open.php?lang=pt_PT ticket.geomaster.pt].

Antes de pedir ajuda, faça o trabalho de casa. Pesquise na net se a questão já foi levantada e resolvida.

Para procurar nas listas do QGIS, use o endereço: http://osgeo-org.1560.x6.nabble.com/QGIS-f4099105.html

= Requisitos =

Para fazer os exercícios propostos, precisa de ter algum espaço livre e o software necessário instalado. Os exercícios são independentes do sistema operativo: tanto pode usar Linux, Windows ou macOS.

== Máquina virtual OSGeo Live ==

Uma boa alternativa para a formação é a utilização da máquina virtual [https://live.osgeo.org/en/index.html OSGeo Live] que já tem todo o software SIG necessário.

= Conteúdos =

== Sentinel-2 Image processing using QGIS+SCP ==

Notes from Sentinel-2 Image processing using QGIS+SCP course at Skovskolen, Nødebo.

Documentation:

[https://readthedocs.org/projects/semiautomaticclassificationmanual/downloads/pdf/latest/ Semi-Automatic Classification Plugin Documentation]

[[Installing SCP in Ubuntu]]

[[Create a Copernicus Open Access Hub account]]

[[Search and download Sentinel-2 images]]

[[Search and download Landsat 8 images]]

[[Radiance to reflectance]]

[[Clip Sentinel-2 images]]

[[Band compositions]]

[[Export band compositions]]

[[Raster algebra: calculating indexes]]

[[Unsupervised classification]]

[[Supervised classification]]

=== Links ===

https://earth.esa.int/web/sentinel/technical-guides/sentinel-2-msi/msi-instrument

http://esa-sen4cap.org/content/eo-products

https://sentinel.esa.int/web/sentinel/user-guides/sentinel-2-msi/document-library

https://www.indexdatabase.de/db/s-single.php?id=96

https://land.copernicus.eu/global/products/ba

https://fromgistors.blogspot.com/2016/11/from-image-download-to-ndvi-calculation.html

http://www.qgis.pt/blog/2016/12/14/detecao-remota-com-o-qgis/ (em Português)

== Wikidata Sixth Birthday ==

[[File:Birthday banner for 4th Wikidata Birthday.png]]

=== Objectivo ===

Fazer uma mapa:
# Mostrar as ruas, largos, praças e outros espaços com topónimos
# Poder filtrar por:
## sexo
## ocupação (religioso, militar poeta, escritor, político...
## século
## etc

Eventualmente, fazer um quantos gráficos, com percentagens:
# topónimos com nome de pessoas versus outras origens
# nomes de mulheres versus nomes de homens
# políticos versus artes e ciências

=== Problema ===

No OpenStreetMap não existe informação sobre as propriedades do topónimo. O topónimo pode estar escrito de diversas formas e contém partes que não interessam (Rua, Avenida, Prof, Doutor, etc). (Nota: cruzar com o dataset da [http://centraldedados.pt/codigos_postais/ Central de Dados dos Códigos Postais]).

A [https://www.openstreetmap.org/way/35997529#map=16/41.1809/-8.6094 Rua de São Tomé] refere-se a uma pessoa?

Rua Egas Moniz. Qual [https://pt.wikipedia.org/wiki/Egas_Moniz Egas Moniz]?

==== Solução ====

Wikidata! Diferença entre a página da [https://pt.wikipedia.org/wiki/Ant%C3%B3nio_Egas_Moniz Wikipédia do Egas Moniz] e a da [https://www.wikidata.org/wiki/Q273219 Wikidata da mesma pessoa].

Criei a entidade: https://www.wikidata.org/wiki/Q58129518

No OpenStreetMap já se usa uma tag [https://wiki.openstreetmap.org/wiki/Key:wikidata wikidata] para entidades geográficas bem conhecidas, como a [https://www.openstreetmap.org/way/247168260 Torre dos Clérigos].

Existe uma proposta para acrescentar a origem de um determinado nome, usando a tag [https://wiki.openstreetmap.org/wiki/Key:name:etymology name:etymology].

==== Limitações ====

Nem tudo está na Wikidata. Na verdade, existe pouca informação (sobre Portugal) no Wikidata.

No OpenStreetMap também não há muitas tags wikidata.

==== Resolução das limitações ====

'''Editar o OpenStreetMap e a Wikidata!'''

Nota: área pantanosa em relação às licenças: CC-0 versus ODBL.

==== Outras fontes de dados ====

Central de dados

http://centraldedados.pt/nomes_proprios/

https://genderize.io/

==== Algum código de base ====

https://gitlab.com/pdiasalmeida/osm-street-names

== Open Data Day, 2021 ==

Publicado no diário do OpenStreetMap.

<syntaxhighlight lang="bash">
jgr@zoe:~/bonn/ownCloud/OSM/Endereços$ xmlstarlet format --indent-tab Addresses_0110_EPSG4258.gml > Addresses_0110_EPSG4258.formated.gml

ogrinfo -ro -so Addresses_0110_EPSG4258.formated.gml Address

ogrinfo -where gml_id="'pt.ine.add.PTCONT.25172'" Addresses_0110_EPSG4258.formated.gml Address

# USAR o driver GMLAS em vez de GML

ogrinfo -ro -so GMLAS:Addresses_0110_EPSG4258.formated.gml Address

ogrinfo -where id="'pt.ine.add.PTCONT.25172'" GMLAS:Addresses_0110_EPSG4258.formated.gml Address

GML_ATTRIBUTES_TO_OGR_FIELDS=YES ogrinfo -where gml_id="'pt.ine.add.PTCONT.25172'" Addresses_0110_EPSG4258.formated.gml Address

GML_SKIP_RESOLVE_ELEMS=NONE ogrinfo -where gml_id="'pt.ine.add.PTCONT.25172'" Addresses_0110_EPSG4258.formated.gml Address

GML_ATTRIBUTES_TO_OGR_FIELDS=YES GML_SKIP_RESOLVE_ELEMS=NONE ogr2ogr -f PostgreSQL PG:'service=ftth schemas=ilhavo' GMLAS:Addresses_0110_EPSG4258.formated.gml -nlt CONVERT_TO_LINEAR

ogr2ogr -f "ESRI Shapefile" ilhavo.shp PG:"service=ftth" "ilhavo.moradas"
</syntaxhighlight>

== Open Data Day, 2018 ==

[[File:Logo odd 2018.png]]

[[Introdução ao OpenStreetMap]]

[[Serviços sobre os dados do OpenStreetMap]]

[[Dados OpenStreetMap no QGIS]]

[[Dados OpenStreetMap no PostgreSQL]]

[[OpenStreetMap API]]

[[Routing com os dados do OpenStreetMap]]

== SIG desktop com QGIS ==

Introdução à interface do QGIS, a visualização complementar de geometrias e dados, filtrar, selecionar, expressões, trabalhar com a seleção, etc.

[[Instalação QGIS no Windows com base no OSGeo4W]]

Instalação da primeira extensão [https://plugins.qgis.org/plugins/quick_map_services/ QuickMapServices].

Os dados vectoriais referem-se a entidades que têm uma componente espacial (geográfica) e um conjunto de atributos.

[[Explorar dados vectoriais]]

[[Georreferenciação de imagens e criação de camadas]]

[[Edição de dados vetoriais]]

[[Geração de um modelo digital do terreno]]

Acrescentar melhorias aos formulários:
# campos que se atualizam automaticamente
# joins e formulários com combox
# um exemplo de uma relação master → detail

[[Ligação a uma base de dados Postgresql]]

[[Análise espacial com rasters]]

==== Para rever ou eliminar... ====

[[Geoprocessamento]]

[[Criar camadas vectoriais]]

Os dados raster referem-se a superfícies contínuas, cujas propriedades se vão alterando ao longo da superfície.

Visualizar dados raster, calculadora raster, calcular o aspecto, declives, mostrar um perfil.

[[Explorar dados raster]]

Cruzar camadas, associar imagens, associar ações a entidades geográficas

[[Cruzar dados vectoriais]]

Introdução à análise espacial: cálculo de áreas de influência, recorte em função da localização, etc.

[[Introdução à análise espacial]]

[[Georreferenciação de mapas]]

[[Criação de camadas]]

[[Teste de auto-avaliação]]

== SIG desktop com QGIS: Tópicos avançados ==

[[Exercício de aquecimento]]

[[QGIS com Postgresql]]

[[Edição de informação geográfica]]

O processamento com o QGIS é tão assustador como fabuloso. Assustador pela diversidade de alternativas que apresenta e fabuloso pela mesma razão. Além de todas as capacidades de processamento que tem no próprio código, O QGIS liga-se muito bem a outros software de processamento, como o GRASS, SAGA, Orfeo Toolbox, etc.

[[Processamento em QGIS]]

As imagens Sentinel são disponibilizadas pela ESA. O tratamento de imagens Sentinel-2 com a extensão [https://fromgistors.blogspot.com/p/semi-automatic-classification-plugin.html Semi-Automatic Classification Plugin]

[[Tratamento de imagens Sentinel]]

As imagens raster podem ser geridas a partir do sistema de ficheiros ou a partir da base de dados Postgresql.

[[Suporte Postgresql para rasters]]

O QGIS está escrito em C++ que é uma linguagem orientado a objetos, que gera código muito eficiente. O QGIS usa a biblioteca QT para todas as componentes de interface com o utilizador.
Embora todo o núcleo esteja em C++, todas as funcionalidades são expostas para outras aplicações através de uma API que pode ser invocada a partir do Python. Ou seja, a partir de um programa Python, podemos comandar o QGIS e tirar partido de todas as suas funcionalidades.

[[Explorar o QGIS a partir do Python]]

[[QField: o QGIS ao ar livre]]

[[Sobre a preparação desta formação]]

== Base de dados espaciais com Postgresql ==

== Data ==

[https://resourcewatch.org/ Resource Watch – Monitoring the Planet's Pulse]

== Spatial Data Mining ==

* [https://geodacenter.github.io/ GeoDa] is a free and open source software tool that serves as an introduction to spatial data analysis.
* [https://github.com/MapPlus/spatial_statistics_for_geotools_udig GeoAnalysis library] is a java-based open source for geospatial analysis.

== QGIS na área da Saúde ==

[https://plugins.qgis.org/plugins/GeoHealth/ Plugin GeoHealth]

== QGIS na área da Arqueologia ==

Tratamento dos arqueossítios em http://www.geira.pt/arqueo/ListaArqueossitios.html

xml disponível em: http://www4.di.uminho.pt/~jcr/XML/didac/xmldocs/arq.xml

<syntaxhighlight lang="bash">
wget http://www4.di.uminho.pt/~jcr/XML/didac/xmldocs/arq.xml
xsltproc sample.xsl arq.xml > arq.csv
</syntaxhighlight>

<syntaxhighlight lang="xml">
<?xml version="1.0"?>
<xsl:stylesheet version="1.0" xmlns:xsl="http://www.w3.org/1999/XSL/Transform">
<xsl:output type="text" indent="no" omit-xml-declaration="yes" />
<xsl:strip-space elements="*" />

<xsl:template match="//ARQELEM">
<xsl:value-of select="normalize-space(IDENTI)"/>|<xsl:value-of select="normalize-space(DESCRI)"/>|<xsl:value-of select="normalize-space(CRONO)"/>|<xsl:value-of select="normalize-space(FREGUE)"/>|<xsl:value-of select="normalize-space(CONCEL)"/>|<xsl:value-of select="normalize-space(LATITU)"/>|<xsl:value-of select="normalize-space(LONGIT)"/>|<xsl:value-of select="normalize-space(ALTITU)"/>|<xsl:value-of select="normalize-space(ACESSO)"/>|<xsl:value-of select="normalize-space(QUADRO)"/>|<xsl:value-of select="normalize-space(TRAARQ)"/>|<xsl:value-of select="normalize-space(DESARQ)"/>|<xsl:value-of select="normalize-space(INTERP)"/><xsl:text>
</xsl:text>
</xsl:template>
</xsl:stylesheet>
</syntaxhighlight>

Tratamento manual:

coordenadas: multiplicar por 1000

usar o separador de campos: |

usar o delimitador de campos: '

Sistemas de coordenadas: EPSG:20790

Resultado final: arqueossitios.csv

=== Portal do Arqueólogo ===

Acabei por sacar pelo QGIS, ligando-me ao servidor.

Dados de ligação:

1) É preciso criar uma nova ligação do tipo: ArcGisFeatureServer, com os seguintes dados:

Nome: Portal do Arqueólogo

URL: https://services8.arcgis.com/ITVSIrZ4rxt6SbBo/arcgis/rest/services/Sitios_20190207_visualização/FeatureServer

==== Sacar lista de sítios ====

<syntaxhighlight lang="bash">
#!/bin/bash

mkdir -p portalarqueologo
for i in {1..1735}
do
curl "http://arqueologia.patrimoniocultural.pt/index.php?sid=sitios&p=$i" -o portalarqueologo/$i.html
done
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd portalarqueologo/
sed -n -e 's/<td data-label="Designação"><a href="\/index.php?sid=sitios\&subsid=$[0-9]\+$">$[^<]\+$<\/a><\/td>/\1\t\2\thttp:\/\/arqueologia.patrimoniocultural.pt\/index.php?sid=sitios\&subsid=\1/p' *.html | sed 's/^\s\+//g' > lista_sitios.csv
</syntaxhighlight>

==== Sacar sítios ====

==== Extrair coordenadas ====

jgr@zoe:~/bin/sitios$ grep '<div id="singleListingMap" data-latitude="[^"]\+" data-longitude="[^"]\+" data-map-icon' *.html > x

sed -n -e 's/$^[0-9]\+$.html:\s\+<div id="singleListingMap" data-latitude="$[0-9.]\+$" data-longitude="$[-0-9.]\+$".\+$/\1\t\2\t\3/p' x

<h2>Monte da Matosa 2</h2> Sítio <span title="CNS">(13709)</span>

grep '<h2>[^<]\+</h2> Sítio <span title="CNS">([\d]\+)</span>' *.html

==== QGIS ====

Abrir lista_sitios.csv

Abrir

== Dados do OpenStreetMap ==

* Introdução ao OpenStreetMap
* Dados do OpenStreetMap no QGIS
* Dados do OpenStreetMap no Postgresql
* Queries com OverPass API, http://overpass-turbo.eu/
* Routing com os dados do OpenStreetMap (OpenTripPlanner)
* Routing com MAPS.ME
* Usar os mapas do OpenStreetMap num blog

=== Requisitos ===

* Computador c/ algum espaço livre
* Dados: serão descarregados na hora, a partir de: http://openstreetmap.pt/wp-content/uploads/
* Software
** QGIS 2.18.17 LTR
** Postgresql v9.6 + PostGIS (não é preciso instalar; haverá um servidor na sala)
** Instalar o MAPS.ME no telemóvel

== Publicação na Web com Geoserver ==

[[Servidores de mapas: conceitos]]

[[Instalação do Geoserver]]

[[Disponibilização de uma camada WMS/WFS]]

[[Disponibilização de uma camada WMTS]]

[[Publicação de grupos]]

== Publicação na Web com uMap ==

A plataforma uMap permite criar mapas de uma forma simples. Os mapas criados podem ser incorporados num blog ou num site.

[[O meu primeiro mapa com o uMap]]

== Drones ==

[[DJI MAVIC 2 PRO]]

[[Flight planner]]

[[Running OpenDroneMap]]

== Contribuir para projectos Open Source no domínio dos SIG ==

[[Contribuir para o Nominatim]]

[[Contribuir para o QGIS]]

[[Contribuir para plugins QGIS]]

[[Contribuir para o OpenTripPlanner]]

[[Contribuir para o GeoExt]]

[[Contribuir para o PostGIS]]

[[Contribuir para o curso PostGIS com Rasters]]

= Outros cursos e recursos =

[http://training.gismentors.eu/isprs-summer-school-2016/index.html ISPRS Congress 2016 Summer School]

[http://training.gismentors.eu/grass-gis-workshop-jena-2018/index.html GRASS GIS Workshop in Jena]

[https://www.hatarilabs.com/ih-en/working-with-sentinel-2-imagery-on-qgis Working with Sentinel 2 Imagery on QGIS]

[https://uwgis.wordpress.com/gis-practicals/flood-risk-mapping/ QGIS Flood Risk Mapping]

[[Spatial-Temporal Data Analysis]]

[[Geospatial Data Mining]]

[[Como gravar cursos em vídeo]]

= Propostas =

[[QGIS: Generalização Cartográfica]], em parceria com IBGE

[[QGIS: Deteção de estradas em imagens Sentinel-2]], em parceria com IBGE

[[QGIS: Ler cartas náuticas]], em parceria com a comunidade QGIS e de acordo com esta [https://github.com/faunalia/qnavigate proposta de melhoramento]

[[QGIS: Carregar informação meteorológica]], em parceria com a comunidade QGIS e de acordo com esta [https://github.com/faunalia/qnavigate proposta de melhoramento]

[[QGIS:Plugin para dados do INE]]

[[QGIS:Plugin para sobre a Saúde em Portugal]]

= Modelo Topográfico =

http://www.dgterritorio.gov.pt/recart/TRANSPORTES%20(Transporte%20rodovi%C3%A1rio)/CatalogoDasViasRodoviariasParte2.html

http://www.dgterritorio.gov.pt/recart/TRANSPORTES%20(Transporte%20rodovi%C3%A1rio)/CatalogoDasViasRodoviariasParte2UTF-8_20190703.csv

<pre>
vi sed.txt

1s/codigoViaRodov/codigo_via_rodov/
1s/tipoViaRodovC/tipo_rodovia_c/
1s/codigoDGT/codigo_dgt/
1s/codigoArruamento/codigo_arruamento/
1s/tipoViaRodovD/tipo_rodovia_d/
1s/tipoViaRodovAbv/tipo_rodovia_abv/
1s/nomeSufixo/nome_sufixo/
1s/nomeAlternativo/nome_alternativo/
1s/pontosExtremoseIntermedios/pontos_extremos_e_intermedios/
1s/lugarINEcod/lugar_ine_cod/
1s/fonteAquisicaoDados/fonte_aquisicao_dados/
1s/dataEdital/data_edital/
1s/DICOFRE/dicofre/
1s/DICO/dico/
1s/DI/di/
1s/CO/co/
1s/dataCat/data_cat/

sed -f sed.txt -i CatalogoDasViasRodoviariasParte2UTF-8_20190703.csv
</pre>

DJI MAVIC 2 PRO

2021-02-22T00:16:13Z

Jgrocha: Created page with " https://dominey.blog/2019/11/04/best-photo-and-video-settings-for-the-dji-mavic-2-pro/"

https://dominey.blog/2019/11/04/best-photo-and-video-settings-for-the-dji-mavic-2-pro/

Flight planner

2021-02-07T18:45:28Z

Jgrocha: /* Legacy software */

=== Software ===

==== Open source software (better with drones using '''PX4''' or '''ArduPilot''' controllers) ====

* [https://www.dronecode.org/ Dronecode Foundation]
** [http://qgroundcontrol.com/ QGroundControl] Qt based application
*** QGroundControl uses the MavLink control and provides full flight control and vehicle setup for '''PX4''' or '''ArduPilot''' powered vehicles.
*** [https://github.com/The1only/rosettadrone Drone Rosetta] is a proxy to the MavLink protocol enabling to use apps like QGroundControl to plan missions. With Drone Rosetta, it is possible to control DJI drones using QGroundControl.

* Airdata

==== Legacy software ====

PIX4DCapture

DroneDeploy

Drone Harmony

'''Dronelink'''

* Mapping Plans: $ 20,00 one time
** Support AGL (ground level) (terrain follow) - Uses ESRI
* [https://www.youtube.com/watch?v=Hley9DDEDdw Gound level usage] by Erik, from DroneLink
* [https://www.youtube.com/watch?v=zsZMyRYfOaA Tutorial Castellano] Boa introdução

* Discussão do focus: https://support.dronelink.com/hc/en-us/community/posts/360036947813-Footage-not-in-focus-Mavic-Pro-

'''Red Waypoint'''

* [http://redwaypoint.com Red Waypoint] $16.99
** Terrain follow

Litchi

* [https://flylitchi.com/ Litchi for DJI Mavic / Phantom / Inspire / Spark] 25,99 €

https://flylitchi.com/hub

=== Forums ===

* [https://mavicpilots.com/forums/mavic-2-pro.68/ Mavic 2 Pro]

=== Tips ===

Quando o drone está na altura do voo, carrear no botão C1 para focar

Afinações para o Mavic...

Flight planner

2021-02-07T15:33:05Z

Jgrocha:

=== Software ===

==== Open source software (better with drones using '''PX4''' or '''ArduPilot''' controllers) ====

* [https://www.dronecode.org/ Dronecode Foundation]
** [http://qgroundcontrol.com/ QGroundControl] Qt based application
*** QGroundControl uses the MavLink control and provides full flight control and vehicle setup for '''PX4''' or '''ArduPilot''' powered vehicles.
*** [https://github.com/The1only/rosettadrone Drone Rosetta] is a proxy to the MavLink protocol enabling to use apps like QGroundControl to plan missions. With Drone Rosetta, it is possible to control DJI drones using QGroundControl.

* Airdata

==== Legacy software ====

PIX4DCapture

DroneDeploy

Drone Harmony

'''Dronelink'''

* Mapping Plans: $ 20,00 one time
** Support AGL (ground level) (terrain follow) - Uses ESRI
* [https://www.youtube.com/watch?v=Hley9DDEDdw Gound level usage] by Erik, from DroneLink
* [https://www.youtube.com/watch?v=zsZMyRYfOaA Tutorial Castellano] Boa introdução

'''Red Waypoint'''

* [http://redwaypoint.com Red Waypoint] $16.99
** Terrain follow

Litchi

* [https://flylitchi.com/ Litchi for DJI Mavic / Phantom / Inspire / Spark] 25,99 €

https://flylitchi.com/hub

=== Forums ===

* [https://mavicpilots.com/forums/mavic-2-pro.68/ Mavic 2 Pro]

=== Tips ===

Quando o drone está na altura do voo, carrear no botão C1 para focar

Afinações para o Mavic...

Flight planner

2021-02-07T00:25:00Z

Jgrocha:

PIX4DCapture

Drone Harmony

=== Focus ===

Quando o drone está na altura do voo, carrear no botão C1 para focar

Afinações para o Mavic...

Flight planner

2021-02-07T00:24:38Z

Jgrocha:

PIX4DCapture

=== Focus ===

Quando o drone está na altura do voo, carrear no botão C1 para focar

Afinações para o Mavic...

Main Page

2020-03-28T00:10:51Z

Jgrocha: /* Portal do Arqueólogo */

= Apresentação =

A formação e a disponibilização de conteúdos faz parte do ADN da Geomaster. Neste espaço, estamos a juntar todos os conteúdos das nossas formações, que ainda estão dispersos por vários sítios.

== Onde e como pedir ajuda? ==

[https://lists.osgeo.org/mailman/listinfo/portugal Lista portuguesa da OSGeo]

[https://lists.osgeo.org/mailman/listinfo/qgis-user Lista internacional do QGIS]

https://gis.stackexchange.com/

A Geomaster está oferecer suporte ao QGIS, de forma gratuita. Use o centro de suporte disponível em [https://ticket.geomaster.pt/open.php?lang=pt_PT ticket.geomaster.pt].

Antes de pedir ajuda, faça o trabalho de casa. Pesquise na net se a questão já foi levantada e resolvida.

Para procurar nas listas do QGIS, use o endereço: http://osgeo-org.1560.x6.nabble.com/QGIS-f4099105.html

= Requisitos =

Para fazer os exercícios propostos, precisa de ter algum espaço livre e o software necessário instalado. Os exercícios são independentes do sistema operativo: tanto pode usar Linux, Windows ou macOS.

== Máquina virtual OSGeo Live ==

Uma boa alternativa para a formação é a utilização da máquina virtual [https://live.osgeo.org/en/index.html OSGeo Live] que já tem todo o software SIG necessário.

= Conteúdos =

== Sentinel-2 Image processing using QGIS+SCP ==

Notes from Sentinel-2 Image processing using QGIS+SCP course at Skovskolen, Nødebo.

Documentation:

[https://readthedocs.org/projects/semiautomaticclassificationmanual/downloads/pdf/latest/ Semi-Automatic Classification Plugin Documentation]

[[Installing SCP in Ubuntu]]

[[Create a Copernicus Open Access Hub account]]

[[Search and download Sentinel-2 images]]

[[Search and download Landsat 8 images]]

[[Radiance to reflectance]]

[[Clip Sentinel-2 images]]

[[Band compositions]]

[[Export band compositions]]

[[Raster algebra: calculating indexes]]

[[Unsupervised classification]]

[[Supervised classification]]

=== Links ===

https://earth.esa.int/web/sentinel/technical-guides/sentinel-2-msi/msi-instrument

http://esa-sen4cap.org/content/eo-products

https://sentinel.esa.int/web/sentinel/user-guides/sentinel-2-msi/document-library

https://www.indexdatabase.de/db/s-single.php?id=96

https://land.copernicus.eu/global/products/ba

https://fromgistors.blogspot.com/2016/11/from-image-download-to-ndvi-calculation.html

http://www.qgis.pt/blog/2016/12/14/detecao-remota-com-o-qgis/ (em Português)

== Wikidata Sixth Birthday ==

[[File:Birthday banner for 4th Wikidata Birthday.png]]

=== Objectivo ===

Fazer uma mapa:
# Mostrar as ruas, largos, praças e outros espaços com topónimos
# Poder filtrar por:
## sexo
## ocupação (religioso, militar poeta, escritor, político...
## século
## etc

Eventualmente, fazer um quantos gráficos, com percentagens:
# topónimos com nome de pessoas versus outras origens
# nomes de mulheres versus nomes de homens
# políticos versus artes e ciências

=== Problema ===

No OpenStreetMap não existe informação sobre as propriedades do topónimo. O topónimo pode estar escrito de diversas formas e contém partes que não interessam (Rua, Avenida, Prof, Doutor, etc). (Nota: cruzar com o dataset da [http://centraldedados.pt/codigos_postais/ Central de Dados dos Códigos Postais]).

A [https://www.openstreetmap.org/way/35997529#map=16/41.1809/-8.6094 Rua de São Tomé] refere-se a uma pessoa?

Rua Egas Moniz. Qual [https://pt.wikipedia.org/wiki/Egas_Moniz Egas Moniz]?

==== Solução ====

Wikidata! Diferença entre a página da [https://pt.wikipedia.org/wiki/Ant%C3%B3nio_Egas_Moniz Wikipédia do Egas Moniz] e a da [https://www.wikidata.org/wiki/Q273219 Wikidata da mesma pessoa].

Criei a entidade: https://www.wikidata.org/wiki/Q58129518

No OpenStreetMap já se usa uma tag [https://wiki.openstreetmap.org/wiki/Key:wikidata wikidata] para entidades geográficas bem conhecidas, como a [https://www.openstreetmap.org/way/247168260 Torre dos Clérigos].

Existe uma proposta para acrescentar a origem de um determinado nome, usando a tag [https://wiki.openstreetmap.org/wiki/Key:name:etymology name:etymology].

==== Limitações ====

Nem tudo está na Wikidata. Na verdade, existe pouca informação (sobre Portugal) no Wikidata.

No OpenStreetMap também não há muitas tags wikidata.

==== Resolução das limitações ====

'''Editar o OpenStreetMap e a Wikidata!'''

Nota: área pantanosa em relação às licenças: CC-0 versus ODBL.

==== Outras fontes de dados ====

Central de dados

http://centraldedados.pt/nomes_proprios/

https://genderize.io/

==== Algum código de base ====

https://gitlab.com/pdiasalmeida/osm-street-names

== Open Data Day, 2018 ==

[[File:Logo odd 2018.png]]

[[Introdução ao OpenStreetMap]]

[[Serviços sobre os dados do OpenStreetMap]]

[[Dados OpenStreetMap no QGIS]]

[[Dados OpenStreetMap no PostgreSQL]]

[[OpenStreetMap API]]

[[Routing com os dados do OpenStreetMap]]

== SIG desktop com QGIS ==

Introdução à interface do QGIS, a visualização complementar de geometrias e dados, filtrar, selecionar, expressões, trabalhar com a seleção, etc.

[[Instalação QGIS no Windows com base no OSGeo4W]]

Instalação da primeira extensão [https://plugins.qgis.org/plugins/quick_map_services/ QuickMapServices].

Os dados vectoriais referem-se a entidades que têm uma componente espacial (geográfica) e um conjunto de atributos.

[[Explorar dados vectoriais]]

[[Georreferenciação de imagens e criação de camadas]]

[[Edição de dados vetoriais]]

[[Geração de um modelo digital do terreno]]

Acrescentar melhorias aos formulários:
# campos que se atualizam automaticamente
# joins e formulários com combox
# um exemplo de uma relação master → detail

[[Ligação a uma base de dados Postgresql]]

[[Análise espacial com rasters]]

==== Para rever ou eliminar... ====

[[Geoprocessamento]]

[[Criar camadas vectoriais]]

Os dados raster referem-se a superfícies contínuas, cujas propriedades se vão alterando ao longo da superfície.

Visualizar dados raster, calculadora raster, calcular o aspecto, declives, mostrar um perfil.

[[Explorar dados raster]]

Cruzar camadas, associar imagens, associar ações a entidades geográficas

[[Cruzar dados vectoriais]]

Introdução à análise espacial: cálculo de áreas de influência, recorte em função da localização, etc.

[[Introdução à análise espacial]]

[[Georreferenciação de mapas]]

[[Criação de camadas]]

[[Teste de auto-avaliação]]

== SIG desktop com QGIS: Tópicos avançados ==

[[Exercício de aquecimento]]

[[QGIS com Postgresql]]

[[Edição de informação geográfica]]

O processamento com o QGIS é tão assustador como fabuloso. Assustador pela diversidade de alternativas que apresenta e fabuloso pela mesma razão. Além de todas as capacidades de processamento que tem no próprio código, O QGIS liga-se muito bem a outros software de processamento, como o GRASS, SAGA, Orfeo Toolbox, etc.

[[Processamento em QGIS]]

As imagens Sentinel são disponibilizadas pela ESA. O tratamento de imagens Sentinel-2 com a extensão [https://fromgistors.blogspot.com/p/semi-automatic-classification-plugin.html Semi-Automatic Classification Plugin]

[[Tratamento de imagens Sentinel]]

As imagens raster podem ser geridas a partir do sistema de ficheiros ou a partir da base de dados Postgresql.

[[Suporte Postgresql para rasters]]

O QGIS está escrito em C++ que é uma linguagem orientado a objetos, que gera código muito eficiente. O QGIS usa a biblioteca QT para todas as componentes de interface com o utilizador.
Embora todo o núcleo esteja em C++, todas as funcionalidades são expostas para outras aplicações através de uma API que pode ser invocada a partir do Python. Ou seja, a partir de um programa Python, podemos comandar o QGIS e tirar partido de todas as suas funcionalidades.

[[Explorar o QGIS a partir do Python]]

[[QField: o QGIS ao ar livre]]

[[Sobre a preparação desta formação]]

== Base de dados espaciais com Postgresql ==

== Data ==

[https://resourcewatch.org/ Resource Watch – Monitoring the Planet's Pulse]

== Spatial Data Mining ==

* [https://geodacenter.github.io/ GeoDa] is a free and open source software tool that serves as an introduction to spatial data analysis.
* [https://github.com/MapPlus/spatial_statistics_for_geotools_udig GeoAnalysis library] is a java-based open source for geospatial analysis.

== QGIS na área da Saúde ==

[https://plugins.qgis.org/plugins/GeoHealth/ Plugin GeoHealth]

== QGIS na área da Arqueologia ==

Tratamento dos arqueossítios em http://www.geira.pt/arqueo/ListaArqueossitios.html

xml disponível em: http://www4.di.uminho.pt/~jcr/XML/didac/xmldocs/arq.xml

<syntaxhighlight lang="bash">
wget http://www4.di.uminho.pt/~jcr/XML/didac/xmldocs/arq.xml
xsltproc sample.xsl arq.xml > arq.csv
</syntaxhighlight>

<syntaxhighlight lang="xml">
<?xml version="1.0"?>
<xsl:stylesheet version="1.0" xmlns:xsl="http://www.w3.org/1999/XSL/Transform">
<xsl:output type="text" indent="no" omit-xml-declaration="yes" />
<xsl:strip-space elements="*" />

<xsl:template match="//ARQELEM">
<xsl:value-of select="normalize-space(IDENTI)"/>|<xsl:value-of select="normalize-space(DESCRI)"/>|<xsl:value-of select="normalize-space(CRONO)"/>|<xsl:value-of select="normalize-space(FREGUE)"/>|<xsl:value-of select="normalize-space(CONCEL)"/>|<xsl:value-of select="normalize-space(LATITU)"/>|<xsl:value-of select="normalize-space(LONGIT)"/>|<xsl:value-of select="normalize-space(ALTITU)"/>|<xsl:value-of select="normalize-space(ACESSO)"/>|<xsl:value-of select="normalize-space(QUADRO)"/>|<xsl:value-of select="normalize-space(TRAARQ)"/>|<xsl:value-of select="normalize-space(DESARQ)"/>|<xsl:value-of select="normalize-space(INTERP)"/><xsl:text>
</xsl:text>
</xsl:template>
</xsl:stylesheet>
</syntaxhighlight>

Tratamento manual:

coordenadas: multiplicar por 1000

usar o separador de campos: |

usar o delimitador de campos: '

Sistemas de coordenadas: EPSG:20790

Resultado final: arqueossitios.csv

=== Portal do Arqueólogo ===

Acabei por sacar pelo QGIS, ligando-me ao servidor.

Dados de ligação:

1) É preciso criar uma nova ligação do tipo: ArcGisFeatureServer, com os seguintes dados:

Nome: Portal do Arqueólogo

URL: https://services8.arcgis.com/ITVSIrZ4rxt6SbBo/arcgis/rest/services/Sitios_20190207_visualização/FeatureServer

==== Sacar lista de sítios ====

<syntaxhighlight lang="bash">
#!/bin/bash

mkdir -p portalarqueologo
for i in {1..1735}
do
curl "http://arqueologia.patrimoniocultural.pt/index.php?sid=sitios&p=$i" -o portalarqueologo/$i.html
done
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd portalarqueologo/
sed -n -e 's/<td data-label="Designação"><a href="\/index.php?sid=sitios\&subsid=$[0-9]\+$">$[^<]\+$<\/a><\/td>/\1\t\2\thttp:\/\/arqueologia.patrimoniocultural.pt\/index.php?sid=sitios\&subsid=\1/p' *.html | sed 's/^\s\+//g' > lista_sitios.csv
</syntaxhighlight>

==== Sacar sítios ====

==== Extrair coordenadas ====

jgr@zoe:~/bin/sitios$ grep '<div id="singleListingMap" data-latitude="[^"]\+" data-longitude="[^"]\+" data-map-icon' *.html > x

sed -n -e 's/$^[0-9]\+$.html:\s\+<div id="singleListingMap" data-latitude="$[0-9.]\+$" data-longitude="$[-0-9.]\+$".\+$/\1\t\2\t\3/p' x

<h2>Monte da Matosa 2</h2> Sítio <span title="CNS">(13709)</span>

grep '<h2>[^<]\+</h2> Sítio <span title="CNS">([\d]\+)</span>' *.html

==== QGIS ====

Abrir lista_sitios.csv

Abrir

== Dados do OpenStreetMap ==

* Introdução ao OpenStreetMap
* Dados do OpenStreetMap no QGIS
* Dados do OpenStreetMap no Postgresql
* Queries com OverPass API, http://overpass-turbo.eu/
* Routing com os dados do OpenStreetMap (OpenTripPlanner)
* Routing com MAPS.ME
* Usar os mapas do OpenStreetMap num blog

=== Requisitos ===

* Computador c/ algum espaço livre
* Dados: serão descarregados na hora, a partir de: http://openstreetmap.pt/wp-content/uploads/
* Software
** QGIS 2.18.17 LTR
** Postgresql v9.6 + PostGIS (não é preciso instalar; haverá um servidor na sala)
** Instalar o MAPS.ME no telemóvel

== Publicação na Web com Geoserver ==

[[Servidores de mapas: conceitos]]

[[Instalação do Geoserver]]

[[Disponibilização de uma camada WMS/WFS]]

[[Disponibilização de uma camada WMTS]]

[[Publicação de grupos]]

== Publicação na Web com uMap ==

A plataforma uMap permite criar mapas de uma forma simples. Os mapas criados podem ser incorporados num blog ou num site.

[[O meu primeiro mapa com o uMap]]

== Drones ==

[[DJI MAVIC 2 PRO]]

[[Flight planner]]

[[Running OpenDroneMap]]

== Contribuir para projectos Open Source no domínio dos SIG ==

[[Contribuir para o Nominatim]]

[[Contribuir para o QGIS]]

[[Contribuir para plugins QGIS]]

[[Contribuir para o OpenTripPlanner]]

[[Contribuir para o GeoExt]]

[[Contribuir para o PostGIS]]

[[Contribuir para o curso PostGIS com Rasters]]

= Outros cursos e recursos =

[http://training.gismentors.eu/isprs-summer-school-2016/index.html ISPRS Congress 2016 Summer School]

[http://training.gismentors.eu/grass-gis-workshop-jena-2018/index.html GRASS GIS Workshop in Jena]

[https://www.hatarilabs.com/ih-en/working-with-sentinel-2-imagery-on-qgis Working with Sentinel 2 Imagery on QGIS]

[https://uwgis.wordpress.com/gis-practicals/flood-risk-mapping/ QGIS Flood Risk Mapping]

[[Spatial-Temporal Data Analysis]]

[[Geospatial Data Mining]]

[[Como gravar cursos em vídeo]]

= Propostas =

[[QGIS: Generalização Cartográfica]], em parceria com IBGE

[[QGIS: Deteção de estradas em imagens Sentinel-2]], em parceria com IBGE

[[QGIS: Ler cartas náuticas]], em parceria com a comunidade QGIS e de acordo com esta [https://github.com/faunalia/qnavigate proposta de melhoramento]

[[QGIS: Carregar informação meteorológica]], em parceria com a comunidade QGIS e de acordo com esta [https://github.com/faunalia/qnavigate proposta de melhoramento]

[[QGIS:Plugin para dados do INE]]

[[QGIS:Plugin para sobre a Saúde em Portugal]]

= Modelo Topográfico =

http://www.dgterritorio.gov.pt/recart/TRANSPORTES%20(Transporte%20rodovi%C3%A1rio)/CatalogoDasViasRodoviariasParte2.html

http://www.dgterritorio.gov.pt/recart/TRANSPORTES%20(Transporte%20rodovi%C3%A1rio)/CatalogoDasViasRodoviariasParte2UTF-8_20190703.csv

<pre>
vi sed.txt

1s/codigoViaRodov/codigo_via_rodov/
1s/tipoViaRodovC/tipo_rodovia_c/
1s/codigoDGT/codigo_dgt/
1s/codigoArruamento/codigo_arruamento/
1s/tipoViaRodovD/tipo_rodovia_d/
1s/tipoViaRodovAbv/tipo_rodovia_abv/
1s/nomeSufixo/nome_sufixo/
1s/nomeAlternativo/nome_alternativo/
1s/pontosExtremoseIntermedios/pontos_extremos_e_intermedios/
1s/lugarINEcod/lugar_ine_cod/
1s/fonteAquisicaoDados/fonte_aquisicao_dados/
1s/dataEdital/data_edital/
1s/DICOFRE/dicofre/
1s/DICO/dico/
1s/DI/di/
1s/CO/co/
1s/dataCat/data_cat/

sed -f sed.txt -i CatalogoDasViasRodoviariasParte2UTF-8_20190703.csv
</pre>

Como gravar cursos em vídeo

2020-03-26T23:51:18Z

Jgrocha:

=== Aplicações ===

==== Screen capture ====

RecordMyDesktop - Só a área da janela da aplicação (QGIS, Firefox, etc). Nas opções retirar as decorações (da janela).

Por o fundo do desktop amarelo

Preparar a janela

Usar a resolução 1280x720

<del>Usar a resolução 1366x768 ''(Standardized HDTV 720p/1080i displays or “HD ready”, used in most cheaper notebooks)''</del>

<syntaxhighlight lang="bash">
sudo apt install wmctrl

jgr@zoe:~/dev/scrcpy/x$ wmctrl -lG
0x02200002 -1 7054 54 313 763 zoe conky (zoe)
0x05a00010 0 1930 64 1808 1052 zoe command line - How do I find the window dimensions and position accurately including decorations? - Unix & Linux Stack Exchange - Mozilla Firefox
0x06c00006 0 10 91 960 1025 zoe jgr@zoe: ~/dev/scrcpy/x
0x07a00003 0 87 171 567 692 zoe Controlo de Volume
0x06009d29 0 3964 96 1299 939 zoe Formulários
0x06e00010 0 440 208 1280 720 N/A *exercicio - QGIS 6a2c31d897
0x0605e92f 0 -72 -10 1583 1097 zoe Pasta pessoal
0x07800017 0 0 83 1920 1025 N/A Untitled* / HD 1080p 25 fps — Kdenlive
0x06c0672a 0 34 566 654 434 zoe jgr@zoe: ~

wmctrl -r "Untitled Project - QGIS 6a2c31d897" -e 0,633,265,1280,720
</syntaxhighlight>

==== Anotações no ecrã ====

http://manpages.ubuntu.com/manpages/cosmic/man1/gromit-mpx.1.html

sudo apt install gromit-mpx

Começa: F9
Shift F9
draw/Shift draw

==== Telemóvel como WebCam ====

Usar o [https://github.com/Genymobile/scrcpy scrcpy] para controlar a câmara.

Instalar a partir das sources ou com snap

<syntaxhighlight lang="bash">
cd ~/dev/scrcpy
git pull origin master
rm -rf x
export ANDROID_HOME=~/Android/Sdk
meson x --buildtype release --strip -Db_lto=true
cd x
ninja
sudo ninja install
</syntaxhighlight>

[[File:Captura de ecrã de 2018-11-18 16-50-59.png]]

Ligar por Wifi (na mesma rede)

Começar com a ligação por USB, para configurar o <syntaxhighlight lang="bash" inline>adb</syntaxhighlight>.

Ligar USB. (Tem que se permitir "Depuração por USB", nas "Opções do programador")

<syntaxhighlight lang="bash">
jgr@zoe:~$ adb devices
List of devices attached
ce071717210b872104 device

adb disconnect

# then choose one of these depending on how you are connecting to your device
# adb usb // for usb
# adb tcpip 5555 // for adb over wifi
</syntaxhighlight>

Descobrir o IP do telefone

<syntaxhighlight lang="bash">
jgr@zoe:~$ arp -a
unknown80b234059058.lan (192.168.1.65) em 80:b2:34:05:90:58 [ether] em wlp2s0
vodafonegw (192.168.1.1) em 50:1d:93:b8:f6:21 [ether] em wlp2s0
Sternschanze.lan (192.168.1.66) em 24:18:1d:0e:c3:66 [ether] em wlp2s0

adb tcpip 5555
adb connect 192.168.1.66:5555

# desligar o cabo USB (para não ter dois devices, um por USB e outro por rede)

scrcpy
</syntaxhighlight>

==== Kdenlive ====

==== Audacity ====

=== Hardware ===

Microfone - KIMU PRO: ligar ao telemóvel

Webcam: usar a câmara do telemóvel

Computador

=== Guiões ===

[[Curso de QGIS]]

Explorar o QGIS a partir do Python

2020-01-28T14:37:40Z

Jgrocha:

https://courses.spatialthoughts.com/pyqgis-in-a-day.html#set-canvas-extent-to-a-layer-extent

QGIS 3 standalone Python script

https://gist.github.com/jgrocha/d75d50305e49ba044ff84e96a28f4ed8

<syntaxhighlight lang="python">
#import re
#for alg in QgsApplication.processingRegistry().algorithms():
# if re.match('.*Clip.*', alg.displayName()):
# # gdal:cliprasterbymasklayer
# print(alg.id(), "->", alg.displayName())

# processing.algorithmHelp("gdal:cliprasterbymasklayer")

base_layer = iface.activeLayer()
# features = layer.getFeatures()

# 'selectedFeaturesOnly': False
# QgsProcessingFeatureSourceDefinition(base_layer.id(), False)

processing.run("native:buffer",
{'INPUT': QgsProcessingFeatureSourceDefinition(base_layer.id(), False),
'DISTANCE': 100.0,
'SEGMENTS': 10,
'DISSOLVE': True,
'END_CAP_STYLE': 0,
'JOIN_STYLE': 0,
'MITER_LIMIT': 10,
'OUTPUT': '/tmp/buffers.shp'})

</syntaxhighlight>

Spatial-Temporal Data Analysis

2020-01-15T23:42:38Z

Jgrocha: Created page with " === Datasets === [https://marinecadastre.gov/ais/ Vessel Traffic Data] === Software === Postgresql QGIS + Time manager plugin [http://madlib.apache.org/ Apache MADlib: B..."

=== Datasets ===

[https://marinecadastre.gov/ais/ Vessel Traffic Data]

=== Software ===

Postgresql

QGIS + Time manager plugin

[http://madlib.apache.org/ Apache MADlib: Big Data Machine Learning in SQL]

[https://www.knime.com/knime-analytics-platform KNIME platform (open source)]

=== Machine Learning ===

[https://www.cs.waikato.ac.nz/ml/weka/ WEKA The workbench for machine learning]

Main Page

2020-01-15T23:08:52Z

Jgrocha: /* Outros cursos e recursos */

= Apresentação =

A formação e a disponibilização de conteúdos faz parte do ADN da Geomaster. Neste espaço, estamos a juntar todos os conteúdos das nossas formações, que ainda estão dispersos por vários sítios.

== Onde e como pedir ajuda? ==

[https://lists.osgeo.org/mailman/listinfo/portugal Lista portuguesa da OSGeo]

[https://lists.osgeo.org/mailman/listinfo/qgis-user Lista internacional do QGIS]

https://gis.stackexchange.com/

A Geomaster está oferecer suporte ao QGIS, de forma gratuita. Use o centro de suporte disponível em [https://ticket.geomaster.pt/open.php?lang=pt_PT ticket.geomaster.pt].

Antes de pedir ajuda, faça o trabalho de casa. Pesquise na net se a questão já foi levantada e resolvida.

Para procurar nas listas do QGIS, use o endereço: http://osgeo-org.1560.x6.nabble.com/QGIS-f4099105.html

= Requisitos =

Para fazer os exercícios propostos, precisa de ter algum espaço livre e o software necessário instalado. Os exercícios são independentes do sistema operativo: tanto pode usar Linux, Windows ou macOS.

== Máquina virtual OSGeo Live ==

Uma boa alternativa para a formação é a utilização da máquina virtual [https://live.osgeo.org/en/index.html OSGeo Live] que já tem todo o software SIG necessário.

= Conteúdos =

== Sentinel-2 Image processing using QGIS+SCP ==

Notes from Sentinel-2 Image processing using QGIS+SCP course at Skovskolen, Nødebo.

Documentation:

[https://readthedocs.org/projects/semiautomaticclassificationmanual/downloads/pdf/latest/ Semi-Automatic Classification Plugin Documentation]

[[Installing SCP in Ubuntu]]

[[Create a Copernicus Open Access Hub account]]

[[Search and download Sentinel-2 images]]

[[Search and download Landsat 8 images]]

[[Radiance to reflectance]]

[[Clip Sentinel-2 images]]

[[Band compositions]]

[[Export band compositions]]

[[Raster algebra: calculating indexes]]

[[Unsupervised classification]]

[[Supervised classification]]

=== Links ===

https://earth.esa.int/web/sentinel/technical-guides/sentinel-2-msi/msi-instrument

http://esa-sen4cap.org/content/eo-products

https://sentinel.esa.int/web/sentinel/user-guides/sentinel-2-msi/document-library

https://www.indexdatabase.de/db/s-single.php?id=96

https://land.copernicus.eu/global/products/ba

https://fromgistors.blogspot.com/2016/11/from-image-download-to-ndvi-calculation.html

http://www.qgis.pt/blog/2016/12/14/detecao-remota-com-o-qgis/ (em Português)

== Wikidata Sixth Birthday ==

[[File:Birthday banner for 4th Wikidata Birthday.png]]

=== Objectivo ===

Fazer uma mapa:
# Mostrar as ruas, largos, praças e outros espaços com topónimos
# Poder filtrar por:
## sexo
## ocupação (religioso, militar poeta, escritor, político...
## século
## etc

Eventualmente, fazer um quantos gráficos, com percentagens:
# topónimos com nome de pessoas versus outras origens
# nomes de mulheres versus nomes de homens
# políticos versus artes e ciências

=== Problema ===

No OpenStreetMap não existe informação sobre as propriedades do topónimo. O topónimo pode estar escrito de diversas formas e contém partes que não interessam (Rua, Avenida, Prof, Doutor, etc). (Nota: cruzar com o dataset da [http://centraldedados.pt/codigos_postais/ Central de Dados dos Códigos Postais]).

A [https://www.openstreetmap.org/way/35997529#map=16/41.1809/-8.6094 Rua de São Tomé] refere-se a uma pessoa?

Rua Egas Moniz. Qual [https://pt.wikipedia.org/wiki/Egas_Moniz Egas Moniz]?

==== Solução ====

Wikidata! Diferença entre a página da [https://pt.wikipedia.org/wiki/Ant%C3%B3nio_Egas_Moniz Wikipédia do Egas Moniz] e a da [https://www.wikidata.org/wiki/Q273219 Wikidata da mesma pessoa].

Criei a entidade: https://www.wikidata.org/wiki/Q58129518

No OpenStreetMap já se usa uma tag [https://wiki.openstreetmap.org/wiki/Key:wikidata wikidata] para entidades geográficas bem conhecidas, como a [https://www.openstreetmap.org/way/247168260 Torre dos Clérigos].

Existe uma proposta para acrescentar a origem de um determinado nome, usando a tag [https://wiki.openstreetmap.org/wiki/Key:name:etymology name:etymology].

==== Limitações ====

Nem tudo está na Wikidata. Na verdade, existe pouca informação (sobre Portugal) no Wikidata.

No OpenStreetMap também não há muitas tags wikidata.

==== Resolução das limitações ====

'''Editar o OpenStreetMap e a Wikidata!'''

Nota: área pantanosa em relação às licenças: CC-0 versus ODBL.

==== Outras fontes de dados ====

Central de dados

http://centraldedados.pt/nomes_proprios/

https://genderize.io/

==== Algum código de base ====

https://gitlab.com/pdiasalmeida/osm-street-names

== Open Data Day, 2018 ==

[[File:Logo odd 2018.png]]

[[Introdução ao OpenStreetMap]]

[[Serviços sobre os dados do OpenStreetMap]]

[[Dados OpenStreetMap no QGIS]]

[[Dados OpenStreetMap no PostgreSQL]]

[[OpenStreetMap API]]

[[Routing com os dados do OpenStreetMap]]

== SIG desktop com QGIS ==

Introdução à interface do QGIS, a visualização complementar de geometrias e dados, filtrar, selecionar, expressões, trabalhar com a seleção, etc.

[[Instalação QGIS no Windows com base no OSGeo4W]]

Instalação da primeira extensão [https://plugins.qgis.org/plugins/quick_map_services/ QuickMapServices].

Os dados vectoriais referem-se a entidades que têm uma componente espacial (geográfica) e um conjunto de atributos.

[[Explorar dados vectoriais]]

[[Georreferenciação de imagens e criação de camadas]]

[[Edição de dados vetoriais]]

[[Geração de um modelo digital do terreno]]

Acrescentar melhorias aos formulários:
# campos que se atualizam automaticamente
# joins e formulários com combox
# um exemplo de uma relação master → detail

[[Ligação a uma base de dados Postgresql]]

[[Análise espacial com rasters]]

==== Para rever ou eliminar... ====

[[Geoprocessamento]]

[[Criar camadas vectoriais]]

Os dados raster referem-se a superfícies contínuas, cujas propriedades se vão alterando ao longo da superfície.

Visualizar dados raster, calculadora raster, calcular o aspecto, declives, mostrar um perfil.

[[Explorar dados raster]]

Cruzar camadas, associar imagens, associar ações a entidades geográficas

[[Cruzar dados vectoriais]]

Introdução à análise espacial: cálculo de áreas de influência, recorte em função da localização, etc.

[[Introdução à análise espacial]]

[[Georreferenciação de mapas]]

[[Criação de camadas]]

[[Teste de auto-avaliação]]

== SIG desktop com QGIS: Tópicos avançados ==

[[Exercício de aquecimento]]

[[QGIS com Postgresql]]

[[Edição de informação geográfica]]

O processamento com o QGIS é tão assustador como fabuloso. Assustador pela diversidade de alternativas que apresenta e fabuloso pela mesma razão. Além de todas as capacidades de processamento que tem no próprio código, O QGIS liga-se muito bem a outros software de processamento, como o GRASS, SAGA, Orfeo Toolbox, etc.

[[Processamento em QGIS]]

As imagens Sentinel são disponibilizadas pela ESA. O tratamento de imagens Sentinel-2 com a extensão [https://fromgistors.blogspot.com/p/semi-automatic-classification-plugin.html Semi-Automatic Classification Plugin]

[[Tratamento de imagens Sentinel]]

As imagens raster podem ser geridas a partir do sistema de ficheiros ou a partir da base de dados Postgresql.

[[Suporte Postgresql para rasters]]

O QGIS está escrito em C++ que é uma linguagem orientado a objetos, que gera código muito eficiente. O QGIS usa a biblioteca QT para todas as componentes de interface com o utilizador.
Embora todo o núcleo esteja em C++, todas as funcionalidades são expostas para outras aplicações através de uma API que pode ser invocada a partir do Python. Ou seja, a partir de um programa Python, podemos comandar o QGIS e tirar partido de todas as suas funcionalidades.

[[Explorar o QGIS a partir do Python]]

[[QField: o QGIS ao ar livre]]

[[Sobre a preparação desta formação]]

== Base de dados espaciais com Postgresql ==

== Data ==

[https://resourcewatch.org/ Resource Watch – Monitoring the Planet's Pulse]

== Spatial Data Mining ==

* [https://geodacenter.github.io/ GeoDa] is a free and open source software tool that serves as an introduction to spatial data analysis.
* [https://github.com/MapPlus/spatial_statistics_for_geotools_udig GeoAnalysis library] is a java-based open source for geospatial analysis.

== QGIS na área da Saúde ==

[https://plugins.qgis.org/plugins/GeoHealth/ Plugin GeoHealth]

== QGIS na área da Arqueologia ==

Tratamento dos arqueossítios em http://www.geira.pt/arqueo/ListaArqueossitios.html

xml disponível em: http://www4.di.uminho.pt/~jcr/XML/didac/xmldocs/arq.xml

<syntaxhighlight lang="bash">
wget http://www4.di.uminho.pt/~jcr/XML/didac/xmldocs/arq.xml
xsltproc sample.xsl arq.xml > arq.csv
</syntaxhighlight>

<syntaxhighlight lang="xml">
<?xml version="1.0"?>
<xsl:stylesheet version="1.0" xmlns:xsl="http://www.w3.org/1999/XSL/Transform">
<xsl:output type="text" indent="no" omit-xml-declaration="yes" />
<xsl:strip-space elements="*" />

<xsl:template match="//ARQELEM">
<xsl:value-of select="normalize-space(IDENTI)"/>|<xsl:value-of select="normalize-space(DESCRI)"/>|<xsl:value-of select="normalize-space(CRONO)"/>|<xsl:value-of select="normalize-space(FREGUE)"/>|<xsl:value-of select="normalize-space(CONCEL)"/>|<xsl:value-of select="normalize-space(LATITU)"/>|<xsl:value-of select="normalize-space(LONGIT)"/>|<xsl:value-of select="normalize-space(ALTITU)"/>|<xsl:value-of select="normalize-space(ACESSO)"/>|<xsl:value-of select="normalize-space(QUADRO)"/>|<xsl:value-of select="normalize-space(TRAARQ)"/>|<xsl:value-of select="normalize-space(DESARQ)"/>|<xsl:value-of select="normalize-space(INTERP)"/><xsl:text>
</xsl:text>
</xsl:template>
</xsl:stylesheet>
</syntaxhighlight>

Tratamento manual:

coordenadas: multiplicar por 1000

usar o separador de campos: |

usar o delimitador de campos: '

Sistemas de coordenadas: EPSG:20790

Resultado final: arqueossitios.csv

=== Portal do Arqueólogo ===

Acabei por sacar pelo QGIS, ligando-me ao servidor.

Dados de ligação:

==== Sacar lista de sítios ====

<syntaxhighlight lang="bash">
#!/bin/bash

mkdir -p portalarqueologo
for i in {1..1735}
do
curl "http://arqueologia.patrimoniocultural.pt/index.php?sid=sitios&p=$i" -o portalarqueologo/$i.html
done
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd portalarqueologo/
sed -n -e 's/<td data-label="Designação"><a href="\/index.php?sid=sitios\&subsid=$[0-9]\+$">$[^<]\+$<\/a><\/td>/\1\t\2\thttp:\/\/arqueologia.patrimoniocultural.pt\/index.php?sid=sitios\&subsid=\1/p' *.html | sed 's/^\s\+//g' > lista_sitios.csv
</syntaxhighlight>

==== Sacar sítios ====

==== Extrair coordenadas ====

jgr@zoe:~/bin/sitios$ grep '<div id="singleListingMap" data-latitude="[^"]\+" data-longitude="[^"]\+" data-map-icon' *.html > x

sed -n -e 's/$^[0-9]\+$.html:\s\+<div id="singleListingMap" data-latitude="$[0-9.]\+$" data-longitude="$[-0-9.]\+$".\+$/\1\t\2\t\3/p' x

<h2>Monte da Matosa 2</h2> Sítio <span title="CNS">(13709)</span>

grep '<h2>[^<]\+</h2> Sítio <span title="CNS">([\d]\+)</span>' *.html

==== QGIS ====

Abrir lista_sitios.csv

Abrir

== Dados do OpenStreetMap ==

* Introdução ao OpenStreetMap
* Dados do OpenStreetMap no QGIS
* Dados do OpenStreetMap no Postgresql
* Queries com OverPass API, http://overpass-turbo.eu/
* Routing com os dados do OpenStreetMap (OpenTripPlanner)
* Routing com MAPS.ME
* Usar os mapas do OpenStreetMap num blog

=== Requisitos ===

* Computador c/ algum espaço livre
* Dados: serão descarregados na hora, a partir de: http://openstreetmap.pt/wp-content/uploads/
* Software
** QGIS 2.18.17 LTR
** Postgresql v9.6 + PostGIS (não é preciso instalar; haverá um servidor na sala)
** Instalar o MAPS.ME no telemóvel

== Publicação na Web com Geoserver ==

[[Servidores de mapas: conceitos]]

[[Instalação do Geoserver]]

[[Disponibilização de uma camada WMS/WFS]]

[[Disponibilização de uma camada WMTS]]

[[Publicação de grupos]]

== Publicação na Web com uMap ==

A plataforma uMap permite criar mapas de uma forma simples. Os mapas criados podem ser incorporados num blog ou num site.

[[O meu primeiro mapa com o uMap]]

== Drones ==

[[DJI MAVIC 2 PRO]]

[[Flight planner]]

[[Running OpenDroneMap]]

== Contribuir para projectos Open Source no domínio dos SIG ==

[[Contribuir para o Nominatim]]

[[Contribuir para o QGIS]]

[[Contribuir para plugins QGIS]]

[[Contribuir para o OpenTripPlanner]]

[[Contribuir para o GeoExt]]

[[Contribuir para o PostGIS]]

[[Contribuir para o curso PostGIS com Rasters]]

= Outros cursos e recursos =

[http://training.gismentors.eu/isprs-summer-school-2016/index.html ISPRS Congress 2016 Summer School]

[http://training.gismentors.eu/grass-gis-workshop-jena-2018/index.html GRASS GIS Workshop in Jena]

[https://www.hatarilabs.com/ih-en/working-with-sentinel-2-imagery-on-qgis Working with Sentinel 2 Imagery on QGIS]

[https://uwgis.wordpress.com/gis-practicals/flood-risk-mapping/ QGIS Flood Risk Mapping]

[[Spatial-Temporal Data Analysis]]

[[Geospatial Data Mining]]

[[Como gravar cursos em vídeo]]

= Propostas =

[[QGIS: Generalização Cartográfica]], em parceria com IBGE

[[QGIS: Deteção de estradas em imagens Sentinel-2]], em parceria com IBGE

[[QGIS: Ler cartas náuticas]], em parceria com a comunidade QGIS e de acordo com esta [https://github.com/faunalia/qnavigate proposta de melhoramento]

[[QGIS: Carregar informação meteorológica]], em parceria com a comunidade QGIS e de acordo com esta [https://github.com/faunalia/qnavigate proposta de melhoramento]

[[QGIS:Plugin para dados do INE]]

[[QGIS:Plugin para sobre a Saúde em Portugal]]

= Modelo Topográfico =

http://www.dgterritorio.gov.pt/recart/TRANSPORTES%20(Transporte%20rodovi%C3%A1rio)/CatalogoDasViasRodoviariasParte2.html

http://www.dgterritorio.gov.pt/recart/TRANSPORTES%20(Transporte%20rodovi%C3%A1rio)/CatalogoDasViasRodoviariasParte2UTF-8_20190703.csv

<pre>
vi sed.txt

1s/codigoViaRodov/codigo_via_rodov/
1s/tipoViaRodovC/tipo_rodovia_c/
1s/codigoDGT/codigo_dgt/
1s/codigoArruamento/codigo_arruamento/
1s/tipoViaRodovD/tipo_rodovia_d/
1s/tipoViaRodovAbv/tipo_rodovia_abv/
1s/nomeSufixo/nome_sufixo/
1s/nomeAlternativo/nome_alternativo/
1s/pontosExtremoseIntermedios/pontos_extremos_e_intermedios/
1s/lugarINEcod/lugar_ine_cod/
1s/fonteAquisicaoDados/fonte_aquisicao_dados/
1s/dataEdital/data_edital/
1s/DICOFRE/dicofre/
1s/DICO/dico/
1s/DI/di/
1s/CO/co/
1s/dataCat/data_cat/

sed -f sed.txt -i CatalogoDasViasRodoviariasParte2UTF-8_20190703.csv
</pre>

Explorar o QGIS a partir do Python

2019-11-18T16:57:42Z

Jgrocha:

https://courses.spatialthoughts.com/pyqgis-in-a-day.html#set-canvas-extent-to-a-layer-extent

QGIS 3 standalone Python script

https://gist.github.com/jgrocha/d75d50305e49ba044ff84e96a28f4ed8

Main Page

2019-10-03T13:36:16Z

Jgrocha: /* Propostas */

= Apresentação =

A formação e a disponibilização de conteúdos faz parte do ADN da Geomaster. Neste espaço, estamos a juntar todos os conteúdos das nossas formações, que ainda estão dispersos por vários sítios.

== Onde e como pedir ajuda? ==

[https://lists.osgeo.org/mailman/listinfo/portugal Lista portuguesa da OSGeo]

[https://lists.osgeo.org/mailman/listinfo/qgis-user Lista internacional do QGIS]

https://gis.stackexchange.com/

A Geomaster está oferecer suporte ao QGIS, de forma gratuita. Use o centro de suporte disponível em [https://ticket.geomaster.pt/open.php?lang=pt_PT ticket.geomaster.pt].

Antes de pedir ajuda, faça o trabalho de casa. Pesquise na net se a questão já foi levantada e resolvida.

Para procurar nas listas do QGIS, use o endereço: http://osgeo-org.1560.x6.nabble.com/QGIS-f4099105.html

= Requisitos =

Para fazer os exercícios propostos, precisa de ter algum espaço livre e o software necessário instalado. Os exercícios são independentes do sistema operativo: tanto pode usar Linux, Windows ou macOS.

== Máquina virtual OSGeo Live ==

Uma boa alternativa para a formação é a utilização da máquina virtual [https://live.osgeo.org/en/index.html OSGeo Live] que já tem todo o software SIG necessário.

= Conteúdos =

== Sentinel-2 Image processing using QGIS+SCP ==

Notes from Sentinel-2 Image processing using QGIS+SCP course at Skovskolen, Nødebo.

Documentation:

[https://readthedocs.org/projects/semiautomaticclassificationmanual/downloads/pdf/latest/ Semi-Automatic Classification Plugin Documentation]

[[Installing SCP in Ubuntu]]

[[Create a Copernicus Open Access Hub account]]

[[Search and download Sentinel-2 images]]

[[Search and download Landsat 8 images]]

[[Radiance to reflectance]]

[[Clip Sentinel-2 images]]

[[Band compositions]]

[[Export band compositions]]

[[Raster algebra: calculating indexes]]

[[Unsupervised classification]]

[[Supervised classification]]

=== Links ===

https://earth.esa.int/web/sentinel/technical-guides/sentinel-2-msi/msi-instrument

http://esa-sen4cap.org/content/eo-products

https://sentinel.esa.int/web/sentinel/user-guides/sentinel-2-msi/document-library

https://www.indexdatabase.de/db/s-single.php?id=96

https://land.copernicus.eu/global/products/ba

https://fromgistors.blogspot.com/2016/11/from-image-download-to-ndvi-calculation.html

http://www.qgis.pt/blog/2016/12/14/detecao-remota-com-o-qgis/ (em Português)

== Wikidata Sixth Birthday ==

[[File:Birthday banner for 4th Wikidata Birthday.png]]

=== Objectivo ===

Fazer uma mapa:
# Mostrar as ruas, largos, praças e outros espaços com topónimos
# Poder filtrar por:
## sexo
## ocupação (religioso, militar poeta, escritor, político...
## século
## etc

Eventualmente, fazer um quantos gráficos, com percentagens:
# topónimos com nome de pessoas versus outras origens
# nomes de mulheres versus nomes de homens
# políticos versus artes e ciências

=== Problema ===

No OpenStreetMap não existe informação sobre as propriedades do topónimo. O topónimo pode estar escrito de diversas formas e contém partes que não interessam (Rua, Avenida, Prof, Doutor, etc). (Nota: cruzar com o dataset da [http://centraldedados.pt/codigos_postais/ Central de Dados dos Códigos Postais]).

A [https://www.openstreetmap.org/way/35997529#map=16/41.1809/-8.6094 Rua de São Tomé] refere-se a uma pessoa?

Rua Egas Moniz. Qual [https://pt.wikipedia.org/wiki/Egas_Moniz Egas Moniz]?

==== Solução ====

Wikidata! Diferença entre a página da [https://pt.wikipedia.org/wiki/Ant%C3%B3nio_Egas_Moniz Wikipédia do Egas Moniz] e a da [https://www.wikidata.org/wiki/Q273219 Wikidata da mesma pessoa].

Criei a entidade: https://www.wikidata.org/wiki/Q58129518

No OpenStreetMap já se usa uma tag [https://wiki.openstreetmap.org/wiki/Key:wikidata wikidata] para entidades geográficas bem conhecidas, como a [https://www.openstreetmap.org/way/247168260 Torre dos Clérigos].

Existe uma proposta para acrescentar a origem de um determinado nome, usando a tag [https://wiki.openstreetmap.org/wiki/Key:name:etymology name:etymology].

==== Limitações ====

Nem tudo está na Wikidata. Na verdade, existe pouca informação (sobre Portugal) no Wikidata.

No OpenStreetMap também não há muitas tags wikidata.

==== Resolução das limitações ====

'''Editar o OpenStreetMap e a Wikidata!'''

Nota: área pantanosa em relação às licenças: CC-0 versus ODBL.

==== Outras fontes de dados ====

Central de dados

http://centraldedados.pt/nomes_proprios/

https://genderize.io/

==== Algum código de base ====

https://gitlab.com/pdiasalmeida/osm-street-names

== Open Data Day, 2018 ==

[[File:Logo odd 2018.png]]

[[Introdução ao OpenStreetMap]]

[[Serviços sobre os dados do OpenStreetMap]]

[[Dados OpenStreetMap no QGIS]]

[[Dados OpenStreetMap no PostgreSQL]]

[[OpenStreetMap API]]

[[Routing com os dados do OpenStreetMap]]

== SIG desktop com QGIS ==

Introdução à interface do QGIS, a visualização complementar de geometrias e dados, filtrar, selecionar, expressões, trabalhar com a seleção, etc.

[[Instalação QGIS no Windows com base no OSGeo4W]]

Instalação da primeira extensão [https://plugins.qgis.org/plugins/quick_map_services/ QuickMapServices].

Os dados vectoriais referem-se a entidades que têm uma componente espacial (geográfica) e um conjunto de atributos.

[[Explorar dados vectoriais]]

[[Georreferenciação de imagens e criação de camadas]]

[[Edição de dados vetoriais]]

[[Geração de um modelo digital do terreno]]

Acrescentar melhorias aos formulários:
# campos que se atualizam automaticamente
# joins e formulários com combox
# um exemplo de uma relação master → detail

[[Ligação a uma base de dados Postgresql]]

[[Análise espacial com rasters]]

==== Para rever ou eliminar... ====

[[Geoprocessamento]]

[[Criar camadas vectoriais]]

Os dados raster referem-se a superfícies contínuas, cujas propriedades se vão alterando ao longo da superfície.

Visualizar dados raster, calculadora raster, calcular o aspecto, declives, mostrar um perfil.

[[Explorar dados raster]]

Cruzar camadas, associar imagens, associar ações a entidades geográficas

[[Cruzar dados vectoriais]]

Introdução à análise espacial: cálculo de áreas de influência, recorte em função da localização, etc.

[[Introdução à análise espacial]]

[[Georreferenciação de mapas]]

[[Criação de camadas]]

[[Teste de auto-avaliação]]

== SIG desktop com QGIS: Tópicos avançados ==

[[Exercício de aquecimento]]

[[QGIS com Postgresql]]

[[Edição de informação geográfica]]

O processamento com o QGIS é tão assustador como fabuloso. Assustador pela diversidade de alternativas que apresenta e fabuloso pela mesma razão. Além de todas as capacidades de processamento que tem no próprio código, O QGIS liga-se muito bem a outros software de processamento, como o GRASS, SAGA, Orfeo Toolbox, etc.

[[Processamento em QGIS]]

As imagens Sentinel são disponibilizadas pela ESA. O tratamento de imagens Sentinel-2 com a extensão [https://fromgistors.blogspot.com/p/semi-automatic-classification-plugin.html Semi-Automatic Classification Plugin]

[[Tratamento de imagens Sentinel]]

As imagens raster podem ser geridas a partir do sistema de ficheiros ou a partir da base de dados Postgresql.

[[Suporte Postgresql para rasters]]

O QGIS está escrito em C++ que é uma linguagem orientado a objetos, que gera código muito eficiente. O QGIS usa a biblioteca QT para todas as componentes de interface com o utilizador.
Embora todo o núcleo esteja em C++, todas as funcionalidades são expostas para outras aplicações através de uma API que pode ser invocada a partir do Python. Ou seja, a partir de um programa Python, podemos comandar o QGIS e tirar partido de todas as suas funcionalidades.

[[Explorar o QGIS a partir do Python]]

[[QField: o QGIS ao ar livre]]

[[Sobre a preparação desta formação]]

== Base de dados espaciais com Postgresql ==

== Data ==

[https://resourcewatch.org/ Resource Watch – Monitoring the Planet's Pulse]

== Spatial Data Mining ==

* [https://geodacenter.github.io/ GeoDa] is a free and open source software tool that serves as an introduction to spatial data analysis.
* [https://github.com/MapPlus/spatial_statistics_for_geotools_udig GeoAnalysis library] is a java-based open source for geospatial analysis.

== QGIS na área da Saúde ==

[https://plugins.qgis.org/plugins/GeoHealth/ Plugin GeoHealth]

== QGIS na área da Arqueologia ==

Tratamento dos arqueossítios em http://www.geira.pt/arqueo/ListaArqueossitios.html

xml disponível em: http://www4.di.uminho.pt/~jcr/XML/didac/xmldocs/arq.xml

<syntaxhighlight lang="bash">
wget http://www4.di.uminho.pt/~jcr/XML/didac/xmldocs/arq.xml
xsltproc sample.xsl arq.xml > arq.csv
</syntaxhighlight>

<syntaxhighlight lang="xml">
<?xml version="1.0"?>
<xsl:stylesheet version="1.0" xmlns:xsl="http://www.w3.org/1999/XSL/Transform">
<xsl:output type="text" indent="no" omit-xml-declaration="yes" />
<xsl:strip-space elements="*" />

<xsl:template match="//ARQELEM">
<xsl:value-of select="normalize-space(IDENTI)"/>|<xsl:value-of select="normalize-space(DESCRI)"/>|<xsl:value-of select="normalize-space(CRONO)"/>|<xsl:value-of select="normalize-space(FREGUE)"/>|<xsl:value-of select="normalize-space(CONCEL)"/>|<xsl:value-of select="normalize-space(LATITU)"/>|<xsl:value-of select="normalize-space(LONGIT)"/>|<xsl:value-of select="normalize-space(ALTITU)"/>|<xsl:value-of select="normalize-space(ACESSO)"/>|<xsl:value-of select="normalize-space(QUADRO)"/>|<xsl:value-of select="normalize-space(TRAARQ)"/>|<xsl:value-of select="normalize-space(DESARQ)"/>|<xsl:value-of select="normalize-space(INTERP)"/><xsl:text>
</xsl:text>
</xsl:template>
</xsl:stylesheet>
</syntaxhighlight>

Tratamento manual:

coordenadas: multiplicar por 1000

usar o separador de campos: |

usar o delimitador de campos: '

Sistemas de coordenadas: EPSG:20790

Resultado final: arqueossitios.csv

=== Portal do Arqueólogo ===

Acabei por sacar pelo QGIS, ligando-me ao servidor.

Dados de ligação:

==== Sacar lista de sítios ====

<syntaxhighlight lang="bash">
#!/bin/bash

mkdir -p portalarqueologo
for i in {1..1735}
do
curl "http://arqueologia.patrimoniocultural.pt/index.php?sid=sitios&p=$i" -o portalarqueologo/$i.html
done
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd portalarqueologo/
sed -n -e 's/<td data-label="Designação"><a href="\/index.php?sid=sitios\&subsid=$[0-9]\+$">$[^<]\+$<\/a><\/td>/\1\t\2\thttp:\/\/arqueologia.patrimoniocultural.pt\/index.php?sid=sitios\&subsid=\1/p' *.html | sed 's/^\s\+//g' > lista_sitios.csv
</syntaxhighlight>

==== Sacar sítios ====

==== Extrair coordenadas ====

jgr@zoe:~/bin/sitios$ grep '<div id="singleListingMap" data-latitude="[^"]\+" data-longitude="[^"]\+" data-map-icon' *.html > x

sed -n -e 's/$^[0-9]\+$.html:\s\+<div id="singleListingMap" data-latitude="$[0-9.]\+$" data-longitude="$[-0-9.]\+$".\+$/\1\t\2\t\3/p' x

<h2>Monte da Matosa 2</h2> Sítio <span title="CNS">(13709)</span>

grep '<h2>[^<]\+</h2> Sítio <span title="CNS">([\d]\+)</span>' *.html

==== QGIS ====

Abrir lista_sitios.csv

Abrir

== Dados do OpenStreetMap ==

* Introdução ao OpenStreetMap
* Dados do OpenStreetMap no QGIS
* Dados do OpenStreetMap no Postgresql
* Queries com OverPass API, http://overpass-turbo.eu/
* Routing com os dados do OpenStreetMap (OpenTripPlanner)
* Routing com MAPS.ME
* Usar os mapas do OpenStreetMap num blog

=== Requisitos ===

* Computador c/ algum espaço livre
* Dados: serão descarregados na hora, a partir de: http://openstreetmap.pt/wp-content/uploads/
* Software
** QGIS 2.18.17 LTR
** Postgresql v9.6 + PostGIS (não é preciso instalar; haverá um servidor na sala)
** Instalar o MAPS.ME no telemóvel

== Publicação na Web com Geoserver ==

[[Servidores de mapas: conceitos]]

[[Instalação do Geoserver]]

[[Disponibilização de uma camada WMS/WFS]]

[[Disponibilização de uma camada WMTS]]

[[Publicação de grupos]]

== Publicação na Web com uMap ==

A plataforma uMap permite criar mapas de uma forma simples. Os mapas criados podem ser incorporados num blog ou num site.

[[O meu primeiro mapa com o uMap]]

== Drones ==

[[DJI MAVIC 2 PRO]]

[[Flight planner]]

[[Running OpenDroneMap]]

== Contribuir para projectos Open Source no domínio dos SIG ==

[[Contribuir para o Nominatim]]

[[Contribuir para o QGIS]]

[[Contribuir para plugins QGIS]]

[[Contribuir para o OpenTripPlanner]]

[[Contribuir para o GeoExt]]

[[Contribuir para o PostGIS]]

[[Contribuir para o curso PostGIS com Rasters]]

= Outros cursos e recursos =

[http://training.gismentors.eu/isprs-summer-school-2016/index.html ISPRS Congress 2016 Summer School]

[http://training.gismentors.eu/grass-gis-workshop-jena-2018/index.html GRASS GIS Workshop in Jena]

[https://www.hatarilabs.com/ih-en/working-with-sentinel-2-imagery-on-qgis Working with Sentinel 2 Imagery on QGIS]

[https://uwgis.wordpress.com/gis-practicals/flood-risk-mapping/ QGIS Flood Risk Mapping]

[[Como gravar cursos em vídeo]]

= Propostas =

[[QGIS: Generalização Cartográfica]], em parceria com IBGE

[[QGIS: Deteção de estradas em imagens Sentinel-2]], em parceria com IBGE

[[QGIS: Ler cartas náuticas]], em parceria com a comunidade QGIS e de acordo com esta [https://github.com/faunalia/qnavigate proposta de melhoramento]

[[QGIS: Carregar informação meteorológica]], em parceria com a comunidade QGIS e de acordo com esta [https://github.com/faunalia/qnavigate proposta de melhoramento]

[[QGIS:Plugin para dados do INE]]

[[QGIS:Plugin para sobre a Saúde em Portugal]]

= Modelo Topográfico =

http://www.dgterritorio.gov.pt/recart/TRANSPORTES%20(Transporte%20rodovi%C3%A1rio)/CatalogoDasViasRodoviariasParte2.html

http://www.dgterritorio.gov.pt/recart/TRANSPORTES%20(Transporte%20rodovi%C3%A1rio)/CatalogoDasViasRodoviariasParte2UTF-8_20190703.csv

<pre>
vi sed.txt

1s/codigoViaRodov/codigo_via_rodov/
1s/tipoViaRodovC/tipo_rodovia_c/
1s/codigoDGT/codigo_dgt/
1s/codigoArruamento/codigo_arruamento/
1s/tipoViaRodovD/tipo_rodovia_d/
1s/tipoViaRodovAbv/tipo_rodovia_abv/
1s/nomeSufixo/nome_sufixo/
1s/nomeAlternativo/nome_alternativo/
1s/pontosExtremoseIntermedios/pontos_extremos_e_intermedios/
1s/lugarINEcod/lugar_ine_cod/
1s/fonteAquisicaoDados/fonte_aquisicao_dados/
1s/dataEdital/data_edital/
1s/DICOFRE/dicofre/
1s/DICO/dico/
1s/DI/di/
1s/CO/co/
1s/dataCat/data_cat/

sed -f sed.txt -i CatalogoDasViasRodoviariasParte2UTF-8_20190703.csv
</pre>

Instalação QGIS no Windows com base no OSGeo4W

2019-09-26T12:14:38Z

Jgrocha:

O [https://www.qgis.org/pt_PT/site/ QGIS] é um software livre e de código aberto para sistemas de informação geográfica que permite a visualização, edição, e análise de dados georreferenciados.

O [https://trac.osgeo.org/osgeo4w/ OSGeo4W] é uma distribuição binária de um amplo conjunto de software geoespacial livre para ambientes Windows (Windows 10 até XP). OSGeo4W inclui QGIS, GDAL/OGR, GRASS, assim como muitos outros pacotes. Este projecto permite uma gestão integrada e mais sistematizada de todo o software geoespacial que necessitamos.

Este guia delineia os passos necessários para instalar o QGIS (e outras ferramentas necessárias) em ambiente Windows a partir do OSGeo4W:

:1. Aceder no browser ao site do [https://www.qgis.org/pt_PT/site/ QGIS] e seguir o link ''<nowiki>'Transfira agora'</nowiki>''

::[[File:Qgis-instalar-img1.png|600px]]

:2. Na secção ''<nowiki>'Transferir para Windows'</nowiki>'' seguir o link ''<nowiki>'Instalador a partir da rede OSGeo4W'</nowiki>'' para fazer download do instalador

::[[File:Qgis-instalar-img2.png|600px]]

:3. No instalador escolher ''<nowiki>'Express Desktop Install'</nowiki>'' e seleccionar QGIS, GDAL, e GRASS GIS

::[[File:Qgis-instalar-img3.png|300px]] [[File:Qgis-instalar-img4.png|300px]]

:4. Seguir o instalador (aceitar licenças, aguardar downloads)

:5. Quando o instalador terminar premir concluir. Já é possível utilizar o QGIS, ou através dos atalhos criados ou correndo o programa directamente a partir de <syntaxhighlight lang="text" inline>C:\OSGeo4W64\bin\qgis-bin.exe</syntaxhighlight>

=== Instalação sem permissões de administrador ===

Ter em atenção que:
* os antivírus/firewalls podem bloquear conteúdos
* os proxies podem limitar o acesso

https://gis.stackexchange.com/questions/322197/why-is-osgeo4w-w-qgis-3-6-2-asking-for-admin-rights

Instalação QGIS no Windows com base no OSGeo4W

2019-09-26T09:35:01Z

Jgrocha:

O [https://www.qgis.org/pt_PT/site/ QGIS] é um software livre e de código aberto para sistemas de informação geográfica que permite a visualização, edição, e análise de dados georreferenciados.

O [https://trac.osgeo.org/osgeo4w/ OSGeo4W] é uma distribuição binária de um amplo conjunto de software geoespacial livre para ambientes Windows (Windows 10 até XP). OSGeo4W inclui QGIS, GDAL/OGR, GRASS, assim como muitos outros pacotes. Este projecto permite uma gestão integrada e mais sistematizada de todo o software geoespacial que necessitamos.

Este guia delineia os passos necessários para instalar o QGIS (e outras ferramentas necessárias) em ambiente Windows a partir do OSGeo4W:

:1. Aceder no browser ao site do [https://www.qgis.org/pt_PT/site/ QGIS] e seguir o link ''<nowiki>'Transfira agora'</nowiki>''

::[[File:Qgis-instalar-img1.png|600px]]

:2. Na secção ''<nowiki>'Transferir para Windows'</nowiki>'' seguir o link ''<nowiki>'Instalador a partir da rede OSGeo4W'</nowiki>'' para fazer download do instalador

::[[File:Qgis-instalar-img2.png|600px]]

:3. No instalador escolher ''<nowiki>'Express Desktop Install'</nowiki>'' e seleccionar QGIS, GDAL, e GRASS GIS

::[[File:Qgis-instalar-img3.png|300px]] [[File:Qgis-instalar-img4.png|300px]]

:4. Seguir o instalador (aceitar licenças, aguardar downloads)

:5. Quando o instalador terminar premir concluir. Já é possível utilizar o QGIS, ou através dos atalhos criados ou correndo o programa directamente a partir de <syntaxhighlight lang="text" inline>C:\OSGeo4W64\bin\qgis-bin.exe</syntaxhighlight>

=== Instalação sem permissões de administrador ===

https://gis.stackexchange.com/questions/322197/why-is-osgeo4w-w-qgis-3-6-2-asking-for-admin-rights

Como gravar cursos em vídeo

2019-05-16T19:07:57Z

Jgrocha: /* Telemóvel como WebCam */

=== Aplicações ===

==== Screen capture ====

RecordMyDesktop - Só a área da janela da aplicação (QGIS, Firefox, etc). Nas opções retirar as decorações (da janela).

Por o fundo do desktop amarelo

Preparar a janela

Usar a resolução 1280x720

<del>Usar a resolução 1366x768 ''(Standardized HDTV 720p/1080i displays or “HD ready”, used in most cheaper notebooks)''</del>

<syntaxhighlight lang="bash">
sudo apt install wmctrl

jgr@zoe:~/dev/scrcpy/x$ wmctrl -lG
0x02200002 -1 7054 54 313 763 zoe conky (zoe)
0x05a00010 0 1930 64 1808 1052 zoe command line - How do I find the window dimensions and position accurately including decorations? - Unix & Linux Stack Exchange - Mozilla Firefox
0x06c00006 0 10 91 960 1025 zoe jgr@zoe: ~/dev/scrcpy/x
0x07a00003 0 87 171 567 692 zoe Controlo de Volume
0x06009d29 0 3964 96 1299 939 zoe Formulários
0x06e00010 0 440 208 1280 720 N/A *exercicio - QGIS 6a2c31d897
0x0605e92f 0 -72 -10 1583 1097 zoe Pasta pessoal
0x07800017 0 0 83 1920 1025 N/A Untitled* / HD 1080p 25 fps — Kdenlive
0x06c0672a 0 34 566 654 434 zoe jgr@zoe: ~

wmctrl -r "Untitled Project - QGIS 6a2c31d897" -e 0,633,265,1280,720
</syntaxhighlight>

==== Anotações no ecrã ====

http://manpages.ubuntu.com/manpages/cosmic/man1/gromit-mpx.1.html

sudo apt install gromit-mpx

Começa: F9
Shift F9
draw/Shift draw

==== Telemóvel como WebCam ====

Usar o [https://github.com/Genymobile/scrcpy scrcpy] para controlar a câmara.

<syntaxhighlight lang="bash">
cd ~/dev/scrcpy
git pull origin master
rm -rf x
export ANDROID_HOME=~/Android/Sdk
meson x --buildtype release --strip -Db_lto=true
cd x
ninja
sudo ninja install
</syntaxhighlight>

[[File:Captura de ecrã de 2018-11-18 16-50-59.png]]

Ligar por Wifi (na mesma rede)

Começar com a ligação por USB, para configurar o <syntaxhighlight lang="bash" inline>adb</syntaxhighlight>.

Ligar USB. (Tem que se permitir "Depuração por USB", nas "Opções do programador")

<syntaxhighlight lang="bash">
jgr@zoe:~$ adb devices
List of devices attached
ce071717210b872104 device
</syntaxhighlight>

Descobrir o IP do telefone

<syntaxhighlight lang="bash">
jgr@zoe:~$ arp -a
unknown80b234059058.lan (192.168.1.65) em 80:b2:34:05:90:58 [ether] em wlp2s0
vodafonegw (192.168.1.1) em 50:1d:93:b8:f6:21 [ether] em wlp2s0
Sternschanze.lan (192.168.1.66) em 24:18:1d:0e:c3:66 [ether] em wlp2s0

adb tcpip 5555
adb connect 192.168.1.66:5555

# desligar o cabo USB (para não ter dois devices, um por USB e outro por rede)

scrcpy
</syntaxhighlight>

==== Kdenlive ====

==== Audacity ====

=== Hardware ===

Microfone - KIMU PRO: ligar ao telemóvel

Webcam: usar a câmara do telemóvel

Computador

=== Guiões ===

[[Curso de QGIS]]

OpenStreetMap API

2019-05-16T08:57:31Z

Jgrocha: /* Wizard */

=== Wizard ===

Usar o Wizard do overpass

No Wizard escrever: 'bakery or supermarket in Braga'

No Wizard escrever: 'pharmacy in porto'

<syntaxhighlight lang="text">
/*
This has been generated by the overpass-turbo wizard.
The original search was:
“pharmacy in porto”
*/
[out:json][timeout:25];
// fetch area “porto” to search in
{{geocodeArea:porto}}->.searchArea;
// gather results
(
// query part for: “pharmacy”
node["amenity"="pharmacy"](area.searchArea);
way["amenity"="pharmacy"](area.searchArea);
relation["amenity"="pharmacy"](area.searchArea);
);
// print results
out body;
>;
out skel qt;
</syntaxhighlight>

=== Melhorias ===

Trocar:

<syntaxhighlight lang="text">
// print results
out body;
>;
out skel qt;
</syntaxhighlight>

para sair o centroid, se for um polígono:

<syntaxhighlight lang="text">
// print results
out center;
</syntaxhighlight>

Trocar:

<syntaxhighlight lang="text">
// query part for: “pharmacy”
node["amenity"="pharmacy"](area.searchArea);
way["amenity"="pharmacy"](area.searchArea);
relation["amenity"="pharmacy"](area.searchArea);
</syntaxhighlight>

por:

<syntaxhighlight lang="text">
// query part for: “pharmacy”
nwr["amenity"="pharmacy"](area.searchArea);
</syntaxhighlight>

Resultado final:

<syntaxhighlight lang="text">
/*
This has been generated by the overpass-turbo wizard.
The original search was:
“pharmacy in porto”
*/
[out:json][timeout:25];
// fetch area “porto” to search in
{{geocodeArea:porto}}->.searchArea;
// gather results
(
// query part for: “pharmacy”
nwr["amenity"="pharmacy"](area.searchArea);
);
// print results
out center;
</syntaxhighlight>

=== Manual... ===

Abrir http://overpass-turbo.eu/

Procurar no mapa por: Porto

Escrever a seguinte consulta:

<syntaxhighlight lang="text">
/*
procurar por restaurantes
*/
[out:json];
// gather results
(
node["amenity"="restaurant"]({{bbox}});
);
// print results
out body;
</syntaxhighlight>

Executar a consulta

[[File:Restaurantes porto osm.png]]

Exportar e escolher descarregar como geojson

Abrir o geojson no QGIS

A codificação dos caracteres no GeoJson é UTF-8.

No QGIS, a camada é apresentada com a indicação de que se trata (e bem) do sistema de coordenadas EPSG:4326 (WGS84).

Ao passar a camada para a base de dados, indicar que pretendemos uma transformação do sistema EPSG:4326 para EPSG:3763.

OpenStreetMap API

2019-05-14T23:30:17Z

Jgrocha:

Main Page

2019-05-10T16:36:49Z

Jgrocha: /* QGIS na área da Arqueologia */

= Apresentação =

A formação e a disponibilização de conteúdos faz parte do ADN da Geomaster. Neste espaço, estamos a juntar todos os conteúdos das nossas formações, que ainda estão dispersos por vários sítios.

== Onde e como pedir ajuda? ==

[https://lists.osgeo.org/mailman/listinfo/portugal Lista portuguesa da OSGeo]

[https://lists.osgeo.org/mailman/listinfo/qgis-user Lista internacional do QGIS]

https://gis.stackexchange.com/

A Geomaster está oferecer suporte ao QGIS, de forma gratuita. Use o centro de suporte disponível em [https://ticket.geomaster.pt/open.php?lang=pt_PT ticket.geomaster.pt].

Antes de pedir ajuda, faça o trabalho de casa. Pesquise na net se a questão já foi levantada e resolvida.

Para procurar nas listas do QGIS, use o endereço: http://osgeo-org.1560.x6.nabble.com/QGIS-f4099105.html

= Requisitos =

Para fazer os exercícios propostos, precisa de ter algum espaço livre e o software necessário instalado. Os exercícios são independentes do sistema operativo: tanto pode usar Linux, Windows ou macOS.

== Máquina virtual OSGeo Live ==

Uma boa alternativa para a formação é a utilização da máquina virtual [https://live.osgeo.org/en/index.html OSGeo Live] que já tem todo o software SIG necessário.

= Conteúdos =

== Sentinel-2 Image processing using QGIS+SCP ==

Notes from Sentinel-2 Image processing using QGIS+SCP course at Skovskolen, Nødebo.

Documentation:

[https://readthedocs.org/projects/semiautomaticclassificationmanual/downloads/pdf/latest/ Semi-Automatic Classification Plugin Documentation]

[[Installing SCP in Ubuntu]]

[[Create a Copernicus Open Access Hub account]]

[[Search and download Sentinel-2 images]]

[[Search and download Landsat 8 images]]

[[Radiance to reflectance]]

[[Clip Sentinel-2 images]]

[[Band compositions]]

[[Export band compositions]]

[[Raster algebra: calculating indexes]]

[[Unsupervised classification]]

[[Supervised classification]]

=== Links ===

https://earth.esa.int/web/sentinel/technical-guides/sentinel-2-msi/msi-instrument

http://esa-sen4cap.org/content/eo-products

https://sentinel.esa.int/web/sentinel/user-guides/sentinel-2-msi/document-library

https://www.indexdatabase.de/db/s-single.php?id=96

https://land.copernicus.eu/global/products/ba

https://fromgistors.blogspot.com/2016/11/from-image-download-to-ndvi-calculation.html

http://www.qgis.pt/blog/2016/12/14/detecao-remota-com-o-qgis/ (em Português)

== Wikidata Sixth Birthday ==

[[File:Birthday banner for 4th Wikidata Birthday.png]]

=== Objectivo ===

Fazer uma mapa:
# Mostrar as ruas, largos, praças e outros espaços com topónimos
# Poder filtrar por:
## sexo
## ocupação (religioso, militar poeta, escritor, político...
## século
## etc

Eventualmente, fazer um quantos gráficos, com percentagens:
# topónimos com nome de pessoas versus outras origens
# nomes de mulheres versus nomes de homens
# políticos versus artes e ciências

=== Problema ===

No OpenStreetMap não existe informação sobre as propriedades do topónimo. O topónimo pode estar escrito de diversas formas e contém partes que não interessam (Rua, Avenida, Prof, Doutor, etc). (Nota: cruzar com o dataset da [http://centraldedados.pt/codigos_postais/ Central de Dados dos Códigos Postais]).

A [https://www.openstreetmap.org/way/35997529#map=16/41.1809/-8.6094 Rua de São Tomé] refere-se a uma pessoa?

Rua Egas Moniz. Qual [https://pt.wikipedia.org/wiki/Egas_Moniz Egas Moniz]?

==== Solução ====

Wikidata! Diferença entre a página da [https://pt.wikipedia.org/wiki/Ant%C3%B3nio_Egas_Moniz Wikipédia do Egas Moniz] e a da [https://www.wikidata.org/wiki/Q273219 Wikidata da mesma pessoa].

Criei a entidade: https://www.wikidata.org/wiki/Q58129518

No OpenStreetMap já se usa uma tag [https://wiki.openstreetmap.org/wiki/Key:wikidata wikidata] para entidades geográficas bem conhecidas, como a [https://www.openstreetmap.org/way/247168260 Torre dos Clérigos].

Existe uma proposta para acrescentar a origem de um determinado nome, usando a tag [https://wiki.openstreetmap.org/wiki/Key:name:etymology name:etymology].

==== Limitações ====

Nem tudo está na Wikidata. Na verdade, existe pouca informação (sobre Portugal) no Wikidata.

No OpenStreetMap também não há muitas tags wikidata.

==== Resolução das limitações ====

'''Editar o OpenStreetMap e a Wikidata!'''

Nota: área pantanosa em relação às licenças: CC-0 versus ODBL.

==== Outras fontes de dados ====

Central de dados

http://centraldedados.pt/nomes_proprios/

https://genderize.io/

==== Algum código de base ====

https://gitlab.com/pdiasalmeida/osm-street-names

== Open Data Day, 2018 ==

[[File:Logo odd 2018.png]]

[[Introdução ao OpenStreetMap]]

[[Serviços sobre os dados do OpenStreetMap]]

[[Dados OpenStreetMap no QGIS]]

[[Dados OpenStreetMap no PostgreSQL]]

[[OpenStreetMap API]]

[[Routing com os dados do OpenStreetMap]]

== SIG desktop com QGIS ==

Introdução à interface do QGIS, a visualização complementar de geometrias e dados, filtrar, selecionar, expressões, trabalhar com a seleção, etc.

[[Instalação QGIS no Windows com base no OSGeo4W]]

Instalação da primeira extensão [https://plugins.qgis.org/plugins/quick_map_services/ QuickMapServices].

Os dados vectoriais referem-se a entidades que têm uma componente espacial (geográfica) e um conjunto de atributos.

[[Explorar dados vectoriais]]

[[Georreferenciação de imagens e criação de camadas]]

[[Edição de dados vetoriais]]

[[Geração de um modelo digital do terreno]]

Acrescentar melhorias aos formulários:
# campos que se atualizam automaticamente
# joins e formulários com combox
# um exemplo de uma relação master → detail

[[Ligação a uma base de dados Postgresql]]

[[Análise espacial com rasters]]

==== Para rever ou eliminar... ====

[[Geoprocessamento]]

[[Criar camadas vectoriais]]

Os dados raster referem-se a superfícies contínuas, cujas propriedades se vão alterando ao longo da superfície.

Visualizar dados raster, calculadora raster, calcular o aspecto, declives, mostrar um perfil.

[[Explorar dados raster]]

Cruzar camadas, associar imagens, associar ações a entidades geográficas

[[Cruzar dados vectoriais]]

Introdução à análise espacial: cálculo de áreas de influência, recorte em função da localização, etc.

[[Introdução à análise espacial]]

[[Georreferenciação de mapas]]

[[Criação de camadas]]

[[Teste de auto-avaliação]]

== SIG desktop com QGIS: Tópicos avançados ==

[[Exercício de aquecimento]]

[[QGIS com Postgresql]]

[[Edição de informação geográfica]]

O processamento com o QGIS é tão assustador como fabuloso. Assustador pela diversidade de alternativas que apresenta e fabuloso pela mesma razão. Além de todas as capacidades de processamento que tem no próprio código, O QGIS liga-se muito bem a outros software de processamento, como o GRASS, SAGA, Orfeo Toolbox, etc.

[[Processamento em QGIS]]

As imagens Sentinel são disponibilizadas pela ESA. O tratamento de imagens Sentinel-2 com a extensão [https://fromgistors.blogspot.com/p/semi-automatic-classification-plugin.html Semi-Automatic Classification Plugin]

[[Tratamento de imagens Sentinel]]

As imagens raster podem ser geridas a partir do sistema de ficheiros ou a partir da base de dados Postgresql.

[[Suporte Postgresql para rasters]]

O QGIS está escrito em C++ que é uma linguagem orientado a objetos, que gera código muito eficiente. O QGIS usa a biblioteca QT para todas as componentes de interface com o utilizador.
Embora todo o núcleo esteja em C++, todas as funcionalidades são expostas para outras aplicações através de uma API que pode ser invocada a partir do Python. Ou seja, a partir de um programa Python, podemos comandar o QGIS e tirar partido de todas as suas funcionalidades.

[[Explorar o QGIS a partir do Python]]

[[QField: o QGIS ao ar livre]]

[[Sobre a preparação desta formação]]

== Base de dados espaciais com Postgresql ==

== Data ==

[https://resourcewatch.org/ Resource Watch – Monitoring the Planet's Pulse]

== Spatial Data Mining ==

* [https://geodacenter.github.io/ GeoDa] is a free and open source software tool that serves as an introduction to spatial data analysis.
* [https://github.com/MapPlus/spatial_statistics_for_geotools_udig GeoAnalysis library] is a java-based open source for geospatial analysis.

== QGIS na área da Saúde ==

[https://plugins.qgis.org/plugins/GeoHealth/ Plugin GeoHealth]

== QGIS na área da Arqueologia ==

Tratamento dos arqueossítios em http://www.geira.pt/arqueo/ListaArqueossitios.html

xml disponível em: http://www4.di.uminho.pt/~jcr/XML/didac/xmldocs/arq.xml

<syntaxhighlight lang="bash">
wget http://www4.di.uminho.pt/~jcr/XML/didac/xmldocs/arq.xml
xsltproc sample.xsl arq.xml > arq.csv
</syntaxhighlight>

<syntaxhighlight lang="xml">
<?xml version="1.0"?>
<xsl:stylesheet version="1.0" xmlns:xsl="http://www.w3.org/1999/XSL/Transform">
<xsl:output type="text" indent="no" omit-xml-declaration="yes" />
<xsl:strip-space elements="*" />

<xsl:template match="//ARQELEM">
<xsl:value-of select="normalize-space(IDENTI)"/>|<xsl:value-of select="normalize-space(DESCRI)"/>|<xsl:value-of select="normalize-space(CRONO)"/>|<xsl:value-of select="normalize-space(FREGUE)"/>|<xsl:value-of select="normalize-space(CONCEL)"/>|<xsl:value-of select="normalize-space(LATITU)"/>|<xsl:value-of select="normalize-space(LONGIT)"/>|<xsl:value-of select="normalize-space(ALTITU)"/>|<xsl:value-of select="normalize-space(ACESSO)"/>|<xsl:value-of select="normalize-space(QUADRO)"/>|<xsl:value-of select="normalize-space(TRAARQ)"/>|<xsl:value-of select="normalize-space(DESARQ)"/>|<xsl:value-of select="normalize-space(INTERP)"/><xsl:text>
</xsl:text>
</xsl:template>
</xsl:stylesheet>
</syntaxhighlight>

Tratamento manual:

coordenadas: multiplicar por 1000

usar o separador de campos: |

usar o delimitador de campos: '

Sistemas de coordenadas: EPSG:20790

Resultado final: arqueossitios.csv

=== Portal do Arqueólogo ===

Acabei por sacar pelo QGIS, ligando-me ao servidor.

Dados de ligação:

==== Sacar lista de sítios ====

<syntaxhighlight lang="bash">
#!/bin/bash

mkdir -p portalarqueologo
for i in {1..1735}
do
curl "http://arqueologia.patrimoniocultural.pt/index.php?sid=sitios&p=$i" -o portalarqueologo/$i.html
done
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd portalarqueologo/
sed -n -e 's/<td data-label="Designação"><a href="\/index.php?sid=sitios\&subsid=$[0-9]\+$">$[^<]\+$<\/a><\/td>/\1\t\2\thttp:\/\/arqueologia.patrimoniocultural.pt\/index.php?sid=sitios\&subsid=\1/p' *.html | sed 's/^\s\+//g' > lista_sitios.csv
</syntaxhighlight>

==== Sacar sítios ====

==== Extrair coordenadas ====

jgr@zoe:~/bin/sitios$ grep '<div id="singleListingMap" data-latitude="[^"]\+" data-longitude="[^"]\+" data-map-icon' *.html > x

sed -n -e 's/$^[0-9]\+$.html:\s\+<div id="singleListingMap" data-latitude="$[0-9.]\+$" data-longitude="$[-0-9.]\+$".\+$/\1\t\2\t\3/p' x

<h2>Monte da Matosa 2</h2> Sítio <span title="CNS">(13709)</span>

grep '<h2>[^<]\+</h2> Sítio <span title="CNS">([\d]\+)</span>' *.html

==== QGIS ====

Abrir lista_sitios.csv

Abrir

== Dados do OpenStreetMap ==

* Introdução ao OpenStreetMap
* Dados do OpenStreetMap no QGIS
* Dados do OpenStreetMap no Postgresql
* Queries com OverPass API, http://overpass-turbo.eu/
* Routing com os dados do OpenStreetMap (OpenTripPlanner)
* Routing com MAPS.ME
* Usar os mapas do OpenStreetMap num blog

=== Requisitos ===

* Computador c/ algum espaço livre
* Dados: serão descarregados na hora, a partir de: http://openstreetmap.pt/wp-content/uploads/
* Software
** QGIS 2.18.17 LTR
** Postgresql v9.6 + PostGIS (não é preciso instalar; haverá um servidor na sala)
** Instalar o MAPS.ME no telemóvel

== Publicação na Web com Geoserver ==

[[Servidores de mapas: conceitos]]

[[Instalação do Geoserver]]

[[Disponibilização de uma camada WMS/WFS]]

[[Disponibilização de uma camada WMTS]]

[[Publicação de grupos]]

== Publicação na Web com uMap ==

A plataforma uMap permite criar mapas de uma forma simples. Os mapas criados podem ser incorporados num blog ou num site.

[[O meu primeiro mapa com o uMap]]

== Drones ==

[[DJI MAVIC 2 PRO]]

[[Flight planner]]

[[Running OpenDroneMap]]

== Contribuir para projectos Open Source no domínio dos SIG ==

[[Contribuir para o Nominatim]]

[[Contribuir para o QGIS]]

[[Contribuir para plugins QGIS]]

[[Contribuir para o OpenTripPlanner]]

[[Contribuir para o GeoExt]]

[[Contribuir para o PostGIS]]

[[Contribuir para o curso PostGIS com Rasters]]

= Outros cursos e recursos =

[http://training.gismentors.eu/isprs-summer-school-2016/index.html ISPRS Congress 2016 Summer School]

[http://training.gismentors.eu/grass-gis-workshop-jena-2018/index.html GRASS GIS Workshop in Jena]

[https://www.hatarilabs.com/ih-en/working-with-sentinel-2-imagery-on-qgis Working with Sentinel 2 Imagery on QGIS]

[https://uwgis.wordpress.com/gis-practicals/flood-risk-mapping/ QGIS Flood Risk Mapping]

[[Como gravar cursos em vídeo]]

= Propostas =

[[QGIS: Generalização Cartográfica]], em parceria com IBGE

[[QGIS: Deteção de estradas em imagens Sentinel-2]], em parceria com IBGE

[[QGIS: Ler cartas náuticas]], em parceria com a comunidade QGIS e de acordo com esta [https://github.com/faunalia/qnavigate proposta de melhoramento]

[[QGIS: Carregar informação meteorológica]], em parceria com a comunidade QGIS e de acordo com esta [https://github.com/faunalia/qnavigate proposta de melhoramento]

[[QGIS:Plugin para dados do INE]]

[[QGIS:Plugin para sobre a Saúde em Portugal]]

Main Page

2019-04-26T00:25:48Z

Jgrocha: /* QGIS na área da Saúde */

= Apresentação =

A formação e a disponibilização de conteúdos faz parte do ADN da Geomaster. Neste espaço, estamos a juntar todos os conteúdos das nossas formações, que ainda estão dispersos por vários sítios.

== Onde e como pedir ajuda? ==

[https://lists.osgeo.org/mailman/listinfo/portugal Lista portuguesa da OSGeo]

[https://lists.osgeo.org/mailman/listinfo/qgis-user Lista internacional do QGIS]

https://gis.stackexchange.com/

A Geomaster está oferecer suporte ao QGIS, de forma gratuita. Use o centro de suporte disponível em [https://ticket.geomaster.pt/open.php?lang=pt_PT ticket.geomaster.pt].

Antes de pedir ajuda, faça o trabalho de casa. Pesquise na net se a questão já foi levantada e resolvida.

Para procurar nas listas do QGIS, use o endereço: http://osgeo-org.1560.x6.nabble.com/QGIS-f4099105.html

= Requisitos =

Para fazer os exercícios propostos, precisa de ter algum espaço livre e o software necessário instalado. Os exercícios são independentes do sistema operativo: tanto pode usar Linux, Windows ou macOS.

== Máquina virtual OSGeo Live ==

Uma boa alternativa para a formação é a utilização da máquina virtual [https://live.osgeo.org/en/index.html OSGeo Live] que já tem todo o software SIG necessário.

= Conteúdos =

== Sentinel-2 Image processing using QGIS+SCP ==

Notes from Sentinel-2 Image processing using QGIS+SCP course at Skovskolen, Nødebo.

Documentation:

[https://readthedocs.org/projects/semiautomaticclassificationmanual/downloads/pdf/latest/ Semi-Automatic Classification Plugin Documentation]

[[Installing SCP in Ubuntu]]

[[Create a Copernicus Open Access Hub account]]

[[Search and download Sentinel-2 images]]

[[Search and download Landsat 8 images]]

[[Radiance to reflectance]]

[[Clip Sentinel-2 images]]

[[Band compositions]]

[[Export band compositions]]

[[Raster algebra: calculating indexes]]

[[Unsupervised classification]]

[[Supervised classification]]

=== Links ===

https://earth.esa.int/web/sentinel/technical-guides/sentinel-2-msi/msi-instrument

http://esa-sen4cap.org/content/eo-products

https://sentinel.esa.int/web/sentinel/user-guides/sentinel-2-msi/document-library

https://www.indexdatabase.de/db/s-single.php?id=96

https://land.copernicus.eu/global/products/ba

https://fromgistors.blogspot.com/2016/11/from-image-download-to-ndvi-calculation.html

http://www.qgis.pt/blog/2016/12/14/detecao-remota-com-o-qgis/ (em Português)

== Wikidata Sixth Birthday ==

[[File:Birthday banner for 4th Wikidata Birthday.png]]

=== Objectivo ===

Fazer uma mapa:
# Mostrar as ruas, largos, praças e outros espaços com topónimos
# Poder filtrar por:
## sexo
## ocupação (religioso, militar poeta, escritor, político...
## século
## etc

Eventualmente, fazer um quantos gráficos, com percentagens:
# topónimos com nome de pessoas versus outras origens
# nomes de mulheres versus nomes de homens
# políticos versus artes e ciências

=== Problema ===

No OpenStreetMap não existe informação sobre as propriedades do topónimo. O topónimo pode estar escrito de diversas formas e contém partes que não interessam (Rua, Avenida, Prof, Doutor, etc). (Nota: cruzar com o dataset da [http://centraldedados.pt/codigos_postais/ Central de Dados dos Códigos Postais]).

A [https://www.openstreetmap.org/way/35997529#map=16/41.1809/-8.6094 Rua de São Tomé] refere-se a uma pessoa?

Rua Egas Moniz. Qual [https://pt.wikipedia.org/wiki/Egas_Moniz Egas Moniz]?

==== Solução ====

Wikidata! Diferença entre a página da [https://pt.wikipedia.org/wiki/Ant%C3%B3nio_Egas_Moniz Wikipédia do Egas Moniz] e a da [https://www.wikidata.org/wiki/Q273219 Wikidata da mesma pessoa].

Criei a entidade: https://www.wikidata.org/wiki/Q58129518

No OpenStreetMap já se usa uma tag [https://wiki.openstreetmap.org/wiki/Key:wikidata wikidata] para entidades geográficas bem conhecidas, como a [https://www.openstreetmap.org/way/247168260 Torre dos Clérigos].

Existe uma proposta para acrescentar a origem de um determinado nome, usando a tag [https://wiki.openstreetmap.org/wiki/Key:name:etymology name:etymology].

==== Limitações ====

Nem tudo está na Wikidata. Na verdade, existe pouca informação (sobre Portugal) no Wikidata.

No OpenStreetMap também não há muitas tags wikidata.

==== Resolução das limitações ====

'''Editar o OpenStreetMap e a Wikidata!'''

Nota: área pantanosa em relação às licenças: CC-0 versus ODBL.

==== Outras fontes de dados ====

Central de dados

http://centraldedados.pt/nomes_proprios/

https://genderize.io/

==== Algum código de base ====

https://gitlab.com/pdiasalmeida/osm-street-names

== Open Data Day, 2018 ==

[[File:Logo odd 2018.png]]

[[Introdução ao OpenStreetMap]]

[[Serviços sobre os dados do OpenStreetMap]]

[[Dados OpenStreetMap no QGIS]]

[[Dados OpenStreetMap no PostgreSQL]]

[[OpenStreetMap API]]

[[Routing com os dados do OpenStreetMap]]

== SIG desktop com QGIS ==

Introdução à interface do QGIS, a visualização complementar de geometrias e dados, filtrar, selecionar, expressões, trabalhar com a seleção, etc.

[[Instalação QGIS no Windows com base no OSGeo4W]]

Instalação da primeira extensão [https://plugins.qgis.org/plugins/quick_map_services/ QuickMapServices].

Os dados vectoriais referem-se a entidades que têm uma componente espacial (geográfica) e um conjunto de atributos.

[[Explorar dados vectoriais]]

[[Georreferenciação de imagens e criação de camadas]]

[[Edição de dados vetoriais]]

[[Geração de um modelo digital do terreno]]

Acrescentar melhorias aos formulários:
# campos que se atualizam automaticamente
# joins e formulários com combox
# um exemplo de uma relação master → detail

[[Ligação a uma base de dados Postgresql]]

[[Análise espacial com rasters]]

==== Para rever ou eliminar... ====

[[Geoprocessamento]]

[[Criar camadas vectoriais]]

Os dados raster referem-se a superfícies contínuas, cujas propriedades se vão alterando ao longo da superfície.

Visualizar dados raster, calculadora raster, calcular o aspecto, declives, mostrar um perfil.

[[Explorar dados raster]]

Cruzar camadas, associar imagens, associar ações a entidades geográficas

[[Cruzar dados vectoriais]]

Introdução à análise espacial: cálculo de áreas de influência, recorte em função da localização, etc.

[[Introdução à análise espacial]]

[[Georreferenciação de mapas]]

[[Criação de camadas]]

[[Teste de auto-avaliação]]

== SIG desktop com QGIS: Tópicos avançados ==

[[Exercício de aquecimento]]

[[QGIS com Postgresql]]

[[Edição de informação geográfica]]

O processamento com o QGIS é tão assustador como fabuloso. Assustador pela diversidade de alternativas que apresenta e fabuloso pela mesma razão. Além de todas as capacidades de processamento que tem no próprio código, O QGIS liga-se muito bem a outros software de processamento, como o GRASS, SAGA, Orfeo Toolbox, etc.

[[Processamento em QGIS]]

As imagens Sentinel são disponibilizadas pela ESA. O tratamento de imagens Sentinel-2 com a extensão [https://fromgistors.blogspot.com/p/semi-automatic-classification-plugin.html Semi-Automatic Classification Plugin]

[[Tratamento de imagens Sentinel]]

As imagens raster podem ser geridas a partir do sistema de ficheiros ou a partir da base de dados Postgresql.

[[Suporte Postgresql para rasters]]

O QGIS está escrito em C++ que é uma linguagem orientado a objetos, que gera código muito eficiente. O QGIS usa a biblioteca QT para todas as componentes de interface com o utilizador.
Embora todo o núcleo esteja em C++, todas as funcionalidades são expostas para outras aplicações através de uma API que pode ser invocada a partir do Python. Ou seja, a partir de um programa Python, podemos comandar o QGIS e tirar partido de todas as suas funcionalidades.

[[Explorar o QGIS a partir do Python]]

[[QField: o QGIS ao ar livre]]

[[Sobre a preparação desta formação]]

== Base de dados espaciais com Postgresql ==

== Data ==

[https://resourcewatch.org/ Resource Watch – Monitoring the Planet's Pulse]

== Spatial Data Mining ==

* [https://geodacenter.github.io/ GeoDa] is a free and open source software tool that serves as an introduction to spatial data analysis.
* [https://github.com/MapPlus/spatial_statistics_for_geotools_udig GeoAnalysis library] is a java-based open source for geospatial analysis.

== QGIS na área da Saúde ==

[https://plugins.qgis.org/plugins/GeoHealth/ Plugin GeoHealth]

== QGIS na área da Arqueologia ==

Tratamento dos arqueossítios em http://www.geira.pt/arqueo/ListaArqueossitios.html

xml disponível em: http://www4.di.uminho.pt/~jcr/XML/didac/xmldocs/arq.xml

<syntaxhighlight lang="bash">
wget http://www4.di.uminho.pt/~jcr/XML/didac/xmldocs/arq.xml
xsltproc sample.xsl arq.xml > arq.csv
</syntaxhighlight>

<syntaxhighlight lang="xml">
<?xml version="1.0"?>
<xsl:stylesheet version="1.0" xmlns:xsl="http://www.w3.org/1999/XSL/Transform">
<xsl:output type="text" indent="no" omit-xml-declaration="yes" />
<xsl:strip-space elements="*" />

<xsl:template match="//ARQELEM">
<xsl:value-of select="normalize-space(IDENTI)"/>|<xsl:value-of select="normalize-space(DESCRI)"/>|<xsl:value-of select="normalize-space(CRONO)"/>|<xsl:value-of select="normalize-space(FREGUE)"/>|<xsl:value-of select="normalize-space(CONCEL)"/>|<xsl:value-of select="normalize-space(LATITU)"/>|<xsl:value-of select="normalize-space(LONGIT)"/>|<xsl:value-of select="normalize-space(ALTITU)"/>|<xsl:value-of select="normalize-space(ACESSO)"/>|<xsl:value-of select="normalize-space(QUADRO)"/>|<xsl:value-of select="normalize-space(TRAARQ)"/>|<xsl:value-of select="normalize-space(DESARQ)"/>|<xsl:value-of select="normalize-space(INTERP)"/><xsl:text>
</xsl:text>
</xsl:template>
</xsl:stylesheet>
</syntaxhighlight>

Tratamento manual:

coordenadas: multiplicar por 1000

usar o separador de campos: |

usar o delimitador de campos: '

Sistemas de coordenadas: EPSG:20790

Resultado final: arqueossitios.csv

== Dados do OpenStreetMap ==

* Introdução ao OpenStreetMap
* Dados do OpenStreetMap no QGIS
* Dados do OpenStreetMap no Postgresql
* Queries com OverPass API, http://overpass-turbo.eu/
* Routing com os dados do OpenStreetMap (OpenTripPlanner)
* Routing com MAPS.ME
* Usar os mapas do OpenStreetMap num blog

=== Requisitos ===

* Computador c/ algum espaço livre
* Dados: serão descarregados na hora, a partir de: http://openstreetmap.pt/wp-content/uploads/
* Software
** QGIS 2.18.17 LTR
** Postgresql v9.6 + PostGIS (não é preciso instalar; haverá um servidor na sala)
** Instalar o MAPS.ME no telemóvel

== Publicação na Web com Geoserver ==

[[Servidores de mapas: conceitos]]

[[Instalação do Geoserver]]

[[Disponibilização de uma camada WMS/WFS]]

[[Disponibilização de uma camada WMTS]]

[[Publicação de grupos]]

== Publicação na Web com uMap ==

A plataforma uMap permite criar mapas de uma forma simples. Os mapas criados podem ser incorporados num blog ou num site.

[[O meu primeiro mapa com o uMap]]

== Drones ==

[[DJI MAVIC 2 PRO]]

[[Flight planner]]

[[Running OpenDroneMap]]

== Contribuir para projectos Open Source no domínio dos SIG ==

[[Contribuir para o Nominatim]]

[[Contribuir para o QGIS]]

[[Contribuir para plugins QGIS]]

[[Contribuir para o OpenTripPlanner]]

[[Contribuir para o GeoExt]]

[[Contribuir para o PostGIS]]

[[Contribuir para o curso PostGIS com Rasters]]

= Outros cursos e recursos =

[http://training.gismentors.eu/isprs-summer-school-2016/index.html ISPRS Congress 2016 Summer School]

[http://training.gismentors.eu/grass-gis-workshop-jena-2018/index.html GRASS GIS Workshop in Jena]

[https://www.hatarilabs.com/ih-en/working-with-sentinel-2-imagery-on-qgis Working with Sentinel 2 Imagery on QGIS]

[https://uwgis.wordpress.com/gis-practicals/flood-risk-mapping/ QGIS Flood Risk Mapping]

[[Como gravar cursos em vídeo]]

= Propostas =

[[QGIS: Generalização Cartográfica]], em parceria com IBGE

[[QGIS: Deteção de estradas em imagens Sentinel-2]], em parceria com IBGE

[[QGIS: Ler cartas náuticas]], em parceria com a comunidade QGIS e de acordo com esta [https://github.com/faunalia/qnavigate proposta de melhoramento]

[[QGIS: Carregar informação meteorológica]], em parceria com a comunidade QGIS e de acordo com esta [https://github.com/faunalia/qnavigate proposta de melhoramento]

[[QGIS:Plugin para dados do INE]]

[[QGIS:Plugin para sobre a Saúde em Portugal]]

Como gravar cursos em vídeo

2019-04-11T10:34:20Z

Jgrocha: /* Telemóvel como WebCam */

=== Aplicações ===

==== Screen capture ====

RecordMyDesktop - Só a área da janela da aplicação (QGIS, Firefox, etc). Nas opções retirar as decorações (da janela).

Por o fundo do desktop amarelo

Preparar a janela

Usar a resolução 1280x720

<del>Usar a resolução 1366x768 ''(Standardized HDTV 720p/1080i displays or “HD ready”, used in most cheaper notebooks)''</del>

<syntaxhighlight lang="bash">
sudo apt install wmctrl

jgr@zoe:~/dev/scrcpy/x$ wmctrl -lG
0x02200002 -1 7054 54 313 763 zoe conky (zoe)
0x05a00010 0 1930 64 1808 1052 zoe command line - How do I find the window dimensions and position accurately including decorations? - Unix & Linux Stack Exchange - Mozilla Firefox
0x06c00006 0 10 91 960 1025 zoe jgr@zoe: ~/dev/scrcpy/x
0x07a00003 0 87 171 567 692 zoe Controlo de Volume
0x06009d29 0 3964 96 1299 939 zoe Formulários
0x06e00010 0 440 208 1280 720 N/A *exercicio - QGIS 6a2c31d897
0x0605e92f 0 -72 -10 1583 1097 zoe Pasta pessoal
0x07800017 0 0 83 1920 1025 N/A Untitled* / HD 1080p 25 fps — Kdenlive
0x06c0672a 0 34 566 654 434 zoe jgr@zoe: ~

wmctrl -r "Untitled Project - QGIS 6a2c31d897" -e 0,633,265,1280,720
</syntaxhighlight>

==== Anotações no ecrã ====

http://manpages.ubuntu.com/manpages/cosmic/man1/gromit-mpx.1.html

sudo apt install gromit-mpx

Começa: F9
Shift F9
draw/Shift draw

==== Telemóvel como WebCam ====

Usar o [https://github.com/Genymobile/scrcpy scrcpy] para controlar a câmara.

[[File:Captura de ecrã de 2018-11-18 16-50-59.png]]

Ligar por Wifi (na mesma rede)

Começar com a ligação por USB, para configurar o <syntaxhighlight lang="bash" inline>adb</syntaxhighlight>.

Ligar USB. (Tem que se permitir "Depuração por USB", nas "Opções do programador")

<syntaxhighlight lang="bash">
jgr@zoe:~$ adb devices
List of devices attached
ce071717210b872104 device
</syntaxhighlight>

Descobrir o IP do telefone

<syntaxhighlight lang="bash">
jgr@zoe:~$ arp -a
unknown80b234059058.lan (192.168.1.65) em 80:b2:34:05:90:58 [ether] em wlp2s0
vodafonegw (192.168.1.1) em 50:1d:93:b8:f6:21 [ether] em wlp2s0
Sternschanze.lan (192.168.1.66) em 24:18:1d:0e:c3:66 [ether] em wlp2s0

adb tcpip 5555
adb connect 192.168.1.66:5555

# desligar o cabo USB (para não ter dois devices, um por USB e outro por rede)

scrcpy
</syntaxhighlight>

==== Kdenlive ====

==== Audacity ====

=== Hardware ===

Microfone - KIMU PRO: ligar ao telemóvel

Webcam: usar a câmara do telemóvel

Computador

=== Guiões ===

[[Curso de QGIS]]

Main Page

2019-04-04T13:26:14Z

Jgrocha: /* Propostas */

Running OpenDroneMap

2019-03-06T16:49:50Z

Jgrocha:

=== Drone Workshop ===

Part I

0. The data

EPSG:25832

0.1 The images

0.2 The ground control points

0.2.1 Discuss how to get GCP: survey or from a reference dataset

0.3 The flight path

1. WebODM

1.2 Preparation and Installation

1.3 Run our first task

2. Overview of the products

2.1 Orthophoto

2.2 Point cloud

2.3 DSM

2.4 DTM

Part II

3. Fine tunning the data

3.1 Clip orthophoto

Create a mask layer

Clip

Enable JPG compression

3.2 Point cloud

Clip with pdal

Classify with pdal

4. Taking advantagle of the artifacts

[[Drone workshop print screens]]

1. Flight

WebODM

<syntaxhighlight lang="bash">
pip install docker-compose
</syntaxhighlight>

10:54

2. Data products

2.1 Orthophoto

Discussion: GCP, impact on the elevation model

Swipe tool

Point value: check ortho values

2.2 DEM/DSM

Discussion: difference between

Raster value

Profile tool

Visualization: hillshade

http://plas.io/

https://pdal.io/tutorial/pcl_ground/index.html#pcl-ground

<syntaxhighlight lang="bash">
-- original
pdal translate -i /code/odm_georeferencing/odm_georeferenced_model.laz -o /code/odm_georeferencing/odm_georeferenced_model.laz smrf --filters.smrf.cell=2 --filters.smrf.slope=10 --filters.smrf.window=10

-- VERY GOOD
pdal translate -i odm_georeferencing/odm_georeferenced_model.ply -o odm_georeferencing/odm_georeferenced_model_2.laz smrf --filters.smrf.cell=2 --filters.smrf.window=10

-- good
pdal ground -i odm_georeferencing/odm_georeferenced_model.ply -o odm_georeferencing/odm_georeferenced_model_3.laz
</syntaxhighlight>

PotreeConverter odm_georeferenced_model.ply -o ~/dev/potree/examples/odm -p qgis.drone.workshop --overwrite --projection "+proj=utm +zone=32 +ellps=GRS80 +towgs84=0.0.0.0.0.0.0 +units=m"

<syntaxhighlight lang="bash">
jgr@zoe:~/dev/potree$ gulp watch
</syntaxhighlight>

<syntaxhighlight lang="bash">
jgr@zoe:~/dev/PotreeConverter/master/build/PotreeConverter$ PotreeConverter ~/Documentos/workshop2/odm_georeferencing/odm_georeferenced_model.ply -o ~/dev/potree/examples/odm -p qgis.drone.workshop --overwrite --projection "+proj=utm +zone=32 +ellps=GRS80 +towgs84=0.0.0.0.0.0.0 +units=m"
</syntaxhighlight>

2.3 Point cloud

What we get from the software

Visualization tools

https://pdal.io/workshop/exercises/analysis/dtm/dtm.html

3. Processing data products

3.1 Better classification

lasground

3.2 lasheight

3.3 lasclassify

=== DJI Mavic 2 PRO ===

[https://forum.dji.com/thread-167017-1-1.html Sensor size], [https://www.youtube.com/watch?v=xIncVCe6pg0 Video about sensor size]

==== Erro ====

Culpado: <syntaxhighlight lang="bash" inline>/home/jgr/PycharmProjects/OpenDroneMap/modules/odm_extract_utm</syntaxhighlight>

Todas as imagens estão com Exif.GPSInfo.GPSAltitude = 0.0

<syntaxhighlight lang="bash">
if (lon == 0.0 || lat == 0.0 || alt == 0.0) {
std::string error("Failed parsing GPS position for " + imageFilename);
throw UtmExtractorException(error);
}
</syntaxhighlight>

==== Remendo ====

<syntaxhighlight lang="bash">
exiv2 -pa DJI_0210.JPG
Exif.GPSInfo.GPSAltitude Rational 1 0.0 m

exiv2 -M"set Exif.GPSInfo.GPSAltitude Rational 1/10" DJI_0210.JPG
exiv2 -pa DJI_0210.JPG
Exif.GPSInfo.GPSAltitude Rational 1 0.1 m
</syntaxhighlight>

Chamada:

<syntaxhighlight lang="bash">
[INFO] Wrote images database: /code/images.json
[INFO] Found 106 usable images
[DEBUG] running /code/build/bin/odm_extract_utm -imagesPath /code/images/ -imageListFile /code/img_list.txt -outputCoordFile /code/odm_georeferencing/coords.txt -logFile /code/odm_georeferencing/odm_georeferencing_utm_log.txt
Error in OdmExtractUtm:
Failed parsing GPS position for DJI_0301.JPG
For more detailed information, see log file.
</syntaxhighlight>

<syntaxhighlight lang="text">
[INFO] Found 106 usable images
[WARNING] Could not generate coordinates file. Ignore if there is a GCP file. Error: Error in OdmExtractUtm:
Failed parsing GPS position for DJI_0301.JPG
For more detailed information, see log file.

(...)

Building objmodel:
Saving model... done.
Whole texturing procedure took: 225.586s
[INFO] Running ODM Texturing Cell - Finished
[INFO] Running ODM Georeferencing Cell
[WARNING] Georeferencing failed. Make sure your photos have geotags in the EXIF or you have provided a GCP file.
[INFO] Running ODM Georeferencing Cell - Finished
[INFO] Running ODM DEM Cell
[INFO] Classify: True
[INFO] Create DSM: True
[INFO] Create DTM: True
[INFO] DEM input file /code/odm_georeferencing/odm_georeferenced_model.las found: False
[WARNING] DEM will not be generated
[INFO] Running ODM DEM Cell - Finished
[INFO] Running ODM Orthophoto Cell
[DEBUG] running /code/build/bin/odm_orthophoto -inputFile /code/odm_texturing/odm_textured_model.obj -logFile /code/odm_orthophoto/odm_orthophoto_log.txt -outputFile /code/odm_orthophoto/odm_orthophoto.png -resolution 10.0 -outputCornerFile /code/odm_orthophoto/odm_orthophoto_corners.txt
[WARNING] No geo-referenced orthophoto created due to missing geo-referencing or corner coordinates.
[INFO] Running ODM OrthoPhoto Cell - Finished
[INFO] OpenDroneMap app finished - Sat Dec 29 22:12:22 2018
</syntaxhighlight>

=== Running docker OpenDroneMap ===

==== Update to last OpenDroneMap docker image ====

<syntaxhighlight lang="bash">
docker pull opendronemap/opendronemap
</syntaxhighlight>

==== OpenDroneMap docker image ====

# Install docker
# Add you user to docker group
# sudo -H pip install requests

<syntaxhighlight lang="bash">
mkdir OpenDroneMap
cd OpenDroneMap
git clone git@github.com:OpenDroneMap/odm_data_aukerman.git
cd odm_data_aukerman

export odmi=`pwd`
ls -l $odmi

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd /home/jgr/Documentos/sletten16maj2018-gcp
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
opendronemap/opendronemap --gcp gcp_list.txt --dtm --dsm
</syntaxhighlight>

Sem GCP:

<syntaxhighlight lang="bash">
cd ~/Documentos/costanovadoprado/
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm --orthophoto-resolution 10.0
</syntaxhighlight>

Nota: os ortos estão a ficar com muitas interferências do modelo 3D, nas áreas urbanas.

Related problem: http://community.opendronemap.org/t/buildings/929

Será que voar com a câmara a 75 graus ajuda? Fiz um voo com Double Grid, com a camara a 70 graus (default do Pix4d capture).

==== Mac ====

1. Install Docker

2. <syntaxhighlight lang="bash">
docker run -it --rm -v $(pwd)/images:/code/images -v $(pwd)/odm_orthophoto:/code/odm_orthophoto -v $(pwd)/odm_texturing:/code/odm_texturing -v $(pwd)/odm_georeferencing:/code/odm_georeferencing -v $(pwd)/odm_meshing:/code/odm_meshing -v $(pwd)/opensfm:/code/opensfm -v $(pwd)/odm_dem:/code/odm_dem opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

With GCP (calculating 3000-y coordinate)

<syntaxhighlight lang="bash">
docker run -it --rm -v $(pwd)/images:/code/images -v $(pwd)/odm_orthophoto:/code/odm_orthophoto -v $(pwd)/odm_texturing:/code/odm_texturing -v $(pwd)/odm_georeferencing:/code/odm_georeferencing -v $(pwd)/odm_meshing:/code/odm_meshing -v $(pwd)/opensfm:/code/opensfm -v $(pwd)/odm_dem:/code/odm_dem -v $(pwd)/gcp_list.txt:/code/gcp_list.txt opendronemap/opendronemap --dtm --dsm --gcp gcp_list.txt
</syntaxhighlight>

With GCP (ignoring de - in y coordinate)

TIP: ignore the - (minus) in y axis.

<syntaxhighlight lang="bash">
cd uav_nysted-1
</syntaxhighlight>

<syntaxhighlight lang="bash">
docker run -it --rm -v $(pwd)/images:/code/images -v $(pwd)/odm_orthophoto:/code/odm_orthophoto -v $(pwd)/odm_texturing:/code/odm_texturing -v $(pwd)/odm_georeferencing:/code/odm_georeferencing -v $(pwd)/odm_meshing:/code/odm_meshing -v $(pwd)/opensfm:/code/opensfm -v $(pwd)/odm_dem:/code/odm_dem -v $(pwd)/gcp_list.txt:/code/gcp_list.txt opendronemap/opendronemap --dtm --dsm --gcp gcp_list.txt
</syntaxhighlight>

==== Windows ====

Install Docker

Configure docker (more CPU, more memory)

CPUs: 6

Memory: 12032 Mb

Swap: 4096 Mb

Create the projet folder structure

Project folder:
c:\Users\dlt265\Documents\uav_sckovskolen_feb20018_incl_GCP\

Image folder:
c:\Users\dlt265\Documents\uav_sckovskolen_feb20018_incl_GCP\images

Create folders for the OpenDroneMap output.

<syntaxhighlight lang="bash">
cd Documents\uav_sckovskolen_feb20018_incl_GCP
md odm_orthophoto
md odm_texturing
md odm_georeferencing
md odm_meshing
md opensfm
md odm_dem
</syntaxhighlight>

<syntaxhighlight lang="bash">
docker run -it --rm -v $pwd/images:/code/images -v $pwd/odm_orthophoto:/code/odm_orthophoto -v $pwd/odm_texturing:/code/odm_texturing -v $pwd/odm_georeferencing:/code/odm_georeferencing -v $pwd/odm_meshing:/code/odm_meshing -v $pwd/opensfm:/code/opensfm -v $pwd/odm_dem:/code/odm_dem opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd ~/Documentos/costanovadoprado2xgrid
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm --orthophoto-resolution 10.0 --mesh-octree-depth 10
</syntaxhighlight>

=== OpenSFM viewer (update) ===

<syntaxhighlight lang="bash">
sudo chown -R jgr:jgr *
git clone https://github.com/mapillary/OpenSfM.git
cd OpenSfM/viewer
ln -s ../../images .
python2 -m SimpleHTTPServer 7777
</syntaxhighlight>

=== OpenSFM viewer ===

<syntaxhighlight lang="bash">
jgr@zoe:~/Documentos/costanovadoprado$ sudo chown -R jgr:jgr *
jgr@zoe:~/Documentos/costanovadoprado$ cp -r ~/dev/OpenSfM/viewer opensfm
jgr@zoe:~/Documentos/costanovadoprado$ cd opensfm/
jgr@zoe:~/Documentos/costanovadoprado/opensfm$ ln -s ../images .
jgr@zoe:~/Documentos/costanovadoprado/opensfm$ python -m SimpleHTTPServer
Serving HTTP on 0.0.0.0 port 8000 ...
</syntaxhighlight>

http://localhost:8000/viewer/reconstruction.html#file=/reconstruction.json

==== OpenSFM view images on QGIS ====

/home/jgr/Documentos/costanovadoprado/images/DJI_0595.JPG

-8.7515052, 40.6114774, 22.4100000, 2018:08:23 10:05:11

/home/jgr/Documentos/costanovadoprado/opensfm/reference_lla.json

Centro aproximado do ortophoto resultante (adicionado ao projeto QGIS)

<syntaxhighlight lang="json">
{
"latitude": 40.61272372901514,
"altitude": 0,
"longitude": -8.752983409509966
}
</syntaxhighlight>

<syntaxhighlight lang="json">
"DJI_0595.JPG": {
"orientation": 1,
"camera": "v2 dji fc220 4000 3000 perspective 0.7222",
"gps_position": [
125.10012061257521,
-138.4010433354888,
22.407269606366754
],
"gps_dop": 15.0,
"rotation": [
2.1445873611073996,
-2.2856282209697523,
0.20066193557381898
],
"translation": [
-132.67853610360638,
133.40968771622724,
1.9668907291333997
],
"capture_time": 1535018711.0
},
</syntaxhighlight>

https://github.com/mapillary/OpenSfM/blob/master/opensfm/commands/export_geocoords.py

jgr@zoe:~/Documentos/costanovadoprado/opensfm$ wget https://raw.githubusercontent.com/mapillary/OpenSfM/master/opensfm/commands/export_geocoords.py

NÃO FUNCIONOU...

export_geocoords.py -dataset costanova

Ver: https://github.com/mapillary/OpenSfM/issues/183

=== webODM ===

https://github.com/OpenDroneMap/WebODM

<syntaxhighlight lang="bash">
git clone https://github.com/OpenDroneMap/WebODM --config core.autocrlf=input
cd WebODM
./webodm.sh start
</syntaxhighlight>

jgrocha/xxbatata

=== Tools ===

CloudCompare

QGIS Plugin Photo2Shape

Criar uma shapefile photos

Nas propriedades, no campo <syntaxhighlight inline lang="bash">filepath</syntaxhighlight> mudar para o tipo Fotografia.

=== Ground Control File ===

<syntaxhighlight lang="bash">
echo -7.778152 41.833203 957.575989 | cs2cs +init=epsg:4326 +to +init=epsg:3763
echo 708610.702 6209972.025 26.085 | cs2cs +init=epsg:25832 +to +init=epsg:32633

jgr@zoe:~/Documentos/sletten16maj2018-exif$ gdalsrsinfo epsg:32633 -o proj4
'+proj=utm +zone=33 +datum=WGS84 +units=m +no_defs '
jgr@zoe:~/Documentos/sletten16maj2018-exif$ gdalsrsinfo epsg:25832 -o proj4
'+proj=utm +zone=32 +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs '
</syntaxhighlight>

== Make my own OpenDroneMap image ==

=== Fork and clone ODM repository ===

<syntaxhighlight lang="bash">
git clone git@github.com:jgrocha/OpenDroneMap.git
cd OpenDroneMap
git checkout -b generate-laz-output
</syntaxhighlight>

=== Change source ===

=== Build new image ===

<syntaxhighlight lang="bash">
jgr@zoe:~/PycharmProjects/OpenDroneMap$ docker build --no-cache -t odm_altitude_0 .
</syntaxhighlight>

<syntaxhighlight lang="bash">
docker build -t odm_laz_image .
</syntaxhighlight>

=== Run new image ===

<syntaxhighlight lang="bash">
# cd "/mnt/bonn/nextCloud/Photos/DJI MAVIC PRO 2 Paradela/100MEDIA"
cd /mnt/bonn/nextCloud/Photos
ln -s 'DJI MAVIC PRO 2 Paradela/100MEDIA' images
export odmi=`pwd`
docker run --cpus 8 -it --rm -v $odmi/images:/code/images -v $odmi/odm_orthophoto:/code/odm_orthophoto -v $odmi/odm_texturing:/code/odm_texturing -v $odmi/odm_georeferencing:/code/odm_georeferencing -v $odmi/odm_meshing:/code/odm_meshing -v $odmi/opensfm:/code/opensfm -v $odmi/odm_dem:/code/odm_dem odm_altitude_0 --dtm --dsm --force-ccd 13.2
# --orthophoto-resolution 2.0 --mesh-octree-depth 2 --opensfm-processes 8
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd /home/jgr/Documentos/sletten16maj2018-gcp
export odmi=`pwd`
sudo rm -rf odm_georeferencing odm_meshing odm_orthophoto odm_texturing opensfm
docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
odm_laz_image --gcp gcp_list.txt --dtm --dsm
</syntaxhighlight>

The options for rerunning are: 'resize', 'opensfm', 'slam', 'cmvs', 'pmvs', 'odm_meshing', 'mvs_texturing', 'odm_georeferencing', 'odm_orthophoto'

<syntaxhighlight lang="bash">
docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
odm_laz_image --gcp gcp_list.txt --dtm --dsm --rerun-from odm_georeferencing
</syntaxhighlight>

=== Check the output ===

<syntaxhighlight lang="text">
running /code/build/bin/odm_georef -bundleFile /code/opensfm/bundle_r000.out -imagesPath /code/images -imagesListPath /code/opensfm/list_r000.out -inputFile /code/odm_texturing/odm_textured_model.obj -outputFile /code/odm_texturing/odm_textured_model_geo.obj -inputPointCloudFile /code/opensfm/depthmaps/merged.ply -outputPointCloudFile /code/odm_georeferencing/odm_georeferenced_model.ply -logFile /code/odm_georeferencing/odm_georeferencing_log.txt -outputTransformFile /code/odm_georeferencing/odm_georeferencing_transform.txt -georefFileOutputPath /code/odm_georeferencing/odm_georeferencing_model_geo.txt -gcpFile gcp_list.txt -outputCoordFile /code/odm_georeferencing/coords.txt
[DEBUG] running /code/SuperBuild/build/pdal/bin/pdal pipeline -i /code/odm_georeferencing/las.json --readers.ply.filename=/code/odm_georeferencing/odm_georeferenced_model.ply
PDAL: writers.las: Can't write LAZ output. PDAL not built with LASzip or LAZperf.
</syntaxhighlight>

<syntaxhighlight lang="json">
{
"pipeline": [
"untransformed.ply",
{
"type": "writers.las",
"a_srs": "+proj=utm +zone=33 +datum=WGS84 +units=m +no_defs ",
"offset_x": "334230.28164",
"offset_y": "6208095.41529",
"offset_z": "0",
"compression": "laszip",
"filename": "/code/odm_georeferencing/odm_georeferenced_model.laz"
}
]
}
</syntaxhighlight>

[[File:Captura de ecrã de 2018-06-17 14-34-10.png]]

=== Local pdal+LASzip ===

Build from source!

<syntaxhighlight lang="bash">
/usr/local/bin/pdal pipeline -i las.json --readers.ply.filename=odm_georeferenced_model.ply
-rw-r--r-- 1 jgr jgr 22661583 jun 17 11:47 odm_georeferenced_model.laz
-rw-r--r-- 1 jgr jgr 121586206 jun 17 11:42 odm_georeferenced_model.ply
</syntaxhighlight>

==== Previous result ====

[[File:Captura de ecrã de 2018-06-16 12-26-36.png]]

==== New result ====

=== Create Pull Request ===

close #845

=== Other fixes ===

epsg versus EPSG

== Point cloud classification ==

[DEBUG] running pdal info --boundary --filters.hexbin.edge_length=1 --filters.hexbin.threshold=0 /code/odm_georeferencing/odm_georeferenced_model.filtered.las > /code/odm_georeferencing/odm_georeferenced_model.boundary.json
PDAL: Argument references invalid/unused stage: 'filters.hexbin'.

Running OpenDroneMap

2019-03-04T06:06:34Z

Jgrocha: /* Drone Workshop */

=== Drone Workshop ===

Part I

0. The data

EPSG:25832

0.1 The images

0.2 The ground control points

0.2.1 Discuss how to get GCP: survey or from a reference dataset

0.3 The flight path

1. WebODM

1.2 Preparation and Installation

1.3 Run our first task

2. Overview of the products

2.1 Orthophoto

2.2 Point cloud

2.3 DSM

2.4 DTM

Part II

3. Fine tunning the data

3.1 Clip orthophoto

Create a mask layer

Clip

Enable JPG compression

3.2 Point cloud

Clip with pdal

Classify with pdal

4. Taking advantagle of the artifacts

[[Drone workshop print screens]]

1. Flight

WebODM

<syntaxhighlight lang="bash">
pip install docker-compose
</syntaxhighlight>

10:54

2. Data products

2.1 Orthophoto

Discussion: GCP, impact on the elevation model

Swipe tool

Point value: check ortho values

2.2 DEM/DSM

Discussion: difference between

Raster value

Profile tool

Visualization: hillshade

http://plas.io/

https://pdal.io/tutorial/pcl_ground/index.html#pcl-ground

<syntaxhighlight lang="bash">
-- original
pdal translate -i /code/odm_georeferencing/odm_georeferenced_model.laz -o /code/odm_georeferencing/odm_georeferenced_model.laz smrf --filters.smrf.cell=2 --filters.smrf.slope=10 --filters.smrf.window=10

-- VERY GOOD
pdal translate -i odm_georeferencing/odm_georeferenced_model.ply -o odm_georeferencing/odm_georeferenced_model_2.laz smrf --filters.smrf.cell=2 --filters.smrf.window=10

-- good
pdal ground -i odm_georeferencing/odm_georeferenced_model.ply -o odm_georeferencing/odm_georeferenced_model_3.laz
</syntaxhighlight>

2.3 Point cloud

What we get from the software

Visualization tools

https://pdal.io/workshop/exercises/analysis/dtm/dtm.html

3. Processing data products

3.1 Better classification

lasground

3.2 lasheight

3.3 lasclassify

=== DJI Mavic 2 PRO ===

[https://forum.dji.com/thread-167017-1-1.html Sensor size], [https://www.youtube.com/watch?v=xIncVCe6pg0 Video about sensor size]

==== Erro ====

Culpado: <syntaxhighlight lang="bash" inline>/home/jgr/PycharmProjects/OpenDroneMap/modules/odm_extract_utm</syntaxhighlight>

Todas as imagens estão com Exif.GPSInfo.GPSAltitude = 0.0

<syntaxhighlight lang="bash">
if (lon == 0.0 || lat == 0.0 || alt == 0.0) {
std::string error("Failed parsing GPS position for " + imageFilename);
throw UtmExtractorException(error);
}
</syntaxhighlight>

==== Remendo ====

<syntaxhighlight lang="bash">
exiv2 -pa DJI_0210.JPG
Exif.GPSInfo.GPSAltitude Rational 1 0.0 m

exiv2 -M"set Exif.GPSInfo.GPSAltitude Rational 1/10" DJI_0210.JPG
exiv2 -pa DJI_0210.JPG
Exif.GPSInfo.GPSAltitude Rational 1 0.1 m
</syntaxhighlight>

Chamada:

<syntaxhighlight lang="bash">
[INFO] Wrote images database: /code/images.json
[INFO] Found 106 usable images
[DEBUG] running /code/build/bin/odm_extract_utm -imagesPath /code/images/ -imageListFile /code/img_list.txt -outputCoordFile /code/odm_georeferencing/coords.txt -logFile /code/odm_georeferencing/odm_georeferencing_utm_log.txt
Error in OdmExtractUtm:
Failed parsing GPS position for DJI_0301.JPG
For more detailed information, see log file.
</syntaxhighlight>

<syntaxhighlight lang="text">
[INFO] Found 106 usable images
[WARNING] Could not generate coordinates file. Ignore if there is a GCP file. Error: Error in OdmExtractUtm:
Failed parsing GPS position for DJI_0301.JPG
For more detailed information, see log file.

(...)

Building objmodel:
Saving model... done.
Whole texturing procedure took: 225.586s
[INFO] Running ODM Texturing Cell - Finished
[INFO] Running ODM Georeferencing Cell
[WARNING] Georeferencing failed. Make sure your photos have geotags in the EXIF or you have provided a GCP file.
[INFO] Running ODM Georeferencing Cell - Finished
[INFO] Running ODM DEM Cell
[INFO] Classify: True
[INFO] Create DSM: True
[INFO] Create DTM: True
[INFO] DEM input file /code/odm_georeferencing/odm_georeferenced_model.las found: False
[WARNING] DEM will not be generated
[INFO] Running ODM DEM Cell - Finished
[INFO] Running ODM Orthophoto Cell
[DEBUG] running /code/build/bin/odm_orthophoto -inputFile /code/odm_texturing/odm_textured_model.obj -logFile /code/odm_orthophoto/odm_orthophoto_log.txt -outputFile /code/odm_orthophoto/odm_orthophoto.png -resolution 10.0 -outputCornerFile /code/odm_orthophoto/odm_orthophoto_corners.txt
[WARNING] No geo-referenced orthophoto created due to missing geo-referencing or corner coordinates.
[INFO] Running ODM OrthoPhoto Cell - Finished
[INFO] OpenDroneMap app finished - Sat Dec 29 22:12:22 2018
</syntaxhighlight>

=== Running docker OpenDroneMap ===

==== Update to last OpenDroneMap docker image ====

<syntaxhighlight lang="bash">
docker pull opendronemap/opendronemap
</syntaxhighlight>

==== OpenDroneMap docker image ====

# Install docker
# Add you user to docker group
# sudo -H pip install requests

<syntaxhighlight lang="bash">
mkdir OpenDroneMap
cd OpenDroneMap
git clone git@github.com:OpenDroneMap/odm_data_aukerman.git
cd odm_data_aukerman

export odmi=`pwd`
ls -l $odmi

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd /home/jgr/Documentos/sletten16maj2018-gcp
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
opendronemap/opendronemap --gcp gcp_list.txt --dtm --dsm
</syntaxhighlight>

Sem GCP:

<syntaxhighlight lang="bash">
cd ~/Documentos/costanovadoprado/
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm --orthophoto-resolution 10.0
</syntaxhighlight>

Nota: os ortos estão a ficar com muitas interferências do modelo 3D, nas áreas urbanas.

Related problem: http://community.opendronemap.org/t/buildings/929

Será que voar com a câmara a 75 graus ajuda? Fiz um voo com Double Grid, com a camara a 70 graus (default do Pix4d capture).

==== Mac ====

1. Install Docker

2. <syntaxhighlight lang="bash">
docker run -it --rm -v $(pwd)/images:/code/images -v $(pwd)/odm_orthophoto:/code/odm_orthophoto -v $(pwd)/odm_texturing:/code/odm_texturing -v $(pwd)/odm_georeferencing:/code/odm_georeferencing -v $(pwd)/odm_meshing:/code/odm_meshing -v $(pwd)/opensfm:/code/opensfm -v $(pwd)/odm_dem:/code/odm_dem opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

With GCP (calculating 3000-y coordinate)

<syntaxhighlight lang="bash">
docker run -it --rm -v $(pwd)/images:/code/images -v $(pwd)/odm_orthophoto:/code/odm_orthophoto -v $(pwd)/odm_texturing:/code/odm_texturing -v $(pwd)/odm_georeferencing:/code/odm_georeferencing -v $(pwd)/odm_meshing:/code/odm_meshing -v $(pwd)/opensfm:/code/opensfm -v $(pwd)/odm_dem:/code/odm_dem -v $(pwd)/gcp_list.txt:/code/gcp_list.txt opendronemap/opendronemap --dtm --dsm --gcp gcp_list.txt
</syntaxhighlight>

With GCP (ignoring de - in y coordinate)

TIP: ignore the - (minus) in y axis.

<syntaxhighlight lang="bash">
cd uav_nysted-1
</syntaxhighlight>

<syntaxhighlight lang="bash">
docker run -it --rm -v $(pwd)/images:/code/images -v $(pwd)/odm_orthophoto:/code/odm_orthophoto -v $(pwd)/odm_texturing:/code/odm_texturing -v $(pwd)/odm_georeferencing:/code/odm_georeferencing -v $(pwd)/odm_meshing:/code/odm_meshing -v $(pwd)/opensfm:/code/opensfm -v $(pwd)/odm_dem:/code/odm_dem -v $(pwd)/gcp_list.txt:/code/gcp_list.txt opendronemap/opendronemap --dtm --dsm --gcp gcp_list.txt
</syntaxhighlight>

==== Windows ====

Install Docker

Configure docker (more CPU, more memory)

CPUs: 6

Memory: 12032 Mb

Swap: 4096 Mb

Create the projet folder structure

Project folder:
c:\Users\dlt265\Documents\uav_sckovskolen_feb20018_incl_GCP\

Image folder:
c:\Users\dlt265\Documents\uav_sckovskolen_feb20018_incl_GCP\images

Create folders for the OpenDroneMap output.

<syntaxhighlight lang="bash">
cd Documents\uav_sckovskolen_feb20018_incl_GCP
md odm_orthophoto
md odm_texturing
md odm_georeferencing
md odm_meshing
md opensfm
md odm_dem
</syntaxhighlight>

<syntaxhighlight lang="bash">
docker run -it --rm -v $pwd/images:/code/images -v $pwd/odm_orthophoto:/code/odm_orthophoto -v $pwd/odm_texturing:/code/odm_texturing -v $pwd/odm_georeferencing:/code/odm_georeferencing -v $pwd/odm_meshing:/code/odm_meshing -v $pwd/opensfm:/code/opensfm -v $pwd/odm_dem:/code/odm_dem opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd ~/Documentos/costanovadoprado2xgrid
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm --orthophoto-resolution 10.0 --mesh-octree-depth 10
</syntaxhighlight>

=== OpenSFM viewer (update) ===

<syntaxhighlight lang="bash">
sudo chown -R jgr:jgr *
git clone https://github.com/mapillary/OpenSfM.git
cd OpenSfM/viewer
ln -s ../../images .
python2 -m SimpleHTTPServer 7777
</syntaxhighlight>

=== OpenSFM viewer ===

<syntaxhighlight lang="bash">
jgr@zoe:~/Documentos/costanovadoprado$ sudo chown -R jgr:jgr *
jgr@zoe:~/Documentos/costanovadoprado$ cp -r ~/dev/OpenSfM/viewer opensfm
jgr@zoe:~/Documentos/costanovadoprado$ cd opensfm/
jgr@zoe:~/Documentos/costanovadoprado/opensfm$ ln -s ../images .
jgr@zoe:~/Documentos/costanovadoprado/opensfm$ python -m SimpleHTTPServer
Serving HTTP on 0.0.0.0 port 8000 ...
</syntaxhighlight>

http://localhost:8000/viewer/reconstruction.html#file=/reconstruction.json

==== OpenSFM view images on QGIS ====

/home/jgr/Documentos/costanovadoprado/images/DJI_0595.JPG

-8.7515052, 40.6114774, 22.4100000, 2018:08:23 10:05:11

/home/jgr/Documentos/costanovadoprado/opensfm/reference_lla.json

Centro aproximado do ortophoto resultante (adicionado ao projeto QGIS)

<syntaxhighlight lang="json">
{
"latitude": 40.61272372901514,
"altitude": 0,
"longitude": -8.752983409509966
}
</syntaxhighlight>

<syntaxhighlight lang="json">
"DJI_0595.JPG": {
"orientation": 1,
"camera": "v2 dji fc220 4000 3000 perspective 0.7222",
"gps_position": [
125.10012061257521,
-138.4010433354888,
22.407269606366754
],
"gps_dop": 15.0,
"rotation": [
2.1445873611073996,
-2.2856282209697523,
0.20066193557381898
],
"translation": [
-132.67853610360638,
133.40968771622724,
1.9668907291333997
],
"capture_time": 1535018711.0
},
</syntaxhighlight>

https://github.com/mapillary/OpenSfM/blob/master/opensfm/commands/export_geocoords.py

jgr@zoe:~/Documentos/costanovadoprado/opensfm$ wget https://raw.githubusercontent.com/mapillary/OpenSfM/master/opensfm/commands/export_geocoords.py

NÃO FUNCIONOU...

export_geocoords.py -dataset costanova

Ver: https://github.com/mapillary/OpenSfM/issues/183

=== webODM ===

https://github.com/OpenDroneMap/WebODM

<syntaxhighlight lang="bash">
git clone https://github.com/OpenDroneMap/WebODM --config core.autocrlf=input
cd WebODM
./webodm.sh start
</syntaxhighlight>

jgrocha/xxbatata

=== Tools ===

CloudCompare

QGIS Plugin Photo2Shape

Criar uma shapefile photos

Nas propriedades, no campo <syntaxhighlight inline lang="bash">filepath</syntaxhighlight> mudar para o tipo Fotografia.

=== Ground Control File ===

<syntaxhighlight lang="bash">
echo -7.778152 41.833203 957.575989 | cs2cs +init=epsg:4326 +to +init=epsg:3763
echo 708610.702 6209972.025 26.085 | cs2cs +init=epsg:25832 +to +init=epsg:32633

jgr@zoe:~/Documentos/sletten16maj2018-exif$ gdalsrsinfo epsg:32633 -o proj4
'+proj=utm +zone=33 +datum=WGS84 +units=m +no_defs '
jgr@zoe:~/Documentos/sletten16maj2018-exif$ gdalsrsinfo epsg:25832 -o proj4
'+proj=utm +zone=32 +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs '
</syntaxhighlight>

== Make my own OpenDroneMap image ==

=== Fork and clone ODM repository ===

<syntaxhighlight lang="bash">
git clone git@github.com:jgrocha/OpenDroneMap.git
cd OpenDroneMap
git checkout -b generate-laz-output
</syntaxhighlight>

=== Change source ===

=== Build new image ===

<syntaxhighlight lang="bash">
jgr@zoe:~/PycharmProjects/OpenDroneMap$ docker build --no-cache -t odm_altitude_0 .
</syntaxhighlight>

<syntaxhighlight lang="bash">
docker build -t odm_laz_image .
</syntaxhighlight>

=== Run new image ===

<syntaxhighlight lang="bash">
# cd "/mnt/bonn/nextCloud/Photos/DJI MAVIC PRO 2 Paradela/100MEDIA"
cd /mnt/bonn/nextCloud/Photos
ln -s 'DJI MAVIC PRO 2 Paradela/100MEDIA' images
export odmi=`pwd`
docker run --cpus 8 -it --rm -v $odmi/images:/code/images -v $odmi/odm_orthophoto:/code/odm_orthophoto -v $odmi/odm_texturing:/code/odm_texturing -v $odmi/odm_georeferencing:/code/odm_georeferencing -v $odmi/odm_meshing:/code/odm_meshing -v $odmi/opensfm:/code/opensfm -v $odmi/odm_dem:/code/odm_dem odm_altitude_0 --dtm --dsm --force-ccd 13.2
# --orthophoto-resolution 2.0 --mesh-octree-depth 2 --opensfm-processes 8
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd /home/jgr/Documentos/sletten16maj2018-gcp
export odmi=`pwd`
sudo rm -rf odm_georeferencing odm_meshing odm_orthophoto odm_texturing opensfm
docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
odm_laz_image --gcp gcp_list.txt --dtm --dsm
</syntaxhighlight>

The options for rerunning are: 'resize', 'opensfm', 'slam', 'cmvs', 'pmvs', 'odm_meshing', 'mvs_texturing', 'odm_georeferencing', 'odm_orthophoto'

<syntaxhighlight lang="bash">
docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
odm_laz_image --gcp gcp_list.txt --dtm --dsm --rerun-from odm_georeferencing
</syntaxhighlight>

=== Check the output ===

<syntaxhighlight lang="text">
running /code/build/bin/odm_georef -bundleFile /code/opensfm/bundle_r000.out -imagesPath /code/images -imagesListPath /code/opensfm/list_r000.out -inputFile /code/odm_texturing/odm_textured_model.obj -outputFile /code/odm_texturing/odm_textured_model_geo.obj -inputPointCloudFile /code/opensfm/depthmaps/merged.ply -outputPointCloudFile /code/odm_georeferencing/odm_georeferenced_model.ply -logFile /code/odm_georeferencing/odm_georeferencing_log.txt -outputTransformFile /code/odm_georeferencing/odm_georeferencing_transform.txt -georefFileOutputPath /code/odm_georeferencing/odm_georeferencing_model_geo.txt -gcpFile gcp_list.txt -outputCoordFile /code/odm_georeferencing/coords.txt
[DEBUG] running /code/SuperBuild/build/pdal/bin/pdal pipeline -i /code/odm_georeferencing/las.json --readers.ply.filename=/code/odm_georeferencing/odm_georeferenced_model.ply
PDAL: writers.las: Can't write LAZ output. PDAL not built with LASzip or LAZperf.
</syntaxhighlight>

<syntaxhighlight lang="json">
{
"pipeline": [
"untransformed.ply",
{
"type": "writers.las",
"a_srs": "+proj=utm +zone=33 +datum=WGS84 +units=m +no_defs ",
"offset_x": "334230.28164",
"offset_y": "6208095.41529",
"offset_z": "0",
"compression": "laszip",
"filename": "/code/odm_georeferencing/odm_georeferenced_model.laz"
}
]
}
</syntaxhighlight>

[[File:Captura de ecrã de 2018-06-17 14-34-10.png]]

=== Local pdal+LASzip ===

Build from source!

<syntaxhighlight lang="bash">
/usr/local/bin/pdal pipeline -i las.json --readers.ply.filename=odm_georeferenced_model.ply
-rw-r--r-- 1 jgr jgr 22661583 jun 17 11:47 odm_georeferenced_model.laz
-rw-r--r-- 1 jgr jgr 121586206 jun 17 11:42 odm_georeferenced_model.ply
</syntaxhighlight>

==== Previous result ====

[[File:Captura de ecrã de 2018-06-16 12-26-36.png]]

==== New result ====

=== Create Pull Request ===

close #845

=== Other fixes ===

epsg versus EPSG

== Point cloud classification ==

[DEBUG] running pdal info --boundary --filters.hexbin.edge_length=1 --filters.hexbin.threshold=0 /code/odm_georeferencing/odm_georeferenced_model.filtered.las > /code/odm_georeferencing/odm_georeferenced_model.boundary.json
PDAL: Argument references invalid/unused stage: 'filters.hexbin'.

Running OpenDroneMap

2019-02-28T03:07:17Z

Jgrocha: /* Mac */

=== Drone Workshop ===

[[Drone workshop print screens]]

1. Flight

WebODM

<syntaxhighlight lang="bash">
pip install docker-compose
</syntaxhighlight>

10:54

2. Data products

2.1 Orthophoto

Discussion: GCP, impact on the elevation model

Swipe tool

Point value: check ortho values

2.2 DEM/DSM

Discussion: difference between

Raster value

Profile tool

Visualization: hillshade

http://plas.io/

https://pdal.io/tutorial/pcl_ground/index.html#pcl-ground

<syntaxhighlight lang="bash">
-- original
pdal translate -i /code/odm_georeferencing/odm_georeferenced_model.laz -o /code/odm_georeferencing/odm_georeferenced_model.laz smrf --filters.smrf.cell=2 --filters.smrf.slope=10 --filters.smrf.window=10

-- VERY GOOD
pdal translate -i odm_georeferencing/odm_georeferenced_model.ply -o odm_georeferencing/odm_georeferenced_model_2.laz smrf --filters.smrf.cell=2 --filters.smrf.window=10

-- good
pdal ground -i odm_georeferencing/odm_georeferenced_model.ply -o odm_georeferencing/odm_georeferenced_model_3.laz
</syntaxhighlight>

2.3 Point cloud

What we get from the software

Visualization tools

https://pdal.io/workshop/exercises/analysis/dtm/dtm.html

3. Processing data products

3.1 Better classification

lasground

3.2 lasheight

3.3 lasclassify

=== DJI Mavic 2 PRO ===

[https://forum.dji.com/thread-167017-1-1.html Sensor size], [https://www.youtube.com/watch?v=xIncVCe6pg0 Video about sensor size]

==== Erro ====

Culpado: <syntaxhighlight lang="bash" inline>/home/jgr/PycharmProjects/OpenDroneMap/modules/odm_extract_utm</syntaxhighlight>

Todas as imagens estão com Exif.GPSInfo.GPSAltitude = 0.0

<syntaxhighlight lang="bash">
if (lon == 0.0 || lat == 0.0 || alt == 0.0) {
std::string error("Failed parsing GPS position for " + imageFilename);
throw UtmExtractorException(error);
}
</syntaxhighlight>

==== Remendo ====

<syntaxhighlight lang="bash">
exiv2 -pa DJI_0210.JPG
Exif.GPSInfo.GPSAltitude Rational 1 0.0 m

exiv2 -M"set Exif.GPSInfo.GPSAltitude Rational 1/10" DJI_0210.JPG
exiv2 -pa DJI_0210.JPG
Exif.GPSInfo.GPSAltitude Rational 1 0.1 m
</syntaxhighlight>

Chamada:

<syntaxhighlight lang="bash">
[INFO] Wrote images database: /code/images.json
[INFO] Found 106 usable images
[DEBUG] running /code/build/bin/odm_extract_utm -imagesPath /code/images/ -imageListFile /code/img_list.txt -outputCoordFile /code/odm_georeferencing/coords.txt -logFile /code/odm_georeferencing/odm_georeferencing_utm_log.txt
Error in OdmExtractUtm:
Failed parsing GPS position for DJI_0301.JPG
For more detailed information, see log file.
</syntaxhighlight>

<syntaxhighlight lang="text">
[INFO] Found 106 usable images
[WARNING] Could not generate coordinates file. Ignore if there is a GCP file. Error: Error in OdmExtractUtm:
Failed parsing GPS position for DJI_0301.JPG
For more detailed information, see log file.

(...)

Building objmodel:
Saving model... done.
Whole texturing procedure took: 225.586s
[INFO] Running ODM Texturing Cell - Finished
[INFO] Running ODM Georeferencing Cell
[WARNING] Georeferencing failed. Make sure your photos have geotags in the EXIF or you have provided a GCP file.
[INFO] Running ODM Georeferencing Cell - Finished
[INFO] Running ODM DEM Cell
[INFO] Classify: True
[INFO] Create DSM: True
[INFO] Create DTM: True
[INFO] DEM input file /code/odm_georeferencing/odm_georeferenced_model.las found: False
[WARNING] DEM will not be generated
[INFO] Running ODM DEM Cell - Finished
[INFO] Running ODM Orthophoto Cell
[DEBUG] running /code/build/bin/odm_orthophoto -inputFile /code/odm_texturing/odm_textured_model.obj -logFile /code/odm_orthophoto/odm_orthophoto_log.txt -outputFile /code/odm_orthophoto/odm_orthophoto.png -resolution 10.0 -outputCornerFile /code/odm_orthophoto/odm_orthophoto_corners.txt
[WARNING] No geo-referenced orthophoto created due to missing geo-referencing or corner coordinates.
[INFO] Running ODM OrthoPhoto Cell - Finished
[INFO] OpenDroneMap app finished - Sat Dec 29 22:12:22 2018
</syntaxhighlight>

=== Running docker OpenDroneMap ===

==== Update to last OpenDroneMap docker image ====

<syntaxhighlight lang="bash">
docker pull opendronemap/opendronemap
</syntaxhighlight>

==== OpenDroneMap docker image ====

# Install docker
# Add you user to docker group
# sudo -H pip install requests

<syntaxhighlight lang="bash">
mkdir OpenDroneMap
cd OpenDroneMap
git clone git@github.com:OpenDroneMap/odm_data_aukerman.git
cd odm_data_aukerman

export odmi=`pwd`
ls -l $odmi

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd /home/jgr/Documentos/sletten16maj2018-gcp
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
opendronemap/opendronemap --gcp gcp_list.txt --dtm --dsm
</syntaxhighlight>

Sem GCP:

<syntaxhighlight lang="bash">
cd ~/Documentos/costanovadoprado/
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm --orthophoto-resolution 10.0
</syntaxhighlight>

Nota: os ortos estão a ficar com muitas interferências do modelo 3D, nas áreas urbanas.

Related problem: http://community.opendronemap.org/t/buildings/929

Será que voar com a câmara a 75 graus ajuda? Fiz um voo com Double Grid, com a camara a 70 graus (default do Pix4d capture).

==== Mac ====

1. Install Docker

2. <syntaxhighlight lang="bash">
docker run -it --rm -v $(pwd)/images:/code/images -v $(pwd)/odm_orthophoto:/code/odm_orthophoto -v $(pwd)/odm_texturing:/code/odm_texturing -v $(pwd)/odm_georeferencing:/code/odm_georeferencing -v $(pwd)/odm_meshing:/code/odm_meshing -v $(pwd)/opensfm:/code/opensfm -v $(pwd)/odm_dem:/code/odm_dem opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

With GCP (calculating 3000-y coordinate)

<syntaxhighlight lang="bash">
docker run -it --rm -v $(pwd)/images:/code/images -v $(pwd)/odm_orthophoto:/code/odm_orthophoto -v $(pwd)/odm_texturing:/code/odm_texturing -v $(pwd)/odm_georeferencing:/code/odm_georeferencing -v $(pwd)/odm_meshing:/code/odm_meshing -v $(pwd)/opensfm:/code/opensfm -v $(pwd)/odm_dem:/code/odm_dem -v $(pwd)/gcp_list.txt:/code/gcp_list.txt opendronemap/opendronemap --dtm --dsm --gcp gcp_list.txt
</syntaxhighlight>

With GCP (ignoring de - in y coordinate)

TIP: ignore the - (minus) in y axis.

<syntaxhighlight lang="bash">
cd uav_nysted-1
</syntaxhighlight>

<syntaxhighlight lang="bash">
docker run -it --rm -v $(pwd)/images:/code/images -v $(pwd)/odm_orthophoto:/code/odm_orthophoto -v $(pwd)/odm_texturing:/code/odm_texturing -v $(pwd)/odm_georeferencing:/code/odm_georeferencing -v $(pwd)/odm_meshing:/code/odm_meshing -v $(pwd)/opensfm:/code/opensfm -v $(pwd)/odm_dem:/code/odm_dem -v $(pwd)/gcp_list.txt:/code/gcp_list.txt opendronemap/opendronemap --dtm --dsm --gcp gcp_list.txt
</syntaxhighlight>

==== Windows ====

Install Docker

Configure docker (more CPU, more memory)

CPUs: 6

Memory: 12032 Mb

Swap: 4096 Mb

Create the projet folder structure

Project folder:
c:\Users\dlt265\Documents\uav_sckovskolen_feb20018_incl_GCP\

Image folder:
c:\Users\dlt265\Documents\uav_sckovskolen_feb20018_incl_GCP\images

Create folders for the OpenDroneMap output.

<syntaxhighlight lang="bash">
cd Documents\uav_sckovskolen_feb20018_incl_GCP
md odm_orthophoto
md odm_texturing
md odm_georeferencing
md odm_meshing
md opensfm
md odm_dem
</syntaxhighlight>

<syntaxhighlight lang="bash">
docker run -it --rm -v $pwd/images:/code/images -v $pwd/odm_orthophoto:/code/odm_orthophoto -v $pwd/odm_texturing:/code/odm_texturing -v $pwd/odm_georeferencing:/code/odm_georeferencing -v $pwd/odm_meshing:/code/odm_meshing -v $pwd/opensfm:/code/opensfm -v $pwd/odm_dem:/code/odm_dem opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd ~/Documentos/costanovadoprado2xgrid
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm --orthophoto-resolution 10.0 --mesh-octree-depth 10
</syntaxhighlight>

=== OpenSFM viewer (update) ===

<syntaxhighlight lang="bash">
sudo chown -R jgr:jgr *
git clone https://github.com/mapillary/OpenSfM.git
cd OpenSfM/viewer
ln -s ../../images .
python2 -m SimpleHTTPServer 7777
</syntaxhighlight>

=== OpenSFM viewer ===

<syntaxhighlight lang="bash">
jgr@zoe:~/Documentos/costanovadoprado$ sudo chown -R jgr:jgr *
jgr@zoe:~/Documentos/costanovadoprado$ cp -r ~/dev/OpenSfM/viewer opensfm
jgr@zoe:~/Documentos/costanovadoprado$ cd opensfm/
jgr@zoe:~/Documentos/costanovadoprado/opensfm$ ln -s ../images .
jgr@zoe:~/Documentos/costanovadoprado/opensfm$ python -m SimpleHTTPServer
Serving HTTP on 0.0.0.0 port 8000 ...
</syntaxhighlight>

http://localhost:8000/viewer/reconstruction.html#file=/reconstruction.json

==== OpenSFM view images on QGIS ====

/home/jgr/Documentos/costanovadoprado/images/DJI_0595.JPG

-8.7515052, 40.6114774, 22.4100000, 2018:08:23 10:05:11

/home/jgr/Documentos/costanovadoprado/opensfm/reference_lla.json

Centro aproximado do ortophoto resultante (adicionado ao projeto QGIS)

<syntaxhighlight lang="json">
{
"latitude": 40.61272372901514,
"altitude": 0,
"longitude": -8.752983409509966
}
</syntaxhighlight>

<syntaxhighlight lang="json">
"DJI_0595.JPG": {
"orientation": 1,
"camera": "v2 dji fc220 4000 3000 perspective 0.7222",
"gps_position": [
125.10012061257521,
-138.4010433354888,
22.407269606366754
],
"gps_dop": 15.0,
"rotation": [
2.1445873611073996,
-2.2856282209697523,
0.20066193557381898
],
"translation": [
-132.67853610360638,
133.40968771622724,
1.9668907291333997
],
"capture_time": 1535018711.0
},
</syntaxhighlight>

https://github.com/mapillary/OpenSfM/blob/master/opensfm/commands/export_geocoords.py

jgr@zoe:~/Documentos/costanovadoprado/opensfm$ wget https://raw.githubusercontent.com/mapillary/OpenSfM/master/opensfm/commands/export_geocoords.py

NÃO FUNCIONOU...

export_geocoords.py -dataset costanova

Ver: https://github.com/mapillary/OpenSfM/issues/183

=== webODM ===

https://github.com/OpenDroneMap/WebODM

<syntaxhighlight lang="bash">
git clone https://github.com/OpenDroneMap/WebODM --config core.autocrlf=input
cd WebODM
./webodm.sh start
</syntaxhighlight>

jgrocha/xxbatata

=== Tools ===

CloudCompare

QGIS Plugin Photo2Shape

Criar uma shapefile photos

Nas propriedades, no campo <syntaxhighlight inline lang="bash">filepath</syntaxhighlight> mudar para o tipo Fotografia.

=== Ground Control File ===

<syntaxhighlight lang="bash">
echo -7.778152 41.833203 957.575989 | cs2cs +init=epsg:4326 +to +init=epsg:3763
echo 708610.702 6209972.025 26.085 | cs2cs +init=epsg:25832 +to +init=epsg:32633

jgr@zoe:~/Documentos/sletten16maj2018-exif$ gdalsrsinfo epsg:32633 -o proj4
'+proj=utm +zone=33 +datum=WGS84 +units=m +no_defs '
jgr@zoe:~/Documentos/sletten16maj2018-exif$ gdalsrsinfo epsg:25832 -o proj4
'+proj=utm +zone=32 +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs '
</syntaxhighlight>

== Make my own OpenDroneMap image ==

=== Fork and clone ODM repository ===

<syntaxhighlight lang="bash">
git clone git@github.com:jgrocha/OpenDroneMap.git
cd OpenDroneMap
git checkout -b generate-laz-output
</syntaxhighlight>

=== Change source ===

=== Build new image ===

<syntaxhighlight lang="bash">
jgr@zoe:~/PycharmProjects/OpenDroneMap$ docker build --no-cache -t odm_altitude_0 .
</syntaxhighlight>

<syntaxhighlight lang="bash">
docker build -t odm_laz_image .
</syntaxhighlight>

=== Run new image ===

<syntaxhighlight lang="bash">
# cd "/mnt/bonn/nextCloud/Photos/DJI MAVIC PRO 2 Paradela/100MEDIA"
cd /mnt/bonn/nextCloud/Photos
ln -s 'DJI MAVIC PRO 2 Paradela/100MEDIA' images
export odmi=`pwd`
docker run --cpus 8 -it --rm -v $odmi/images:/code/images -v $odmi/odm_orthophoto:/code/odm_orthophoto -v $odmi/odm_texturing:/code/odm_texturing -v $odmi/odm_georeferencing:/code/odm_georeferencing -v $odmi/odm_meshing:/code/odm_meshing -v $odmi/opensfm:/code/opensfm -v $odmi/odm_dem:/code/odm_dem odm_altitude_0 --dtm --dsm --force-ccd 13.2
# --orthophoto-resolution 2.0 --mesh-octree-depth 2 --opensfm-processes 8
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd /home/jgr/Documentos/sletten16maj2018-gcp
export odmi=`pwd`
sudo rm -rf odm_georeferencing odm_meshing odm_orthophoto odm_texturing opensfm
docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
odm_laz_image --gcp gcp_list.txt --dtm --dsm
</syntaxhighlight>

The options for rerunning are: 'resize', 'opensfm', 'slam', 'cmvs', 'pmvs', 'odm_meshing', 'mvs_texturing', 'odm_georeferencing', 'odm_orthophoto'

<syntaxhighlight lang="bash">
docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
odm_laz_image --gcp gcp_list.txt --dtm --dsm --rerun-from odm_georeferencing
</syntaxhighlight>

=== Check the output ===

<syntaxhighlight lang="text">
running /code/build/bin/odm_georef -bundleFile /code/opensfm/bundle_r000.out -imagesPath /code/images -imagesListPath /code/opensfm/list_r000.out -inputFile /code/odm_texturing/odm_textured_model.obj -outputFile /code/odm_texturing/odm_textured_model_geo.obj -inputPointCloudFile /code/opensfm/depthmaps/merged.ply -outputPointCloudFile /code/odm_georeferencing/odm_georeferenced_model.ply -logFile /code/odm_georeferencing/odm_georeferencing_log.txt -outputTransformFile /code/odm_georeferencing/odm_georeferencing_transform.txt -georefFileOutputPath /code/odm_georeferencing/odm_georeferencing_model_geo.txt -gcpFile gcp_list.txt -outputCoordFile /code/odm_georeferencing/coords.txt
[DEBUG] running /code/SuperBuild/build/pdal/bin/pdal pipeline -i /code/odm_georeferencing/las.json --readers.ply.filename=/code/odm_georeferencing/odm_georeferenced_model.ply
PDAL: writers.las: Can't write LAZ output. PDAL not built with LASzip or LAZperf.
</syntaxhighlight>

<syntaxhighlight lang="json">
{
"pipeline": [
"untransformed.ply",
{
"type": "writers.las",
"a_srs": "+proj=utm +zone=33 +datum=WGS84 +units=m +no_defs ",
"offset_x": "334230.28164",
"offset_y": "6208095.41529",
"offset_z": "0",
"compression": "laszip",
"filename": "/code/odm_georeferencing/odm_georeferenced_model.laz"
}
]
}
</syntaxhighlight>

[[File:Captura de ecrã de 2018-06-17 14-34-10.png]]

=== Local pdal+LASzip ===

Build from source!

<syntaxhighlight lang="bash">
/usr/local/bin/pdal pipeline -i las.json --readers.ply.filename=odm_georeferenced_model.ply
-rw-r--r-- 1 jgr jgr 22661583 jun 17 11:47 odm_georeferenced_model.laz
-rw-r--r-- 1 jgr jgr 121586206 jun 17 11:42 odm_georeferenced_model.ply
</syntaxhighlight>

==== Previous result ====

[[File:Captura de ecrã de 2018-06-16 12-26-36.png]]

==== New result ====

=== Create Pull Request ===

close #845

=== Other fixes ===

epsg versus EPSG

== Point cloud classification ==

[DEBUG] running pdal info --boundary --filters.hexbin.edge_length=1 --filters.hexbin.threshold=0 /code/odm_georeferencing/odm_georeferenced_model.filtered.las > /code/odm_georeferencing/odm_georeferenced_model.boundary.json
PDAL: Argument references invalid/unused stage: 'filters.hexbin'.

Running OpenDroneMap

2019-02-28T02:41:06Z

Jgrocha: /* Mac */

=== Drone Workshop ===

[[Drone workshop print screens]]

1. Flight

WebODM

<syntaxhighlight lang="bash">
pip install docker-compose
</syntaxhighlight>

10:54

2. Data products

2.1 Orthophoto

Discussion: GCP, impact on the elevation model

Swipe tool

Point value: check ortho values

2.2 DEM/DSM

Discussion: difference between

Raster value

Profile tool

Visualization: hillshade

http://plas.io/

https://pdal.io/tutorial/pcl_ground/index.html#pcl-ground

<syntaxhighlight lang="bash">
-- original
pdal translate -i /code/odm_georeferencing/odm_georeferenced_model.laz -o /code/odm_georeferencing/odm_georeferenced_model.laz smrf --filters.smrf.cell=2 --filters.smrf.slope=10 --filters.smrf.window=10

-- VERY GOOD
pdal translate -i odm_georeferencing/odm_georeferenced_model.ply -o odm_georeferencing/odm_georeferenced_model_2.laz smrf --filters.smrf.cell=2 --filters.smrf.window=10

-- good
pdal ground -i odm_georeferencing/odm_georeferenced_model.ply -o odm_georeferencing/odm_georeferenced_model_3.laz
</syntaxhighlight>

2.3 Point cloud

What we get from the software

Visualization tools

https://pdal.io/workshop/exercises/analysis/dtm/dtm.html

3. Processing data products

3.1 Better classification

lasground

3.2 lasheight

3.3 lasclassify

=== DJI Mavic 2 PRO ===

[https://forum.dji.com/thread-167017-1-1.html Sensor size], [https://www.youtube.com/watch?v=xIncVCe6pg0 Video about sensor size]

==== Erro ====

Culpado: <syntaxhighlight lang="bash" inline>/home/jgr/PycharmProjects/OpenDroneMap/modules/odm_extract_utm</syntaxhighlight>

Todas as imagens estão com Exif.GPSInfo.GPSAltitude = 0.0

<syntaxhighlight lang="bash">
if (lon == 0.0 || lat == 0.0 || alt == 0.0) {
std::string error("Failed parsing GPS position for " + imageFilename);
throw UtmExtractorException(error);
}
</syntaxhighlight>

==== Remendo ====

<syntaxhighlight lang="bash">
exiv2 -pa DJI_0210.JPG
Exif.GPSInfo.GPSAltitude Rational 1 0.0 m

exiv2 -M"set Exif.GPSInfo.GPSAltitude Rational 1/10" DJI_0210.JPG
exiv2 -pa DJI_0210.JPG
Exif.GPSInfo.GPSAltitude Rational 1 0.1 m
</syntaxhighlight>

Chamada:

<syntaxhighlight lang="bash">
[INFO] Wrote images database: /code/images.json
[INFO] Found 106 usable images
[DEBUG] running /code/build/bin/odm_extract_utm -imagesPath /code/images/ -imageListFile /code/img_list.txt -outputCoordFile /code/odm_georeferencing/coords.txt -logFile /code/odm_georeferencing/odm_georeferencing_utm_log.txt
Error in OdmExtractUtm:
Failed parsing GPS position for DJI_0301.JPG
For more detailed information, see log file.
</syntaxhighlight>

<syntaxhighlight lang="text">
[INFO] Found 106 usable images
[WARNING] Could not generate coordinates file. Ignore if there is a GCP file. Error: Error in OdmExtractUtm:
Failed parsing GPS position for DJI_0301.JPG
For more detailed information, see log file.

(...)

Building objmodel:
Saving model... done.
Whole texturing procedure took: 225.586s
[INFO] Running ODM Texturing Cell - Finished
[INFO] Running ODM Georeferencing Cell
[WARNING] Georeferencing failed. Make sure your photos have geotags in the EXIF or you have provided a GCP file.
[INFO] Running ODM Georeferencing Cell - Finished
[INFO] Running ODM DEM Cell
[INFO] Classify: True
[INFO] Create DSM: True
[INFO] Create DTM: True
[INFO] DEM input file /code/odm_georeferencing/odm_georeferenced_model.las found: False
[WARNING] DEM will not be generated
[INFO] Running ODM DEM Cell - Finished
[INFO] Running ODM Orthophoto Cell
[DEBUG] running /code/build/bin/odm_orthophoto -inputFile /code/odm_texturing/odm_textured_model.obj -logFile /code/odm_orthophoto/odm_orthophoto_log.txt -outputFile /code/odm_orthophoto/odm_orthophoto.png -resolution 10.0 -outputCornerFile /code/odm_orthophoto/odm_orthophoto_corners.txt
[WARNING] No geo-referenced orthophoto created due to missing geo-referencing or corner coordinates.
[INFO] Running ODM OrthoPhoto Cell - Finished
[INFO] OpenDroneMap app finished - Sat Dec 29 22:12:22 2018
</syntaxhighlight>

=== Running docker OpenDroneMap ===

==== Update to last OpenDroneMap docker image ====

<syntaxhighlight lang="bash">
docker pull opendronemap/opendronemap
</syntaxhighlight>

==== OpenDroneMap docker image ====

# Install docker
# Add you user to docker group
# sudo -H pip install requests

<syntaxhighlight lang="bash">
mkdir OpenDroneMap
cd OpenDroneMap
git clone git@github.com:OpenDroneMap/odm_data_aukerman.git
cd odm_data_aukerman

export odmi=`pwd`
ls -l $odmi

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd /home/jgr/Documentos/sletten16maj2018-gcp
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
opendronemap/opendronemap --gcp gcp_list.txt --dtm --dsm
</syntaxhighlight>

Sem GCP:

<syntaxhighlight lang="bash">
cd ~/Documentos/costanovadoprado/
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm --orthophoto-resolution 10.0
</syntaxhighlight>

Nota: os ortos estão a ficar com muitas interferências do modelo 3D, nas áreas urbanas.

Related problem: http://community.opendronemap.org/t/buildings/929

Será que voar com a câmara a 75 graus ajuda? Fiz um voo com Double Grid, com a camara a 70 graus (default do Pix4d capture).

==== Mac ====

1. Install Docker

2. <syntaxhighlight lang="bash">
docker run -it --rm -v $(pwd)/images:/code/images -v $(pwd)/odm_orthophoto:/code/odm_orthophoto -v $(pwd)/odm_texturing:/code/odm_texturing -v $(pwd)/odm_georeferencing:/code/odm_georeferencing -v $(pwd)/odm_meshing:/code/odm_meshing -v $(pwd)/opensfm:/code/opensfm -v $(pwd)/odm_dem:/code/odm_dem opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

With GCP

<syntaxhighlight lang="bash">
docker run -it --rm -v $(pwd)/images:/code/images -v $(pwd)/odm_orthophoto:/code/odm_orthophoto -v $(pwd)/odm_texturing:/code/odm_texturing -v $(pwd)/odm_georeferencing:/code/odm_georeferencing -v $(pwd)/odm_meshing:/code/odm_meshing -v $(pwd)/opensfm:/code/opensfm -v $(pwd)/odm_dem:/code/odm_dem -v $(pwd)/gcp_list.txt:/code/gcp_list.txt opendronemap/opendronemap --dtm --dsm --gcp gcp_list.txt
</syntaxhighlight>

==== Windows ====

Install Docker

Configure docker (more CPU, more memory)

CPUs: 6

Memory: 12032 Mb

Swap: 4096 Mb

Create the projet folder structure

Project folder:
c:\Users\dlt265\Documents\uav_sckovskolen_feb20018_incl_GCP\

Image folder:
c:\Users\dlt265\Documents\uav_sckovskolen_feb20018_incl_GCP\images

Create folders for the OpenDroneMap output.

<syntaxhighlight lang="bash">
cd Documents\uav_sckovskolen_feb20018_incl_GCP
md odm_orthophoto
md odm_texturing
md odm_georeferencing
md odm_meshing
md opensfm
md odm_dem
</syntaxhighlight>

<syntaxhighlight lang="bash">
docker run -it --rm -v $pwd/images:/code/images -v $pwd/odm_orthophoto:/code/odm_orthophoto -v $pwd/odm_texturing:/code/odm_texturing -v $pwd/odm_georeferencing:/code/odm_georeferencing -v $pwd/odm_meshing:/code/odm_meshing -v $pwd/opensfm:/code/opensfm -v $pwd/odm_dem:/code/odm_dem opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd ~/Documentos/costanovadoprado2xgrid
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm --orthophoto-resolution 10.0 --mesh-octree-depth 10
</syntaxhighlight>

=== OpenSFM viewer (update) ===

<syntaxhighlight lang="bash">
sudo chown -R jgr:jgr *
git clone https://github.com/mapillary/OpenSfM.git
cd OpenSfM/viewer
ln -s ../../images .
python2 -m SimpleHTTPServer 7777
</syntaxhighlight>

=== OpenSFM viewer ===

<syntaxhighlight lang="bash">
jgr@zoe:~/Documentos/costanovadoprado$ sudo chown -R jgr:jgr *
jgr@zoe:~/Documentos/costanovadoprado$ cp -r ~/dev/OpenSfM/viewer opensfm
jgr@zoe:~/Documentos/costanovadoprado$ cd opensfm/
jgr@zoe:~/Documentos/costanovadoprado/opensfm$ ln -s ../images .
jgr@zoe:~/Documentos/costanovadoprado/opensfm$ python -m SimpleHTTPServer
Serving HTTP on 0.0.0.0 port 8000 ...
</syntaxhighlight>

http://localhost:8000/viewer/reconstruction.html#file=/reconstruction.json

==== OpenSFM view images on QGIS ====

/home/jgr/Documentos/costanovadoprado/images/DJI_0595.JPG

-8.7515052, 40.6114774, 22.4100000, 2018:08:23 10:05:11

/home/jgr/Documentos/costanovadoprado/opensfm/reference_lla.json

Centro aproximado do ortophoto resultante (adicionado ao projeto QGIS)

<syntaxhighlight lang="json">
{
"latitude": 40.61272372901514,
"altitude": 0,
"longitude": -8.752983409509966
}
</syntaxhighlight>

<syntaxhighlight lang="json">
"DJI_0595.JPG": {
"orientation": 1,
"camera": "v2 dji fc220 4000 3000 perspective 0.7222",
"gps_position": [
125.10012061257521,
-138.4010433354888,
22.407269606366754
],
"gps_dop": 15.0,
"rotation": [
2.1445873611073996,
-2.2856282209697523,
0.20066193557381898
],
"translation": [
-132.67853610360638,
133.40968771622724,
1.9668907291333997
],
"capture_time": 1535018711.0
},
</syntaxhighlight>

https://github.com/mapillary/OpenSfM/blob/master/opensfm/commands/export_geocoords.py

jgr@zoe:~/Documentos/costanovadoprado/opensfm$ wget https://raw.githubusercontent.com/mapillary/OpenSfM/master/opensfm/commands/export_geocoords.py

NÃO FUNCIONOU...

export_geocoords.py -dataset costanova

Ver: https://github.com/mapillary/OpenSfM/issues/183

=== webODM ===

https://github.com/OpenDroneMap/WebODM

<syntaxhighlight lang="bash">
git clone https://github.com/OpenDroneMap/WebODM --config core.autocrlf=input
cd WebODM
./webodm.sh start
</syntaxhighlight>

jgrocha/xxbatata

=== Tools ===

CloudCompare

QGIS Plugin Photo2Shape

Criar uma shapefile photos

Nas propriedades, no campo <syntaxhighlight inline lang="bash">filepath</syntaxhighlight> mudar para o tipo Fotografia.

=== Ground Control File ===

<syntaxhighlight lang="bash">
echo -7.778152 41.833203 957.575989 | cs2cs +init=epsg:4326 +to +init=epsg:3763
echo 708610.702 6209972.025 26.085 | cs2cs +init=epsg:25832 +to +init=epsg:32633

jgr@zoe:~/Documentos/sletten16maj2018-exif$ gdalsrsinfo epsg:32633 -o proj4
'+proj=utm +zone=33 +datum=WGS84 +units=m +no_defs '
jgr@zoe:~/Documentos/sletten16maj2018-exif$ gdalsrsinfo epsg:25832 -o proj4
'+proj=utm +zone=32 +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs '
</syntaxhighlight>

== Make my own OpenDroneMap image ==

=== Fork and clone ODM repository ===

<syntaxhighlight lang="bash">
git clone git@github.com:jgrocha/OpenDroneMap.git
cd OpenDroneMap
git checkout -b generate-laz-output
</syntaxhighlight>

=== Change source ===

=== Build new image ===

<syntaxhighlight lang="bash">
jgr@zoe:~/PycharmProjects/OpenDroneMap$ docker build --no-cache -t odm_altitude_0 .
</syntaxhighlight>

<syntaxhighlight lang="bash">
docker build -t odm_laz_image .
</syntaxhighlight>

=== Run new image ===

<syntaxhighlight lang="bash">
# cd "/mnt/bonn/nextCloud/Photos/DJI MAVIC PRO 2 Paradela/100MEDIA"
cd /mnt/bonn/nextCloud/Photos
ln -s 'DJI MAVIC PRO 2 Paradela/100MEDIA' images
export odmi=`pwd`
docker run --cpus 8 -it --rm -v $odmi/images:/code/images -v $odmi/odm_orthophoto:/code/odm_orthophoto -v $odmi/odm_texturing:/code/odm_texturing -v $odmi/odm_georeferencing:/code/odm_georeferencing -v $odmi/odm_meshing:/code/odm_meshing -v $odmi/opensfm:/code/opensfm -v $odmi/odm_dem:/code/odm_dem odm_altitude_0 --dtm --dsm --force-ccd 13.2
# --orthophoto-resolution 2.0 --mesh-octree-depth 2 --opensfm-processes 8
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd /home/jgr/Documentos/sletten16maj2018-gcp
export odmi=`pwd`
sudo rm -rf odm_georeferencing odm_meshing odm_orthophoto odm_texturing opensfm
docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
odm_laz_image --gcp gcp_list.txt --dtm --dsm
</syntaxhighlight>

The options for rerunning are: 'resize', 'opensfm', 'slam', 'cmvs', 'pmvs', 'odm_meshing', 'mvs_texturing', 'odm_georeferencing', 'odm_orthophoto'

<syntaxhighlight lang="bash">
docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
odm_laz_image --gcp gcp_list.txt --dtm --dsm --rerun-from odm_georeferencing
</syntaxhighlight>

=== Check the output ===

<syntaxhighlight lang="text">
running /code/build/bin/odm_georef -bundleFile /code/opensfm/bundle_r000.out -imagesPath /code/images -imagesListPath /code/opensfm/list_r000.out -inputFile /code/odm_texturing/odm_textured_model.obj -outputFile /code/odm_texturing/odm_textured_model_geo.obj -inputPointCloudFile /code/opensfm/depthmaps/merged.ply -outputPointCloudFile /code/odm_georeferencing/odm_georeferenced_model.ply -logFile /code/odm_georeferencing/odm_georeferencing_log.txt -outputTransformFile /code/odm_georeferencing/odm_georeferencing_transform.txt -georefFileOutputPath /code/odm_georeferencing/odm_georeferencing_model_geo.txt -gcpFile gcp_list.txt -outputCoordFile /code/odm_georeferencing/coords.txt
[DEBUG] running /code/SuperBuild/build/pdal/bin/pdal pipeline -i /code/odm_georeferencing/las.json --readers.ply.filename=/code/odm_georeferencing/odm_georeferenced_model.ply
PDAL: writers.las: Can't write LAZ output. PDAL not built with LASzip or LAZperf.
</syntaxhighlight>

<syntaxhighlight lang="json">
{
"pipeline": [
"untransformed.ply",
{
"type": "writers.las",
"a_srs": "+proj=utm +zone=33 +datum=WGS84 +units=m +no_defs ",
"offset_x": "334230.28164",
"offset_y": "6208095.41529",
"offset_z": "0",
"compression": "laszip",
"filename": "/code/odm_georeferencing/odm_georeferenced_model.laz"
}
]
}
</syntaxhighlight>

[[File:Captura de ecrã de 2018-06-17 14-34-10.png]]

=== Local pdal+LASzip ===

Build from source!

<syntaxhighlight lang="bash">
/usr/local/bin/pdal pipeline -i las.json --readers.ply.filename=odm_georeferenced_model.ply
-rw-r--r-- 1 jgr jgr 22661583 jun 17 11:47 odm_georeferenced_model.laz
-rw-r--r-- 1 jgr jgr 121586206 jun 17 11:42 odm_georeferenced_model.ply
</syntaxhighlight>

==== Previous result ====

[[File:Captura de ecrã de 2018-06-16 12-26-36.png]]

==== New result ====

=== Create Pull Request ===

close #845

=== Other fixes ===

epsg versus EPSG

== Point cloud classification ==

[DEBUG] running pdal info --boundary --filters.hexbin.edge_length=1 --filters.hexbin.threshold=0 /code/odm_georeferencing/odm_georeferenced_model.filtered.las > /code/odm_georeferencing/odm_georeferenced_model.boundary.json
PDAL: Argument references invalid/unused stage: 'filters.hexbin'.

Running OpenDroneMap

2019-02-28T02:37:08Z

Jgrocha: /* Mac */

=== Drone Workshop ===

[[Drone workshop print screens]]

1. Flight

WebODM

<syntaxhighlight lang="bash">
pip install docker-compose
</syntaxhighlight>

10:54

2. Data products

2.1 Orthophoto

Discussion: GCP, impact on the elevation model

Swipe tool

Point value: check ortho values

2.2 DEM/DSM

Discussion: difference between

Raster value

Profile tool

Visualization: hillshade

http://plas.io/

https://pdal.io/tutorial/pcl_ground/index.html#pcl-ground

<syntaxhighlight lang="bash">
-- original
pdal translate -i /code/odm_georeferencing/odm_georeferenced_model.laz -o /code/odm_georeferencing/odm_georeferenced_model.laz smrf --filters.smrf.cell=2 --filters.smrf.slope=10 --filters.smrf.window=10

-- VERY GOOD
pdal translate -i odm_georeferencing/odm_georeferenced_model.ply -o odm_georeferencing/odm_georeferenced_model_2.laz smrf --filters.smrf.cell=2 --filters.smrf.window=10

-- good
pdal ground -i odm_georeferencing/odm_georeferenced_model.ply -o odm_georeferencing/odm_georeferenced_model_3.laz
</syntaxhighlight>

2.3 Point cloud

What we get from the software

Visualization tools

https://pdal.io/workshop/exercises/analysis/dtm/dtm.html

3. Processing data products

3.1 Better classification

lasground

3.2 lasheight

3.3 lasclassify

=== DJI Mavic 2 PRO ===

[https://forum.dji.com/thread-167017-1-1.html Sensor size], [https://www.youtube.com/watch?v=xIncVCe6pg0 Video about sensor size]

==== Erro ====

Culpado: <syntaxhighlight lang="bash" inline>/home/jgr/PycharmProjects/OpenDroneMap/modules/odm_extract_utm</syntaxhighlight>

Todas as imagens estão com Exif.GPSInfo.GPSAltitude = 0.0

<syntaxhighlight lang="bash">
if (lon == 0.0 || lat == 0.0 || alt == 0.0) {
std::string error("Failed parsing GPS position for " + imageFilename);
throw UtmExtractorException(error);
}
</syntaxhighlight>

==== Remendo ====

<syntaxhighlight lang="bash">
exiv2 -pa DJI_0210.JPG
Exif.GPSInfo.GPSAltitude Rational 1 0.0 m

exiv2 -M"set Exif.GPSInfo.GPSAltitude Rational 1/10" DJI_0210.JPG
exiv2 -pa DJI_0210.JPG
Exif.GPSInfo.GPSAltitude Rational 1 0.1 m
</syntaxhighlight>

Chamada:

<syntaxhighlight lang="bash">
[INFO] Wrote images database: /code/images.json
[INFO] Found 106 usable images
[DEBUG] running /code/build/bin/odm_extract_utm -imagesPath /code/images/ -imageListFile /code/img_list.txt -outputCoordFile /code/odm_georeferencing/coords.txt -logFile /code/odm_georeferencing/odm_georeferencing_utm_log.txt
Error in OdmExtractUtm:
Failed parsing GPS position for DJI_0301.JPG
For more detailed information, see log file.
</syntaxhighlight>

<syntaxhighlight lang="text">
[INFO] Found 106 usable images
[WARNING] Could not generate coordinates file. Ignore if there is a GCP file. Error: Error in OdmExtractUtm:
Failed parsing GPS position for DJI_0301.JPG
For more detailed information, see log file.

(...)

Building objmodel:
Saving model... done.
Whole texturing procedure took: 225.586s
[INFO] Running ODM Texturing Cell - Finished
[INFO] Running ODM Georeferencing Cell
[WARNING] Georeferencing failed. Make sure your photos have geotags in the EXIF or you have provided a GCP file.
[INFO] Running ODM Georeferencing Cell - Finished
[INFO] Running ODM DEM Cell
[INFO] Classify: True
[INFO] Create DSM: True
[INFO] Create DTM: True
[INFO] DEM input file /code/odm_georeferencing/odm_georeferenced_model.las found: False
[WARNING] DEM will not be generated
[INFO] Running ODM DEM Cell - Finished
[INFO] Running ODM Orthophoto Cell
[DEBUG] running /code/build/bin/odm_orthophoto -inputFile /code/odm_texturing/odm_textured_model.obj -logFile /code/odm_orthophoto/odm_orthophoto_log.txt -outputFile /code/odm_orthophoto/odm_orthophoto.png -resolution 10.0 -outputCornerFile /code/odm_orthophoto/odm_orthophoto_corners.txt
[WARNING] No geo-referenced orthophoto created due to missing geo-referencing or corner coordinates.
[INFO] Running ODM OrthoPhoto Cell - Finished
[INFO] OpenDroneMap app finished - Sat Dec 29 22:12:22 2018
</syntaxhighlight>

=== Running docker OpenDroneMap ===

==== Update to last OpenDroneMap docker image ====

<syntaxhighlight lang="bash">
docker pull opendronemap/opendronemap
</syntaxhighlight>

==== OpenDroneMap docker image ====

# Install docker
# Add you user to docker group
# sudo -H pip install requests

<syntaxhighlight lang="bash">
mkdir OpenDroneMap
cd OpenDroneMap
git clone git@github.com:OpenDroneMap/odm_data_aukerman.git
cd odm_data_aukerman

export odmi=`pwd`
ls -l $odmi

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd /home/jgr/Documentos/sletten16maj2018-gcp
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
opendronemap/opendronemap --gcp gcp_list.txt --dtm --dsm
</syntaxhighlight>

Sem GCP:

<syntaxhighlight lang="bash">
cd ~/Documentos/costanovadoprado/
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm --orthophoto-resolution 10.0
</syntaxhighlight>

Nota: os ortos estão a ficar com muitas interferências do modelo 3D, nas áreas urbanas.

Related problem: http://community.opendronemap.org/t/buildings/929

Será que voar com a câmara a 75 graus ajuda? Fiz um voo com Double Grid, com a camara a 70 graus (default do Pix4d capture).

==== Mac ====

1. Install Docker

2. <syntaxhighlight lang="bash">
docker run -it --rm -v $(pwd)/images:/code/images -v $(pwd)/odm_orthophoto:/code/odm_orthophoto -v $(pwd)/odm_texturing:/code/odm_texturing -v $(pwd)/odm_georeferencing:/code/odm_georeferencing -v $(pwd)/odm_meshing:/code/odm_meshing -v $(pwd)/opensfm:/code/opensfm -v $(pwd)/odm_dem:/code/odm_dem opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

<syntaxhighlight lang="bash">
docker run -it --rm -v $(pwd)/images:/code/images -v $(pwd)/odm_orthophoto:/code/odm_orthophoto -v $(pwd)/odm_texturing:/code/odm_texturing -v $(pwd)/odm_georeferencing:/code/odm_georeferencing -v $(pwd)/odm_meshing:/code/odm_meshing -v $(pwd)/opensfm:/code/opensfm -v $(pwd)/odm_dem:/code/odm_dem opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

==== Windows ====

Install Docker

Configure docker (more CPU, more memory)

CPUs: 6

Memory: 12032 Mb

Swap: 4096 Mb

Create the projet folder structure

Project folder:
c:\Users\dlt265\Documents\uav_sckovskolen_feb20018_incl_GCP\

Image folder:
c:\Users\dlt265\Documents\uav_sckovskolen_feb20018_incl_GCP\images

Create folders for the OpenDroneMap output.

<syntaxhighlight lang="bash">
cd Documents\uav_sckovskolen_feb20018_incl_GCP
md odm_orthophoto
md odm_texturing
md odm_georeferencing
md odm_meshing
md opensfm
md odm_dem
</syntaxhighlight>

<syntaxhighlight lang="bash">
docker run -it --rm -v $pwd/images:/code/images -v $pwd/odm_orthophoto:/code/odm_orthophoto -v $pwd/odm_texturing:/code/odm_texturing -v $pwd/odm_georeferencing:/code/odm_georeferencing -v $pwd/odm_meshing:/code/odm_meshing -v $pwd/opensfm:/code/opensfm -v $pwd/odm_dem:/code/odm_dem opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd ~/Documentos/costanovadoprado2xgrid
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm --orthophoto-resolution 10.0 --mesh-octree-depth 10
</syntaxhighlight>

=== OpenSFM viewer (update) ===

<syntaxhighlight lang="bash">
sudo chown -R jgr:jgr *
git clone https://github.com/mapillary/OpenSfM.git
cd OpenSfM/viewer
ln -s ../../images .
python2 -m SimpleHTTPServer 7777
</syntaxhighlight>

=== OpenSFM viewer ===

<syntaxhighlight lang="bash">
jgr@zoe:~/Documentos/costanovadoprado$ sudo chown -R jgr:jgr *
jgr@zoe:~/Documentos/costanovadoprado$ cp -r ~/dev/OpenSfM/viewer opensfm
jgr@zoe:~/Documentos/costanovadoprado$ cd opensfm/
jgr@zoe:~/Documentos/costanovadoprado/opensfm$ ln -s ../images .
jgr@zoe:~/Documentos/costanovadoprado/opensfm$ python -m SimpleHTTPServer
Serving HTTP on 0.0.0.0 port 8000 ...
</syntaxhighlight>

http://localhost:8000/viewer/reconstruction.html#file=/reconstruction.json

==== OpenSFM view images on QGIS ====

/home/jgr/Documentos/costanovadoprado/images/DJI_0595.JPG

-8.7515052, 40.6114774, 22.4100000, 2018:08:23 10:05:11

/home/jgr/Documentos/costanovadoprado/opensfm/reference_lla.json

Centro aproximado do ortophoto resultante (adicionado ao projeto QGIS)

<syntaxhighlight lang="json">
{
"latitude": 40.61272372901514,
"altitude": 0,
"longitude": -8.752983409509966
}
</syntaxhighlight>

<syntaxhighlight lang="json">
"DJI_0595.JPG": {
"orientation": 1,
"camera": "v2 dji fc220 4000 3000 perspective 0.7222",
"gps_position": [
125.10012061257521,
-138.4010433354888,
22.407269606366754
],
"gps_dop": 15.0,
"rotation": [
2.1445873611073996,
-2.2856282209697523,
0.20066193557381898
],
"translation": [
-132.67853610360638,
133.40968771622724,
1.9668907291333997
],
"capture_time": 1535018711.0
},
</syntaxhighlight>

https://github.com/mapillary/OpenSfM/blob/master/opensfm/commands/export_geocoords.py

jgr@zoe:~/Documentos/costanovadoprado/opensfm$ wget https://raw.githubusercontent.com/mapillary/OpenSfM/master/opensfm/commands/export_geocoords.py

NÃO FUNCIONOU...

export_geocoords.py -dataset costanova

Ver: https://github.com/mapillary/OpenSfM/issues/183

=== webODM ===

https://github.com/OpenDroneMap/WebODM

<syntaxhighlight lang="bash">
git clone https://github.com/OpenDroneMap/WebODM --config core.autocrlf=input
cd WebODM
./webodm.sh start
</syntaxhighlight>

jgrocha/xxbatata

=== Tools ===

CloudCompare

QGIS Plugin Photo2Shape

Criar uma shapefile photos

Nas propriedades, no campo <syntaxhighlight inline lang="bash">filepath</syntaxhighlight> mudar para o tipo Fotografia.

=== Ground Control File ===

<syntaxhighlight lang="bash">
echo -7.778152 41.833203 957.575989 | cs2cs +init=epsg:4326 +to +init=epsg:3763
echo 708610.702 6209972.025 26.085 | cs2cs +init=epsg:25832 +to +init=epsg:32633

jgr@zoe:~/Documentos/sletten16maj2018-exif$ gdalsrsinfo epsg:32633 -o proj4
'+proj=utm +zone=33 +datum=WGS84 +units=m +no_defs '
jgr@zoe:~/Documentos/sletten16maj2018-exif$ gdalsrsinfo epsg:25832 -o proj4
'+proj=utm +zone=32 +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs '
</syntaxhighlight>

== Make my own OpenDroneMap image ==

=== Fork and clone ODM repository ===

<syntaxhighlight lang="bash">
git clone git@github.com:jgrocha/OpenDroneMap.git
cd OpenDroneMap
git checkout -b generate-laz-output
</syntaxhighlight>

=== Change source ===

=== Build new image ===

<syntaxhighlight lang="bash">
jgr@zoe:~/PycharmProjects/OpenDroneMap$ docker build --no-cache -t odm_altitude_0 .
</syntaxhighlight>

<syntaxhighlight lang="bash">
docker build -t odm_laz_image .
</syntaxhighlight>

=== Run new image ===

<syntaxhighlight lang="bash">
# cd "/mnt/bonn/nextCloud/Photos/DJI MAVIC PRO 2 Paradela/100MEDIA"
cd /mnt/bonn/nextCloud/Photos
ln -s 'DJI MAVIC PRO 2 Paradela/100MEDIA' images
export odmi=`pwd`
docker run --cpus 8 -it --rm -v $odmi/images:/code/images -v $odmi/odm_orthophoto:/code/odm_orthophoto -v $odmi/odm_texturing:/code/odm_texturing -v $odmi/odm_georeferencing:/code/odm_georeferencing -v $odmi/odm_meshing:/code/odm_meshing -v $odmi/opensfm:/code/opensfm -v $odmi/odm_dem:/code/odm_dem odm_altitude_0 --dtm --dsm --force-ccd 13.2
# --orthophoto-resolution 2.0 --mesh-octree-depth 2 --opensfm-processes 8
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd /home/jgr/Documentos/sletten16maj2018-gcp
export odmi=`pwd`
sudo rm -rf odm_georeferencing odm_meshing odm_orthophoto odm_texturing opensfm
docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
odm_laz_image --gcp gcp_list.txt --dtm --dsm
</syntaxhighlight>

The options for rerunning are: 'resize', 'opensfm', 'slam', 'cmvs', 'pmvs', 'odm_meshing', 'mvs_texturing', 'odm_georeferencing', 'odm_orthophoto'

<syntaxhighlight lang="bash">
docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
odm_laz_image --gcp gcp_list.txt --dtm --dsm --rerun-from odm_georeferencing
</syntaxhighlight>

=== Check the output ===

<syntaxhighlight lang="text">
running /code/build/bin/odm_georef -bundleFile /code/opensfm/bundle_r000.out -imagesPath /code/images -imagesListPath /code/opensfm/list_r000.out -inputFile /code/odm_texturing/odm_textured_model.obj -outputFile /code/odm_texturing/odm_textured_model_geo.obj -inputPointCloudFile /code/opensfm/depthmaps/merged.ply -outputPointCloudFile /code/odm_georeferencing/odm_georeferenced_model.ply -logFile /code/odm_georeferencing/odm_georeferencing_log.txt -outputTransformFile /code/odm_georeferencing/odm_georeferencing_transform.txt -georefFileOutputPath /code/odm_georeferencing/odm_georeferencing_model_geo.txt -gcpFile gcp_list.txt -outputCoordFile /code/odm_georeferencing/coords.txt
[DEBUG] running /code/SuperBuild/build/pdal/bin/pdal pipeline -i /code/odm_georeferencing/las.json --readers.ply.filename=/code/odm_georeferencing/odm_georeferenced_model.ply
PDAL: writers.las: Can't write LAZ output. PDAL not built with LASzip or LAZperf.
</syntaxhighlight>

<syntaxhighlight lang="json">
{
"pipeline": [
"untransformed.ply",
{
"type": "writers.las",
"a_srs": "+proj=utm +zone=33 +datum=WGS84 +units=m +no_defs ",
"offset_x": "334230.28164",
"offset_y": "6208095.41529",
"offset_z": "0",
"compression": "laszip",
"filename": "/code/odm_georeferencing/odm_georeferenced_model.laz"
}
]
}
</syntaxhighlight>

[[File:Captura de ecrã de 2018-06-17 14-34-10.png]]

=== Local pdal+LASzip ===

Build from source!

<syntaxhighlight lang="bash">
/usr/local/bin/pdal pipeline -i las.json --readers.ply.filename=odm_georeferenced_model.ply
-rw-r--r-- 1 jgr jgr 22661583 jun 17 11:47 odm_georeferenced_model.laz
-rw-r--r-- 1 jgr jgr 121586206 jun 17 11:42 odm_georeferenced_model.ply
</syntaxhighlight>

==== Previous result ====

[[File:Captura de ecrã de 2018-06-16 12-26-36.png]]

==== New result ====

=== Create Pull Request ===

close #845

=== Other fixes ===

epsg versus EPSG

== Point cloud classification ==

[DEBUG] running pdal info --boundary --filters.hexbin.edge_length=1 --filters.hexbin.threshold=0 /code/odm_georeferencing/odm_georeferenced_model.filtered.las > /code/odm_georeferencing/odm_georeferenced_model.boundary.json
PDAL: Argument references invalid/unused stage: 'filters.hexbin'.

Drone workshop print screens

2019-02-27T00:03:53Z

Jgrocha: Created page with " File:Captura de ecrã de 2019-02-26 23-32-43.png"

[[File:Captura de ecrã de 2019-02-26 23-32-43.png]]

File:Captura de ecrã de 2019-02-26 23-32-43.png

2019-02-26T23:33:11Z

Jgrocha:

Running OpenDroneMap

2019-02-26T23:30:21Z

Jgrocha: /* Drone Workshop */

=== Drone Workshop ===

[[Drone workshop print screens]]

1. Flight

WebODM

<syntaxhighlight lang="bash">
pip install docker-compose
</syntaxhighlight>

10:54

2. Data products

2.1 Orthophoto

Discussion: GCP, impact on the elevation model

Swipe tool

Point value: check ortho values

2.2 DEM/DSM

Discussion: difference between

Raster value

Profile tool

Visualization: hillshade

http://plas.io/

https://pdal.io/tutorial/pcl_ground/index.html#pcl-ground

<syntaxhighlight lang="bash">
-- original
pdal translate -i /code/odm_georeferencing/odm_georeferenced_model.laz -o /code/odm_georeferencing/odm_georeferenced_model.laz smrf --filters.smrf.cell=2 --filters.smrf.slope=10 --filters.smrf.window=10

-- VERY GOOD
pdal translate -i odm_georeferencing/odm_georeferenced_model.ply -o odm_georeferencing/odm_georeferenced_model_2.laz smrf --filters.smrf.cell=2 --filters.smrf.window=10

-- good
pdal ground -i odm_georeferencing/odm_georeferenced_model.ply -o odm_georeferencing/odm_georeferenced_model_3.laz
</syntaxhighlight>

2.3 Point cloud

What we get from the software

Visualization tools

https://pdal.io/workshop/exercises/analysis/dtm/dtm.html

3. Processing data products

3.1 Better classification

lasground

3.2 lasheight

3.3 lasclassify

=== DJI Mavic 2 PRO ===

[https://forum.dji.com/thread-167017-1-1.html Sensor size], [https://www.youtube.com/watch?v=xIncVCe6pg0 Video about sensor size]

==== Erro ====

Culpado: <syntaxhighlight lang="bash" inline>/home/jgr/PycharmProjects/OpenDroneMap/modules/odm_extract_utm</syntaxhighlight>

Todas as imagens estão com Exif.GPSInfo.GPSAltitude = 0.0

<syntaxhighlight lang="bash">
if (lon == 0.0 || lat == 0.0 || alt == 0.0) {
std::string error("Failed parsing GPS position for " + imageFilename);
throw UtmExtractorException(error);
}
</syntaxhighlight>

==== Remendo ====

<syntaxhighlight lang="bash">
exiv2 -pa DJI_0210.JPG
Exif.GPSInfo.GPSAltitude Rational 1 0.0 m

exiv2 -M"set Exif.GPSInfo.GPSAltitude Rational 1/10" DJI_0210.JPG
exiv2 -pa DJI_0210.JPG
Exif.GPSInfo.GPSAltitude Rational 1 0.1 m
</syntaxhighlight>

Chamada:

<syntaxhighlight lang="bash">
[INFO] Wrote images database: /code/images.json
[INFO] Found 106 usable images
[DEBUG] running /code/build/bin/odm_extract_utm -imagesPath /code/images/ -imageListFile /code/img_list.txt -outputCoordFile /code/odm_georeferencing/coords.txt -logFile /code/odm_georeferencing/odm_georeferencing_utm_log.txt
Error in OdmExtractUtm:
Failed parsing GPS position for DJI_0301.JPG
For more detailed information, see log file.
</syntaxhighlight>

<syntaxhighlight lang="text">
[INFO] Found 106 usable images
[WARNING] Could not generate coordinates file. Ignore if there is a GCP file. Error: Error in OdmExtractUtm:
Failed parsing GPS position for DJI_0301.JPG
For more detailed information, see log file.

(...)

Building objmodel:
Saving model... done.
Whole texturing procedure took: 225.586s
[INFO] Running ODM Texturing Cell - Finished
[INFO] Running ODM Georeferencing Cell
[WARNING] Georeferencing failed. Make sure your photos have geotags in the EXIF or you have provided a GCP file.
[INFO] Running ODM Georeferencing Cell - Finished
[INFO] Running ODM DEM Cell
[INFO] Classify: True
[INFO] Create DSM: True
[INFO] Create DTM: True
[INFO] DEM input file /code/odm_georeferencing/odm_georeferenced_model.las found: False
[WARNING] DEM will not be generated
[INFO] Running ODM DEM Cell - Finished
[INFO] Running ODM Orthophoto Cell
[DEBUG] running /code/build/bin/odm_orthophoto -inputFile /code/odm_texturing/odm_textured_model.obj -logFile /code/odm_orthophoto/odm_orthophoto_log.txt -outputFile /code/odm_orthophoto/odm_orthophoto.png -resolution 10.0 -outputCornerFile /code/odm_orthophoto/odm_orthophoto_corners.txt
[WARNING] No geo-referenced orthophoto created due to missing geo-referencing or corner coordinates.
[INFO] Running ODM OrthoPhoto Cell - Finished
[INFO] OpenDroneMap app finished - Sat Dec 29 22:12:22 2018
</syntaxhighlight>

=== Running docker OpenDroneMap ===

==== Update to last OpenDroneMap docker image ====

<syntaxhighlight lang="bash">
docker pull opendronemap/opendronemap
</syntaxhighlight>

==== OpenDroneMap docker image ====

# Install docker
# Add you user to docker group
# sudo -H pip install requests

<syntaxhighlight lang="bash">
mkdir OpenDroneMap
cd OpenDroneMap
git clone git@github.com:OpenDroneMap/odm_data_aukerman.git
cd odm_data_aukerman

export odmi=`pwd`
ls -l $odmi

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd /home/jgr/Documentos/sletten16maj2018-gcp
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
opendronemap/opendronemap --gcp gcp_list.txt --dtm --dsm
</syntaxhighlight>

Sem GCP:

<syntaxhighlight lang="bash">
cd ~/Documentos/costanovadoprado/
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm --orthophoto-resolution 10.0
</syntaxhighlight>

Nota: os ortos estão a ficar com muitas interferências do modelo 3D, nas áreas urbanas.

Related problem: http://community.opendronemap.org/t/buildings/929

Será que voar com a câmara a 75 graus ajuda? Fiz um voo com Double Grid, com a camara a 70 graus (default do Pix4d capture).

==== Mac ====

1. Install Docker

2. <syntaxhighlight lang="bash">
docker run -it --rm -v $(pwd)/images:/code/images -v $(pwd)/odm_orthophoto:/code/odm_orthophoto -v $(pwd)/odm_texturing:/code/odm_texturing -v $(pwd)/odm_georeferencing:/code/odm_georeferencing -v $(pwd)/odm_meshing:/code/odm_meshing -v $(pwd)/opensfm:/code/opensfm -v $(pwd)/odm_dem:/code/odm_dem opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

==== Windows ====

Install Docker

Configure docker (more CPU, more memory)

CPUs: 6

Memory: 12032 Mb

Swap: 4096 Mb

Create the projet folder structure

Project folder:
c:\Users\dlt265\Documents\uav_sckovskolen_feb20018_incl_GCP\

Image folder:
c:\Users\dlt265\Documents\uav_sckovskolen_feb20018_incl_GCP\images

Create folders for the OpenDroneMap output.

<syntaxhighlight lang="bash">
cd Documents\uav_sckovskolen_feb20018_incl_GCP
md odm_orthophoto
md odm_texturing
md odm_georeferencing
md odm_meshing
md opensfm
md odm_dem
</syntaxhighlight>

<syntaxhighlight lang="bash">
docker run -it --rm -v $pwd/images:/code/images -v $pwd/odm_orthophoto:/code/odm_orthophoto -v $pwd/odm_texturing:/code/odm_texturing -v $pwd/odm_georeferencing:/code/odm_georeferencing -v $pwd/odm_meshing:/code/odm_meshing -v $pwd/opensfm:/code/opensfm -v $pwd/odm_dem:/code/odm_dem opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd ~/Documentos/costanovadoprado2xgrid
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm --orthophoto-resolution 10.0 --mesh-octree-depth 10
</syntaxhighlight>

=== OpenSFM viewer (update) ===

<syntaxhighlight lang="bash">
sudo chown -R jgr:jgr *
git clone https://github.com/mapillary/OpenSfM.git
cd OpenSfM/viewer
ln -s ../../images .
python2 -m SimpleHTTPServer 7777
</syntaxhighlight>

=== OpenSFM viewer ===

<syntaxhighlight lang="bash">
jgr@zoe:~/Documentos/costanovadoprado$ sudo chown -R jgr:jgr *
jgr@zoe:~/Documentos/costanovadoprado$ cp -r ~/dev/OpenSfM/viewer opensfm
jgr@zoe:~/Documentos/costanovadoprado$ cd opensfm/
jgr@zoe:~/Documentos/costanovadoprado/opensfm$ ln -s ../images .
jgr@zoe:~/Documentos/costanovadoprado/opensfm$ python -m SimpleHTTPServer
Serving HTTP on 0.0.0.0 port 8000 ...
</syntaxhighlight>

http://localhost:8000/viewer/reconstruction.html#file=/reconstruction.json

==== OpenSFM view images on QGIS ====

/home/jgr/Documentos/costanovadoprado/images/DJI_0595.JPG

-8.7515052, 40.6114774, 22.4100000, 2018:08:23 10:05:11

/home/jgr/Documentos/costanovadoprado/opensfm/reference_lla.json

Centro aproximado do ortophoto resultante (adicionado ao projeto QGIS)

<syntaxhighlight lang="json">
{
"latitude": 40.61272372901514,
"altitude": 0,
"longitude": -8.752983409509966
}
</syntaxhighlight>

<syntaxhighlight lang="json">
"DJI_0595.JPG": {
"orientation": 1,
"camera": "v2 dji fc220 4000 3000 perspective 0.7222",
"gps_position": [
125.10012061257521,
-138.4010433354888,
22.407269606366754
],
"gps_dop": 15.0,
"rotation": [
2.1445873611073996,
-2.2856282209697523,
0.20066193557381898
],
"translation": [
-132.67853610360638,
133.40968771622724,
1.9668907291333997
],
"capture_time": 1535018711.0
},
</syntaxhighlight>

https://github.com/mapillary/OpenSfM/blob/master/opensfm/commands/export_geocoords.py

jgr@zoe:~/Documentos/costanovadoprado/opensfm$ wget https://raw.githubusercontent.com/mapillary/OpenSfM/master/opensfm/commands/export_geocoords.py

NÃO FUNCIONOU...

export_geocoords.py -dataset costanova

Ver: https://github.com/mapillary/OpenSfM/issues/183

=== webODM ===

https://github.com/OpenDroneMap/WebODM

<syntaxhighlight lang="bash">
git clone https://github.com/OpenDroneMap/WebODM --config core.autocrlf=input
cd WebODM
./webodm.sh start
</syntaxhighlight>

jgrocha/xxbatata

=== Tools ===

CloudCompare

QGIS Plugin Photo2Shape

Criar uma shapefile photos

Nas propriedades, no campo <syntaxhighlight inline lang="bash">filepath</syntaxhighlight> mudar para o tipo Fotografia.

=== Ground Control File ===

<syntaxhighlight lang="bash">
echo -7.778152 41.833203 957.575989 | cs2cs +init=epsg:4326 +to +init=epsg:3763
echo 708610.702 6209972.025 26.085 | cs2cs +init=epsg:25832 +to +init=epsg:32633

jgr@zoe:~/Documentos/sletten16maj2018-exif$ gdalsrsinfo epsg:32633 -o proj4
'+proj=utm +zone=33 +datum=WGS84 +units=m +no_defs '
jgr@zoe:~/Documentos/sletten16maj2018-exif$ gdalsrsinfo epsg:25832 -o proj4
'+proj=utm +zone=32 +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs '
</syntaxhighlight>

== Make my own OpenDroneMap image ==

=== Fork and clone ODM repository ===

<syntaxhighlight lang="bash">
git clone git@github.com:jgrocha/OpenDroneMap.git
cd OpenDroneMap
git checkout -b generate-laz-output
</syntaxhighlight>

=== Change source ===

=== Build new image ===

<syntaxhighlight lang="bash">
jgr@zoe:~/PycharmProjects/OpenDroneMap$ docker build --no-cache -t odm_altitude_0 .
</syntaxhighlight>

<syntaxhighlight lang="bash">
docker build -t odm_laz_image .
</syntaxhighlight>

=== Run new image ===

<syntaxhighlight lang="bash">
# cd "/mnt/bonn/nextCloud/Photos/DJI MAVIC PRO 2 Paradela/100MEDIA"
cd /mnt/bonn/nextCloud/Photos
ln -s 'DJI MAVIC PRO 2 Paradela/100MEDIA' images
export odmi=`pwd`
docker run --cpus 8 -it --rm -v $odmi/images:/code/images -v $odmi/odm_orthophoto:/code/odm_orthophoto -v $odmi/odm_texturing:/code/odm_texturing -v $odmi/odm_georeferencing:/code/odm_georeferencing -v $odmi/odm_meshing:/code/odm_meshing -v $odmi/opensfm:/code/opensfm -v $odmi/odm_dem:/code/odm_dem odm_altitude_0 --dtm --dsm --force-ccd 13.2
# --orthophoto-resolution 2.0 --mesh-octree-depth 2 --opensfm-processes 8
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd /home/jgr/Documentos/sletten16maj2018-gcp
export odmi=`pwd`
sudo rm -rf odm_georeferencing odm_meshing odm_orthophoto odm_texturing opensfm
docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
odm_laz_image --gcp gcp_list.txt --dtm --dsm
</syntaxhighlight>

The options for rerunning are: 'resize', 'opensfm', 'slam', 'cmvs', 'pmvs', 'odm_meshing', 'mvs_texturing', 'odm_georeferencing', 'odm_orthophoto'

<syntaxhighlight lang="bash">
docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
odm_laz_image --gcp gcp_list.txt --dtm --dsm --rerun-from odm_georeferencing
</syntaxhighlight>

=== Check the output ===

<syntaxhighlight lang="text">
running /code/build/bin/odm_georef -bundleFile /code/opensfm/bundle_r000.out -imagesPath /code/images -imagesListPath /code/opensfm/list_r000.out -inputFile /code/odm_texturing/odm_textured_model.obj -outputFile /code/odm_texturing/odm_textured_model_geo.obj -inputPointCloudFile /code/opensfm/depthmaps/merged.ply -outputPointCloudFile /code/odm_georeferencing/odm_georeferenced_model.ply -logFile /code/odm_georeferencing/odm_georeferencing_log.txt -outputTransformFile /code/odm_georeferencing/odm_georeferencing_transform.txt -georefFileOutputPath /code/odm_georeferencing/odm_georeferencing_model_geo.txt -gcpFile gcp_list.txt -outputCoordFile /code/odm_georeferencing/coords.txt
[DEBUG] running /code/SuperBuild/build/pdal/bin/pdal pipeline -i /code/odm_georeferencing/las.json --readers.ply.filename=/code/odm_georeferencing/odm_georeferenced_model.ply
PDAL: writers.las: Can't write LAZ output. PDAL not built with LASzip or LAZperf.
</syntaxhighlight>

<syntaxhighlight lang="json">
{
"pipeline": [
"untransformed.ply",
{
"type": "writers.las",
"a_srs": "+proj=utm +zone=33 +datum=WGS84 +units=m +no_defs ",
"offset_x": "334230.28164",
"offset_y": "6208095.41529",
"offset_z": "0",
"compression": "laszip",
"filename": "/code/odm_georeferencing/odm_georeferenced_model.laz"
}
]
}
</syntaxhighlight>

[[File:Captura de ecrã de 2018-06-17 14-34-10.png]]

=== Local pdal+LASzip ===

Build from source!

<syntaxhighlight lang="bash">
/usr/local/bin/pdal pipeline -i las.json --readers.ply.filename=odm_georeferenced_model.ply
-rw-r--r-- 1 jgr jgr 22661583 jun 17 11:47 odm_georeferenced_model.laz
-rw-r--r-- 1 jgr jgr 121586206 jun 17 11:42 odm_georeferenced_model.ply
</syntaxhighlight>

==== Previous result ====

[[File:Captura de ecrã de 2018-06-16 12-26-36.png]]

==== New result ====

=== Create Pull Request ===

close #845

=== Other fixes ===

epsg versus EPSG

== Point cloud classification ==

[DEBUG] running pdal info --boundary --filters.hexbin.edge_length=1 --filters.hexbin.threshold=0 /code/odm_georeferencing/odm_georeferenced_model.filtered.las > /code/odm_georeferencing/odm_georeferenced_model.boundary.json
PDAL: Argument references invalid/unused stage: 'filters.hexbin'.

Análise espacial com rasters

2019-02-10T19:04:23Z

Jgrocha:

Dados do exercício

Critérios:
* Magnitude dos tremores de terra (em função da magnitude; usar interpolação IDW)
** Reclassificar
* Densidade dos tremores de terra (em função da distância; usar interpolação Heatmap)
** Reclassificar
* Distância estradas/railways/built-up areas
** Buffers ?
** Interpolação por classes ???

Resultado final

Interpolação IDW

Reclassificação com base em 4 critérios

[[File:Captura de ecrã de 2019-02-10 11-15-12.png]]

[[File:Captura de ecrã de 2019-02-10 11-13-51.png]]

Heatmap

[[File:Captura de ecrã de 2019-02-10 18-32-30.png]]

Resultado

[[File:Heatmap.png]]

File:Heatmap.png

2019-02-10T18:35:55Z

Jgrocha:

File:Captura de ecrã de 2019-02-10 18-32-30.png

2019-02-10T18:34:31Z

Jgrocha:

Análise espacial com rasters

2019-02-10T17:35:20Z

Jgrocha:

Análise espacial com rasters

2019-02-10T17:35:04Z

Jgrocha:

Dados do exercício

Critérios:
* Magnitude dos tremores de terra (em função da magnitude; usar interpolação IDW)
** Reclassificar
* Densidade dos tremores de terra (em função da distância; usar interpolação Heatmap)
** Reclassificar
* Distância estradas/railways/built-up areas
** Buffers ?
** Interpolação por classes ???

Resultado final

Interpolação IDW

Reclassificação com base em 4 critérios

[[File:Captura de ecrã de 2019-02-10 11-15-12.png]]
[[File:Captura de ecrã de 2019-02-10 11-15-12.png]]

[[File:Captura de ecrã de 2019-02-10 11-13-51.png]]

Análise espacial com rasters

2019-02-10T11:36:33Z

Jgrocha:

File:Captura de ecrã de 2019-02-10 11-15-12.png

2019-02-10T11:22:03Z

Jgrocha: Jgrocha uploaded a new version of File:Captura de ecrã de 2019-02-10 11-15-12.png

File:Captura de ecrã de 2019-02-10 11-13-51.png

2019-02-10T11:16:55Z

Jgrocha:

File:Captura de ecrã de 2019-02-10 11-15-12.png

2019-02-10T11:16:30Z

Jgrocha:

Análise espacial com rasters

2019-02-10T11:15:45Z

Jgrocha:

Dados do

Interpolação IDW

Reclassificação com base em 4 critérios

[[File:Captura de ecrã de 2019-02-10 11-15-12.png]]

[[File:Captura de ecrã de 2019-02-10 11-13-51.png]]

Análise espacial com rasters

2019-02-10T11:13:20Z

Jgrocha: Created page with "Dados do Interpolação IDW Reclassificação com base em 4 critérios [[]] [[]]"

Dados do

Interpolação IDW

Reclassificação com base em 4 critérios

[[]]

[[]]

Main Page

2019-02-10T11:11:12Z

Jgrocha: /* SIG desktop com QGIS */

Running OpenDroneMap

2019-02-04T15:19:30Z

Jgrocha: /* Windows */

=== Drone Workshop ===

1. Flight

WebODM

<syntaxhighlight lang="bash">
pip install docker-compose
</syntaxhighlight>

10:54

2. Data products

2.1 Orthophoto

Discussion: GCP, impact on the elevation model

Swipe tool

Point value: check ortho values

2.2 DEM/DSM

Discussion: difference between

Raster value

Profile tool

Visualization: hillshade

http://plas.io/

https://pdal.io/tutorial/pcl_ground/index.html#pcl-ground

<syntaxhighlight lang="bash">
-- original
pdal translate -i /code/odm_georeferencing/odm_georeferenced_model.laz -o /code/odm_georeferencing/odm_georeferenced_model.laz smrf --filters.smrf.cell=2 --filters.smrf.slope=10 --filters.smrf.window=10

-- VERY GOOD
pdal translate -i odm_georeferencing/odm_georeferenced_model.ply -o odm_georeferencing/odm_georeferenced_model_2.laz smrf --filters.smrf.cell=2 --filters.smrf.window=10

-- good
pdal ground -i odm_georeferencing/odm_georeferenced_model.ply -o odm_georeferencing/odm_georeferenced_model_3.laz
</syntaxhighlight>

2.3 Point cloud

What we get from the software

Visualization tools

https://pdal.io/workshop/exercises/analysis/dtm/dtm.html

3. Processing data products

3.1 Better classification

lasground

3.2 lasheight

3.3 lasclassify

=== DJI Mavic 2 PRO ===

[https://forum.dji.com/thread-167017-1-1.html Sensor size], [https://www.youtube.com/watch?v=xIncVCe6pg0 Video about sensor size]

==== Erro ====

Culpado: <syntaxhighlight lang="bash" inline>/home/jgr/PycharmProjects/OpenDroneMap/modules/odm_extract_utm</syntaxhighlight>

Todas as imagens estão com Exif.GPSInfo.GPSAltitude = 0.0

<syntaxhighlight lang="bash">
if (lon == 0.0 || lat == 0.0 || alt == 0.0) {
std::string error("Failed parsing GPS position for " + imageFilename);
throw UtmExtractorException(error);
}
</syntaxhighlight>

==== Remendo ====

<syntaxhighlight lang="bash">
exiv2 -pa DJI_0210.JPG
Exif.GPSInfo.GPSAltitude Rational 1 0.0 m

exiv2 -M"set Exif.GPSInfo.GPSAltitude Rational 1/10" DJI_0210.JPG
exiv2 -pa DJI_0210.JPG
Exif.GPSInfo.GPSAltitude Rational 1 0.1 m
</syntaxhighlight>

Chamada:

<syntaxhighlight lang="bash">
[INFO] Wrote images database: /code/images.json
[INFO] Found 106 usable images
[DEBUG] running /code/build/bin/odm_extract_utm -imagesPath /code/images/ -imageListFile /code/img_list.txt -outputCoordFile /code/odm_georeferencing/coords.txt -logFile /code/odm_georeferencing/odm_georeferencing_utm_log.txt
Error in OdmExtractUtm:
Failed parsing GPS position for DJI_0301.JPG
For more detailed information, see log file.
</syntaxhighlight>

<syntaxhighlight lang="text">
[INFO] Found 106 usable images
[WARNING] Could not generate coordinates file. Ignore if there is a GCP file. Error: Error in OdmExtractUtm:
Failed parsing GPS position for DJI_0301.JPG
For more detailed information, see log file.

(...)

Building objmodel:
Saving model... done.
Whole texturing procedure took: 225.586s
[INFO] Running ODM Texturing Cell - Finished
[INFO] Running ODM Georeferencing Cell
[WARNING] Georeferencing failed. Make sure your photos have geotags in the EXIF or you have provided a GCP file.
[INFO] Running ODM Georeferencing Cell - Finished
[INFO] Running ODM DEM Cell
[INFO] Classify: True
[INFO] Create DSM: True
[INFO] Create DTM: True
[INFO] DEM input file /code/odm_georeferencing/odm_georeferenced_model.las found: False
[WARNING] DEM will not be generated
[INFO] Running ODM DEM Cell - Finished
[INFO] Running ODM Orthophoto Cell
[DEBUG] running /code/build/bin/odm_orthophoto -inputFile /code/odm_texturing/odm_textured_model.obj -logFile /code/odm_orthophoto/odm_orthophoto_log.txt -outputFile /code/odm_orthophoto/odm_orthophoto.png -resolution 10.0 -outputCornerFile /code/odm_orthophoto/odm_orthophoto_corners.txt
[WARNING] No geo-referenced orthophoto created due to missing geo-referencing or corner coordinates.
[INFO] Running ODM OrthoPhoto Cell - Finished
[INFO] OpenDroneMap app finished - Sat Dec 29 22:12:22 2018
</syntaxhighlight>

=== Running docker OpenDroneMap ===

==== Update to last OpenDroneMap docker image ====

<syntaxhighlight lang="bash">
docker pull opendronemap/opendronemap
</syntaxhighlight>

==== OpenDroneMap docker image ====

# Install docker
# Add you user to docker group
# sudo -H pip install requests

<syntaxhighlight lang="bash">
mkdir OpenDroneMap
cd OpenDroneMap
git clone git@github.com:OpenDroneMap/odm_data_aukerman.git
cd odm_data_aukerman

export odmi=`pwd`
ls -l $odmi

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd /home/jgr/Documentos/sletten16maj2018-gcp
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
opendronemap/opendronemap --gcp gcp_list.txt --dtm --dsm
</syntaxhighlight>

Sem GCP:

<syntaxhighlight lang="bash">
cd ~/Documentos/costanovadoprado/
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm --orthophoto-resolution 10.0
</syntaxhighlight>

Nota: os ortos estão a ficar com muitas interferências do modelo 3D, nas áreas urbanas.

Related problem: http://community.opendronemap.org/t/buildings/929

Será que voar com a câmara a 75 graus ajuda? Fiz um voo com Double Grid, com a camara a 70 graus (default do Pix4d capture).

==== Mac ====

1. Install Docker

2. <syntaxhighlight lang="bash">
docker run -it --rm -v $(pwd)/images:/code/images -v $(pwd)/odm_orthophoto:/code/odm_orthophoto -v $(pwd)/odm_texturing:/code/odm_texturing -v $(pwd)/odm_georeferencing:/code/odm_georeferencing -v $(pwd)/odm_meshing:/code/odm_meshing -v $(pwd)/opensfm:/code/opensfm -v $(pwd)/odm_dem:/code/odm_dem opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

==== Windows ====

Install Docker

Configure docker (more CPU, more memory)

CPUs: 6

Memory: 12032 Mb

Swap: 4096 Mb

Create the projet folder structure

Project folder:
c:\Users\dlt265\Documents\uav_sckovskolen_feb20018_incl_GCP\

Image folder:
c:\Users\dlt265\Documents\uav_sckovskolen_feb20018_incl_GCP\images

Create folders for the OpenDroneMap output.

<syntaxhighlight lang="bash">
cd Documents\uav_sckovskolen_feb20018_incl_GCP
md odm_orthophoto
md odm_texturing
md odm_georeferencing
md odm_meshing
md opensfm
md odm_dem
</syntaxhighlight>

<syntaxhighlight lang="bash">
docker run -it --rm -v $pwd/images:/code/images -v $pwd/odm_orthophoto:/code/odm_orthophoto -v $pwd/odm_texturing:/code/odm_texturing -v $pwd/odm_georeferencing:/code/odm_georeferencing -v $pwd/odm_meshing:/code/odm_meshing -v $pwd/opensfm:/code/opensfm -v $pwd/odm_dem:/code/odm_dem opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd ~/Documentos/costanovadoprado2xgrid
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm --orthophoto-resolution 10.0 --mesh-octree-depth 10
</syntaxhighlight>

=== OpenSFM viewer (update) ===

<syntaxhighlight lang="bash">
sudo chown -R jgr:jgr *
git clone https://github.com/mapillary/OpenSfM.git
cd OpenSfM/viewer
ln -s ../../images .
python2 -m SimpleHTTPServer 7777
</syntaxhighlight>

=== OpenSFM viewer ===

<syntaxhighlight lang="bash">
jgr@zoe:~/Documentos/costanovadoprado$ sudo chown -R jgr:jgr *
jgr@zoe:~/Documentos/costanovadoprado$ cp -r ~/dev/OpenSfM/viewer opensfm
jgr@zoe:~/Documentos/costanovadoprado$ cd opensfm/
jgr@zoe:~/Documentos/costanovadoprado/opensfm$ ln -s ../images .
jgr@zoe:~/Documentos/costanovadoprado/opensfm$ python -m SimpleHTTPServer
Serving HTTP on 0.0.0.0 port 8000 ...
</syntaxhighlight>

http://localhost:8000/viewer/reconstruction.html#file=/reconstruction.json

==== OpenSFM view images on QGIS ====

/home/jgr/Documentos/costanovadoprado/images/DJI_0595.JPG

-8.7515052, 40.6114774, 22.4100000, 2018:08:23 10:05:11

/home/jgr/Documentos/costanovadoprado/opensfm/reference_lla.json

Centro aproximado do ortophoto resultante (adicionado ao projeto QGIS)

<syntaxhighlight lang="json">
{
"latitude": 40.61272372901514,
"altitude": 0,
"longitude": -8.752983409509966
}
</syntaxhighlight>

<syntaxhighlight lang="json">
"DJI_0595.JPG": {
"orientation": 1,
"camera": "v2 dji fc220 4000 3000 perspective 0.7222",
"gps_position": [
125.10012061257521,
-138.4010433354888,
22.407269606366754
],
"gps_dop": 15.0,
"rotation": [
2.1445873611073996,
-2.2856282209697523,
0.20066193557381898
],
"translation": [
-132.67853610360638,
133.40968771622724,
1.9668907291333997
],
"capture_time": 1535018711.0
},
</syntaxhighlight>

https://github.com/mapillary/OpenSfM/blob/master/opensfm/commands/export_geocoords.py

jgr@zoe:~/Documentos/costanovadoprado/opensfm$ wget https://raw.githubusercontent.com/mapillary/OpenSfM/master/opensfm/commands/export_geocoords.py

NÃO FUNCIONOU...

export_geocoords.py -dataset costanova

Ver: https://github.com/mapillary/OpenSfM/issues/183

=== webODM ===

https://github.com/OpenDroneMap/WebODM

<syntaxhighlight lang="bash">
git clone https://github.com/OpenDroneMap/WebODM --config core.autocrlf=input
cd WebODM
./webodm.sh start
</syntaxhighlight>

jgrocha/xxbatata

=== Tools ===

CloudCompare

QGIS Plugin Photo2Shape

Criar uma shapefile photos

Nas propriedades, no campo <syntaxhighlight inline lang="bash">filepath</syntaxhighlight> mudar para o tipo Fotografia.

=== Ground Control File ===

<syntaxhighlight lang="bash">
echo -7.778152 41.833203 957.575989 | cs2cs +init=epsg:4326 +to +init=epsg:3763
echo 708610.702 6209972.025 26.085 | cs2cs +init=epsg:25832 +to +init=epsg:32633

jgr@zoe:~/Documentos/sletten16maj2018-exif$ gdalsrsinfo epsg:32633 -o proj4
'+proj=utm +zone=33 +datum=WGS84 +units=m +no_defs '
jgr@zoe:~/Documentos/sletten16maj2018-exif$ gdalsrsinfo epsg:25832 -o proj4
'+proj=utm +zone=32 +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs '
</syntaxhighlight>

== Make my own OpenDroneMap image ==

=== Fork and clone ODM repository ===

<syntaxhighlight lang="bash">
git clone git@github.com:jgrocha/OpenDroneMap.git
cd OpenDroneMap
git checkout -b generate-laz-output
</syntaxhighlight>

=== Change source ===

=== Build new image ===

<syntaxhighlight lang="bash">
jgr@zoe:~/PycharmProjects/OpenDroneMap$ docker build --no-cache -t odm_altitude_0 .
</syntaxhighlight>

<syntaxhighlight lang="bash">
docker build -t odm_laz_image .
</syntaxhighlight>

=== Run new image ===

<syntaxhighlight lang="bash">
# cd "/mnt/bonn/nextCloud/Photos/DJI MAVIC PRO 2 Paradela/100MEDIA"
cd /mnt/bonn/nextCloud/Photos
ln -s 'DJI MAVIC PRO 2 Paradela/100MEDIA' images
export odmi=`pwd`
docker run --cpus 8 -it --rm -v $odmi/images:/code/images -v $odmi/odm_orthophoto:/code/odm_orthophoto -v $odmi/odm_texturing:/code/odm_texturing -v $odmi/odm_georeferencing:/code/odm_georeferencing -v $odmi/odm_meshing:/code/odm_meshing -v $odmi/opensfm:/code/opensfm -v $odmi/odm_dem:/code/odm_dem odm_altitude_0 --dtm --dsm --force-ccd 13.2
# --orthophoto-resolution 2.0 --mesh-octree-depth 2 --opensfm-processes 8
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd /home/jgr/Documentos/sletten16maj2018-gcp
export odmi=`pwd`
sudo rm -rf odm_georeferencing odm_meshing odm_orthophoto odm_texturing opensfm
docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
odm_laz_image --gcp gcp_list.txt --dtm --dsm
</syntaxhighlight>

The options for rerunning are: 'resize', 'opensfm', 'slam', 'cmvs', 'pmvs', 'odm_meshing', 'mvs_texturing', 'odm_georeferencing', 'odm_orthophoto'

<syntaxhighlight lang="bash">
docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
odm_laz_image --gcp gcp_list.txt --dtm --dsm --rerun-from odm_georeferencing
</syntaxhighlight>

=== Check the output ===

<syntaxhighlight lang="text">
running /code/build/bin/odm_georef -bundleFile /code/opensfm/bundle_r000.out -imagesPath /code/images -imagesListPath /code/opensfm/list_r000.out -inputFile /code/odm_texturing/odm_textured_model.obj -outputFile /code/odm_texturing/odm_textured_model_geo.obj -inputPointCloudFile /code/opensfm/depthmaps/merged.ply -outputPointCloudFile /code/odm_georeferencing/odm_georeferenced_model.ply -logFile /code/odm_georeferencing/odm_georeferencing_log.txt -outputTransformFile /code/odm_georeferencing/odm_georeferencing_transform.txt -georefFileOutputPath /code/odm_georeferencing/odm_georeferencing_model_geo.txt -gcpFile gcp_list.txt -outputCoordFile /code/odm_georeferencing/coords.txt
[DEBUG] running /code/SuperBuild/build/pdal/bin/pdal pipeline -i /code/odm_georeferencing/las.json --readers.ply.filename=/code/odm_georeferencing/odm_georeferenced_model.ply
PDAL: writers.las: Can't write LAZ output. PDAL not built with LASzip or LAZperf.
</syntaxhighlight>

<syntaxhighlight lang="json">
{
"pipeline": [
"untransformed.ply",
{
"type": "writers.las",
"a_srs": "+proj=utm +zone=33 +datum=WGS84 +units=m +no_defs ",
"offset_x": "334230.28164",
"offset_y": "6208095.41529",
"offset_z": "0",
"compression": "laszip",
"filename": "/code/odm_georeferencing/odm_georeferenced_model.laz"
}
]
}
</syntaxhighlight>

[[File:Captura de ecrã de 2018-06-17 14-34-10.png]]

=== Local pdal+LASzip ===

Build from source!

<syntaxhighlight lang="bash">
/usr/local/bin/pdal pipeline -i las.json --readers.ply.filename=odm_georeferenced_model.ply
-rw-r--r-- 1 jgr jgr 22661583 jun 17 11:47 odm_georeferenced_model.laz
-rw-r--r-- 1 jgr jgr 121586206 jun 17 11:42 odm_georeferenced_model.ply
</syntaxhighlight>

==== Previous result ====

[[File:Captura de ecrã de 2018-06-16 12-26-36.png]]

==== New result ====

=== Create Pull Request ===

close #845

=== Other fixes ===

epsg versus EPSG

== Point cloud classification ==

[DEBUG] running pdal info --boundary --filters.hexbin.edge_length=1 --filters.hexbin.threshold=0 /code/odm_georeferencing/odm_georeferenced_model.filtered.las > /code/odm_georeferencing/odm_georeferenced_model.boundary.json
PDAL: Argument references invalid/unused stage: 'filters.hexbin'.

Running OpenDroneMap

2019-02-04T10:55:30Z

Jgrocha: /* Drone Workshop */

=== Drone Workshop ===

1. Flight

WebODM

<syntaxhighlight lang="bash">
pip install docker-compose
</syntaxhighlight>

10:54

2. Data products

2.1 Orthophoto

Discussion: GCP, impact on the elevation model

Swipe tool

Point value: check ortho values

2.2 DEM/DSM

Discussion: difference between

Raster value

Profile tool

Visualization: hillshade

http://plas.io/

https://pdal.io/tutorial/pcl_ground/index.html#pcl-ground

<syntaxhighlight lang="bash">
-- original
pdal translate -i /code/odm_georeferencing/odm_georeferenced_model.laz -o /code/odm_georeferencing/odm_georeferenced_model.laz smrf --filters.smrf.cell=2 --filters.smrf.slope=10 --filters.smrf.window=10

-- VERY GOOD
pdal translate -i odm_georeferencing/odm_georeferenced_model.ply -o odm_georeferencing/odm_georeferenced_model_2.laz smrf --filters.smrf.cell=2 --filters.smrf.window=10

-- good
pdal ground -i odm_georeferencing/odm_georeferenced_model.ply -o odm_georeferencing/odm_georeferenced_model_3.laz
</syntaxhighlight>

2.3 Point cloud

What we get from the software

Visualization tools

https://pdal.io/workshop/exercises/analysis/dtm/dtm.html

3. Processing data products

3.1 Better classification

lasground

3.2 lasheight

3.3 lasclassify

=== DJI Mavic 2 PRO ===

[https://forum.dji.com/thread-167017-1-1.html Sensor size], [https://www.youtube.com/watch?v=xIncVCe6pg0 Video about sensor size]

==== Erro ====

Culpado: <syntaxhighlight lang="bash" inline>/home/jgr/PycharmProjects/OpenDroneMap/modules/odm_extract_utm</syntaxhighlight>

Todas as imagens estão com Exif.GPSInfo.GPSAltitude = 0.0

<syntaxhighlight lang="bash">
if (lon == 0.0 || lat == 0.0 || alt == 0.0) {
std::string error("Failed parsing GPS position for " + imageFilename);
throw UtmExtractorException(error);
}
</syntaxhighlight>

==== Remendo ====

<syntaxhighlight lang="bash">
exiv2 -pa DJI_0210.JPG
Exif.GPSInfo.GPSAltitude Rational 1 0.0 m

exiv2 -M"set Exif.GPSInfo.GPSAltitude Rational 1/10" DJI_0210.JPG
exiv2 -pa DJI_0210.JPG
Exif.GPSInfo.GPSAltitude Rational 1 0.1 m
</syntaxhighlight>

Chamada:

<syntaxhighlight lang="bash">
[INFO] Wrote images database: /code/images.json
[INFO] Found 106 usable images
[DEBUG] running /code/build/bin/odm_extract_utm -imagesPath /code/images/ -imageListFile /code/img_list.txt -outputCoordFile /code/odm_georeferencing/coords.txt -logFile /code/odm_georeferencing/odm_georeferencing_utm_log.txt
Error in OdmExtractUtm:
Failed parsing GPS position for DJI_0301.JPG
For more detailed information, see log file.
</syntaxhighlight>

<syntaxhighlight lang="text">
[INFO] Found 106 usable images
[WARNING] Could not generate coordinates file. Ignore if there is a GCP file. Error: Error in OdmExtractUtm:
Failed parsing GPS position for DJI_0301.JPG
For more detailed information, see log file.

(...)

Building objmodel:
Saving model... done.
Whole texturing procedure took: 225.586s
[INFO] Running ODM Texturing Cell - Finished
[INFO] Running ODM Georeferencing Cell
[WARNING] Georeferencing failed. Make sure your photos have geotags in the EXIF or you have provided a GCP file.
[INFO] Running ODM Georeferencing Cell - Finished
[INFO] Running ODM DEM Cell
[INFO] Classify: True
[INFO] Create DSM: True
[INFO] Create DTM: True
[INFO] DEM input file /code/odm_georeferencing/odm_georeferenced_model.las found: False
[WARNING] DEM will not be generated
[INFO] Running ODM DEM Cell - Finished
[INFO] Running ODM Orthophoto Cell
[DEBUG] running /code/build/bin/odm_orthophoto -inputFile /code/odm_texturing/odm_textured_model.obj -logFile /code/odm_orthophoto/odm_orthophoto_log.txt -outputFile /code/odm_orthophoto/odm_orthophoto.png -resolution 10.0 -outputCornerFile /code/odm_orthophoto/odm_orthophoto_corners.txt
[WARNING] No geo-referenced orthophoto created due to missing geo-referencing or corner coordinates.
[INFO] Running ODM OrthoPhoto Cell - Finished
[INFO] OpenDroneMap app finished - Sat Dec 29 22:12:22 2018
</syntaxhighlight>

=== Running docker OpenDroneMap ===

==== Update to last OpenDroneMap docker image ====

<syntaxhighlight lang="bash">
docker pull opendronemap/opendronemap
</syntaxhighlight>

==== OpenDroneMap docker image ====

# Install docker
# Add you user to docker group
# sudo -H pip install requests

<syntaxhighlight lang="bash">
mkdir OpenDroneMap
cd OpenDroneMap
git clone git@github.com:OpenDroneMap/odm_data_aukerman.git
cd odm_data_aukerman

export odmi=`pwd`
ls -l $odmi

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd /home/jgr/Documentos/sletten16maj2018-gcp
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
opendronemap/opendronemap --gcp gcp_list.txt --dtm --dsm
</syntaxhighlight>

Sem GCP:

<syntaxhighlight lang="bash">
cd ~/Documentos/costanovadoprado/
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm --orthophoto-resolution 10.0
</syntaxhighlight>

Nota: os ortos estão a ficar com muitas interferências do modelo 3D, nas áreas urbanas.

Related problem: http://community.opendronemap.org/t/buildings/929

Será que voar com a câmara a 75 graus ajuda? Fiz um voo com Double Grid, com a camara a 70 graus (default do Pix4d capture).

==== Windows ====

Install Docker

Configure docker (more CPU, more memory)

CPUs: 6

Memory: 12032 Mb

Swap: 4096 Mb

Create the projet folder structure

Project folder:
c:\Users\dlt265\Documents\uav_sckovskolen_feb20018_incl_GCP\

Image folder:
c:\Users\dlt265\Documents\uav_sckovskolen_feb20018_incl_GCP\images

Create folders for the OpenDroneMap output.

<syntaxhighlight lang="bash">
cd Documents\uav_sckovskolen_feb20018_incl_GCP
md odm_orthophoto
md odm_texturing
md odm_georeferencing
md odm_meshing
md opensfm
md odm_dem
</syntaxhighlight>

<syntaxhighlight lang="bash">
docker run -it --rm -v $pwd/images:/code/images -v $pwd/odm_orthophoto:/code/odm_orthophoto -v $pwd/odm_texturing:/code/odm_texturing -v $pwd/odm_georeferencing:/code/odm_georeferencing -v $pwd/odm_meshing:/code/odm_meshing -v $pwd/opensfm:/code/opensfm -v $pwd/odm_dem:/code/odm_dem opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd ~/Documentos/costanovadoprado2xgrid
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm --orthophoto-resolution 10.0 --mesh-octree-depth 10
</syntaxhighlight>

=== OpenSFM viewer (update) ===

<syntaxhighlight lang="bash">
sudo chown -R jgr:jgr *
git clone https://github.com/mapillary/OpenSfM.git
cd OpenSfM/viewer
ln -s ../../images .
python2 -m SimpleHTTPServer 7777
</syntaxhighlight>

=== OpenSFM viewer ===

<syntaxhighlight lang="bash">
jgr@zoe:~/Documentos/costanovadoprado$ sudo chown -R jgr:jgr *
jgr@zoe:~/Documentos/costanovadoprado$ cp -r ~/dev/OpenSfM/viewer opensfm
jgr@zoe:~/Documentos/costanovadoprado$ cd opensfm/
jgr@zoe:~/Documentos/costanovadoprado/opensfm$ ln -s ../images .
jgr@zoe:~/Documentos/costanovadoprado/opensfm$ python -m SimpleHTTPServer
Serving HTTP on 0.0.0.0 port 8000 ...
</syntaxhighlight>

http://localhost:8000/viewer/reconstruction.html#file=/reconstruction.json

==== OpenSFM view images on QGIS ====

/home/jgr/Documentos/costanovadoprado/images/DJI_0595.JPG

-8.7515052, 40.6114774, 22.4100000, 2018:08:23 10:05:11

/home/jgr/Documentos/costanovadoprado/opensfm/reference_lla.json

Centro aproximado do ortophoto resultante (adicionado ao projeto QGIS)

<syntaxhighlight lang="json">
{
"latitude": 40.61272372901514,
"altitude": 0,
"longitude": -8.752983409509966
}
</syntaxhighlight>

<syntaxhighlight lang="json">
"DJI_0595.JPG": {
"orientation": 1,
"camera": "v2 dji fc220 4000 3000 perspective 0.7222",
"gps_position": [
125.10012061257521,
-138.4010433354888,
22.407269606366754
],
"gps_dop": 15.0,
"rotation": [
2.1445873611073996,
-2.2856282209697523,
0.20066193557381898
],
"translation": [
-132.67853610360638,
133.40968771622724,
1.9668907291333997
],
"capture_time": 1535018711.0
},
</syntaxhighlight>

https://github.com/mapillary/OpenSfM/blob/master/opensfm/commands/export_geocoords.py

jgr@zoe:~/Documentos/costanovadoprado/opensfm$ wget https://raw.githubusercontent.com/mapillary/OpenSfM/master/opensfm/commands/export_geocoords.py

NÃO FUNCIONOU...

export_geocoords.py -dataset costanova

Ver: https://github.com/mapillary/OpenSfM/issues/183

=== webODM ===

https://github.com/OpenDroneMap/WebODM

<syntaxhighlight lang="bash">
git clone https://github.com/OpenDroneMap/WebODM --config core.autocrlf=input
cd WebODM
./webodm.sh start
</syntaxhighlight>

jgrocha/xxbatata

=== Tools ===

CloudCompare

QGIS Plugin Photo2Shape

Criar uma shapefile photos

Nas propriedades, no campo <syntaxhighlight inline lang="bash">filepath</syntaxhighlight> mudar para o tipo Fotografia.

=== Ground Control File ===

<syntaxhighlight lang="bash">
echo -7.778152 41.833203 957.575989 | cs2cs +init=epsg:4326 +to +init=epsg:3763
echo 708610.702 6209972.025 26.085 | cs2cs +init=epsg:25832 +to +init=epsg:32633

jgr@zoe:~/Documentos/sletten16maj2018-exif$ gdalsrsinfo epsg:32633 -o proj4
'+proj=utm +zone=33 +datum=WGS84 +units=m +no_defs '
jgr@zoe:~/Documentos/sletten16maj2018-exif$ gdalsrsinfo epsg:25832 -o proj4
'+proj=utm +zone=32 +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs '
</syntaxhighlight>

== Make my own OpenDroneMap image ==

=== Fork and clone ODM repository ===

<syntaxhighlight lang="bash">
git clone git@github.com:jgrocha/OpenDroneMap.git
cd OpenDroneMap
git checkout -b generate-laz-output
</syntaxhighlight>

=== Change source ===

=== Build new image ===

<syntaxhighlight lang="bash">
jgr@zoe:~/PycharmProjects/OpenDroneMap$ docker build --no-cache -t odm_altitude_0 .
</syntaxhighlight>

<syntaxhighlight lang="bash">
docker build -t odm_laz_image .
</syntaxhighlight>

=== Run new image ===

<syntaxhighlight lang="bash">
# cd "/mnt/bonn/nextCloud/Photos/DJI MAVIC PRO 2 Paradela/100MEDIA"
cd /mnt/bonn/nextCloud/Photos
ln -s 'DJI MAVIC PRO 2 Paradela/100MEDIA' images
export odmi=`pwd`
docker run --cpus 8 -it --rm -v $odmi/images:/code/images -v $odmi/odm_orthophoto:/code/odm_orthophoto -v $odmi/odm_texturing:/code/odm_texturing -v $odmi/odm_georeferencing:/code/odm_georeferencing -v $odmi/odm_meshing:/code/odm_meshing -v $odmi/opensfm:/code/opensfm -v $odmi/odm_dem:/code/odm_dem odm_altitude_0 --dtm --dsm --force-ccd 13.2
# --orthophoto-resolution 2.0 --mesh-octree-depth 2 --opensfm-processes 8
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd /home/jgr/Documentos/sletten16maj2018-gcp
export odmi=`pwd`
sudo rm -rf odm_georeferencing odm_meshing odm_orthophoto odm_texturing opensfm
docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
odm_laz_image --gcp gcp_list.txt --dtm --dsm
</syntaxhighlight>

The options for rerunning are: 'resize', 'opensfm', 'slam', 'cmvs', 'pmvs', 'odm_meshing', 'mvs_texturing', 'odm_georeferencing', 'odm_orthophoto'

<syntaxhighlight lang="bash">
docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
odm_laz_image --gcp gcp_list.txt --dtm --dsm --rerun-from odm_georeferencing
</syntaxhighlight>

=== Check the output ===

<syntaxhighlight lang="text">
running /code/build/bin/odm_georef -bundleFile /code/opensfm/bundle_r000.out -imagesPath /code/images -imagesListPath /code/opensfm/list_r000.out -inputFile /code/odm_texturing/odm_textured_model.obj -outputFile /code/odm_texturing/odm_textured_model_geo.obj -inputPointCloudFile /code/opensfm/depthmaps/merged.ply -outputPointCloudFile /code/odm_georeferencing/odm_georeferenced_model.ply -logFile /code/odm_georeferencing/odm_georeferencing_log.txt -outputTransformFile /code/odm_georeferencing/odm_georeferencing_transform.txt -georefFileOutputPath /code/odm_georeferencing/odm_georeferencing_model_geo.txt -gcpFile gcp_list.txt -outputCoordFile /code/odm_georeferencing/coords.txt
[DEBUG] running /code/SuperBuild/build/pdal/bin/pdal pipeline -i /code/odm_georeferencing/las.json --readers.ply.filename=/code/odm_georeferencing/odm_georeferenced_model.ply
PDAL: writers.las: Can't write LAZ output. PDAL not built with LASzip or LAZperf.
</syntaxhighlight>

<syntaxhighlight lang="json">
{
"pipeline": [
"untransformed.ply",
{
"type": "writers.las",
"a_srs": "+proj=utm +zone=33 +datum=WGS84 +units=m +no_defs ",
"offset_x": "334230.28164",
"offset_y": "6208095.41529",
"offset_z": "0",
"compression": "laszip",
"filename": "/code/odm_georeferencing/odm_georeferenced_model.laz"
}
]
}
</syntaxhighlight>

[[File:Captura de ecrã de 2018-06-17 14-34-10.png]]

=== Local pdal+LASzip ===

Build from source!

<syntaxhighlight lang="bash">
/usr/local/bin/pdal pipeline -i las.json --readers.ply.filename=odm_georeferenced_model.ply
-rw-r--r-- 1 jgr jgr 22661583 jun 17 11:47 odm_georeferenced_model.laz
-rw-r--r-- 1 jgr jgr 121586206 jun 17 11:42 odm_georeferenced_model.ply
</syntaxhighlight>

==== Previous result ====

[[File:Captura de ecrã de 2018-06-16 12-26-36.png]]

==== New result ====

=== Create Pull Request ===

close #845

=== Other fixes ===

epsg versus EPSG

== Point cloud classification ==

[DEBUG] running pdal info --boundary --filters.hexbin.edge_length=1 --filters.hexbin.threshold=0 /code/odm_georeferencing/odm_georeferenced_model.filtered.las > /code/odm_georeferencing/odm_georeferenced_model.boundary.json
PDAL: Argument references invalid/unused stage: 'filters.hexbin'.

Running OpenDroneMap

2019-02-04T10:34:41Z

Jgrocha: /* Drone Workshop */

=== Drone Workshop ===

1. Flight

WebODM

<syntaxhighlight lang="bash">
pip install docker-compose
</syntaxhighlight>

2. Data products

2.1 Orthophoto

Discussion: GCP, impact on the elevation model

Swipe tool

Point value: check ortho values

2.2 DEM/DSM

Discussion: difference between

Raster value

Profile tool

Visualization: hillshade

http://plas.io/

https://pdal.io/tutorial/pcl_ground/index.html#pcl-ground

<syntaxhighlight lang="bash">
-- original
pdal translate -i /code/odm_georeferencing/odm_georeferenced_model.laz -o /code/odm_georeferencing/odm_georeferenced_model.laz smrf --filters.smrf.cell=2 --filters.smrf.slope=10 --filters.smrf.window=10

-- VERY GOOD
pdal translate -i odm_georeferencing/odm_georeferenced_model.ply -o odm_georeferencing/odm_georeferenced_model_2.laz smrf --filters.smrf.cell=2 --filters.smrf.window=10

-- good
pdal ground -i odm_georeferencing/odm_georeferenced_model.ply -o odm_georeferencing/odm_georeferenced_model_3.laz
</syntaxhighlight>

2.3 Point cloud

What we get from the software

Visualization tools

https://pdal.io/workshop/exercises/analysis/dtm/dtm.html

3. Processing data products

3.1 Better classification

lasground

3.2 lasheight

3.3 lasclassify

=== DJI Mavic 2 PRO ===

[https://forum.dji.com/thread-167017-1-1.html Sensor size], [https://www.youtube.com/watch?v=xIncVCe6pg0 Video about sensor size]

==== Erro ====

Culpado: <syntaxhighlight lang="bash" inline>/home/jgr/PycharmProjects/OpenDroneMap/modules/odm_extract_utm</syntaxhighlight>

Todas as imagens estão com Exif.GPSInfo.GPSAltitude = 0.0

<syntaxhighlight lang="bash">
if (lon == 0.0 || lat == 0.0 || alt == 0.0) {
std::string error("Failed parsing GPS position for " + imageFilename);
throw UtmExtractorException(error);
}
</syntaxhighlight>

==== Remendo ====

<syntaxhighlight lang="bash">
exiv2 -pa DJI_0210.JPG
Exif.GPSInfo.GPSAltitude Rational 1 0.0 m

exiv2 -M"set Exif.GPSInfo.GPSAltitude Rational 1/10" DJI_0210.JPG
exiv2 -pa DJI_0210.JPG
Exif.GPSInfo.GPSAltitude Rational 1 0.1 m
</syntaxhighlight>

Chamada:

<syntaxhighlight lang="bash">
[INFO] Wrote images database: /code/images.json
[INFO] Found 106 usable images
[DEBUG] running /code/build/bin/odm_extract_utm -imagesPath /code/images/ -imageListFile /code/img_list.txt -outputCoordFile /code/odm_georeferencing/coords.txt -logFile /code/odm_georeferencing/odm_georeferencing_utm_log.txt
Error in OdmExtractUtm:
Failed parsing GPS position for DJI_0301.JPG
For more detailed information, see log file.
</syntaxhighlight>

<syntaxhighlight lang="text">
[INFO] Found 106 usable images
[WARNING] Could not generate coordinates file. Ignore if there is a GCP file. Error: Error in OdmExtractUtm:
Failed parsing GPS position for DJI_0301.JPG
For more detailed information, see log file.

(...)

Building objmodel:
Saving model... done.
Whole texturing procedure took: 225.586s
[INFO] Running ODM Texturing Cell - Finished
[INFO] Running ODM Georeferencing Cell
[WARNING] Georeferencing failed. Make sure your photos have geotags in the EXIF or you have provided a GCP file.
[INFO] Running ODM Georeferencing Cell - Finished
[INFO] Running ODM DEM Cell
[INFO] Classify: True
[INFO] Create DSM: True
[INFO] Create DTM: True
[INFO] DEM input file /code/odm_georeferencing/odm_georeferenced_model.las found: False
[WARNING] DEM will not be generated
[INFO] Running ODM DEM Cell - Finished
[INFO] Running ODM Orthophoto Cell
[DEBUG] running /code/build/bin/odm_orthophoto -inputFile /code/odm_texturing/odm_textured_model.obj -logFile /code/odm_orthophoto/odm_orthophoto_log.txt -outputFile /code/odm_orthophoto/odm_orthophoto.png -resolution 10.0 -outputCornerFile /code/odm_orthophoto/odm_orthophoto_corners.txt
[WARNING] No geo-referenced orthophoto created due to missing geo-referencing or corner coordinates.
[INFO] Running ODM OrthoPhoto Cell - Finished
[INFO] OpenDroneMap app finished - Sat Dec 29 22:12:22 2018
</syntaxhighlight>

=== Running docker OpenDroneMap ===

==== Update to last OpenDroneMap docker image ====

<syntaxhighlight lang="bash">
docker pull opendronemap/opendronemap
</syntaxhighlight>

==== OpenDroneMap docker image ====

# Install docker
# Add you user to docker group
# sudo -H pip install requests

<syntaxhighlight lang="bash">
mkdir OpenDroneMap
cd OpenDroneMap
git clone git@github.com:OpenDroneMap/odm_data_aukerman.git
cd odm_data_aukerman

export odmi=`pwd`
ls -l $odmi

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd /home/jgr/Documentos/sletten16maj2018-gcp
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
opendronemap/opendronemap --gcp gcp_list.txt --dtm --dsm
</syntaxhighlight>

Sem GCP:

<syntaxhighlight lang="bash">
cd ~/Documentos/costanovadoprado/
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm --orthophoto-resolution 10.0
</syntaxhighlight>

Nota: os ortos estão a ficar com muitas interferências do modelo 3D, nas áreas urbanas.

Related problem: http://community.opendronemap.org/t/buildings/929

Será que voar com a câmara a 75 graus ajuda? Fiz um voo com Double Grid, com a camara a 70 graus (default do Pix4d capture).

==== Windows ====

Install Docker

Configure docker (more CPU, more memory)

CPUs: 6

Memory: 12032 Mb

Swap: 4096 Mb

Create the projet folder structure

Project folder:
c:\Users\dlt265\Documents\uav_sckovskolen_feb20018_incl_GCP\

Image folder:
c:\Users\dlt265\Documents\uav_sckovskolen_feb20018_incl_GCP\images

Create folders for the OpenDroneMap output.

<syntaxhighlight lang="bash">
cd Documents\uav_sckovskolen_feb20018_incl_GCP
md odm_orthophoto
md odm_texturing
md odm_georeferencing
md odm_meshing
md opensfm
md odm_dem
</syntaxhighlight>

<syntaxhighlight lang="bash">
docker run -it --rm -v $pwd/images:/code/images -v $pwd/odm_orthophoto:/code/odm_orthophoto -v $pwd/odm_texturing:/code/odm_texturing -v $pwd/odm_georeferencing:/code/odm_georeferencing -v $pwd/odm_meshing:/code/odm_meshing -v $pwd/opensfm:/code/opensfm -v $pwd/odm_dem:/code/odm_dem opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd ~/Documentos/costanovadoprado2xgrid
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm --orthophoto-resolution 10.0 --mesh-octree-depth 10
</syntaxhighlight>

=== OpenSFM viewer (update) ===

<syntaxhighlight lang="bash">
sudo chown -R jgr:jgr *
git clone https://github.com/mapillary/OpenSfM.git
cd OpenSfM/viewer
ln -s ../../images .
python2 -m SimpleHTTPServer 7777
</syntaxhighlight>

=== OpenSFM viewer ===

<syntaxhighlight lang="bash">
jgr@zoe:~/Documentos/costanovadoprado$ sudo chown -R jgr:jgr *
jgr@zoe:~/Documentos/costanovadoprado$ cp -r ~/dev/OpenSfM/viewer opensfm
jgr@zoe:~/Documentos/costanovadoprado$ cd opensfm/
jgr@zoe:~/Documentos/costanovadoprado/opensfm$ ln -s ../images .
jgr@zoe:~/Documentos/costanovadoprado/opensfm$ python -m SimpleHTTPServer
Serving HTTP on 0.0.0.0 port 8000 ...
</syntaxhighlight>

http://localhost:8000/viewer/reconstruction.html#file=/reconstruction.json

==== OpenSFM view images on QGIS ====

/home/jgr/Documentos/costanovadoprado/images/DJI_0595.JPG

-8.7515052, 40.6114774, 22.4100000, 2018:08:23 10:05:11

/home/jgr/Documentos/costanovadoprado/opensfm/reference_lla.json

Centro aproximado do ortophoto resultante (adicionado ao projeto QGIS)

<syntaxhighlight lang="json">
{
"latitude": 40.61272372901514,
"altitude": 0,
"longitude": -8.752983409509966
}
</syntaxhighlight>

<syntaxhighlight lang="json">
"DJI_0595.JPG": {
"orientation": 1,
"camera": "v2 dji fc220 4000 3000 perspective 0.7222",
"gps_position": [
125.10012061257521,
-138.4010433354888,
22.407269606366754
],
"gps_dop": 15.0,
"rotation": [
2.1445873611073996,
-2.2856282209697523,
0.20066193557381898
],
"translation": [
-132.67853610360638,
133.40968771622724,
1.9668907291333997
],
"capture_time": 1535018711.0
},
</syntaxhighlight>

https://github.com/mapillary/OpenSfM/blob/master/opensfm/commands/export_geocoords.py

jgr@zoe:~/Documentos/costanovadoprado/opensfm$ wget https://raw.githubusercontent.com/mapillary/OpenSfM/master/opensfm/commands/export_geocoords.py

NÃO FUNCIONOU...

export_geocoords.py -dataset costanova

Ver: https://github.com/mapillary/OpenSfM/issues/183

=== webODM ===

https://github.com/OpenDroneMap/WebODM

<syntaxhighlight lang="bash">
git clone https://github.com/OpenDroneMap/WebODM --config core.autocrlf=input
cd WebODM
./webodm.sh start
</syntaxhighlight>

jgrocha/xxbatata

=== Tools ===

CloudCompare

QGIS Plugin Photo2Shape

Criar uma shapefile photos

Nas propriedades, no campo <syntaxhighlight inline lang="bash">filepath</syntaxhighlight> mudar para o tipo Fotografia.

=== Ground Control File ===

<syntaxhighlight lang="bash">
echo -7.778152 41.833203 957.575989 | cs2cs +init=epsg:4326 +to +init=epsg:3763
echo 708610.702 6209972.025 26.085 | cs2cs +init=epsg:25832 +to +init=epsg:32633

jgr@zoe:~/Documentos/sletten16maj2018-exif$ gdalsrsinfo epsg:32633 -o proj4
'+proj=utm +zone=33 +datum=WGS84 +units=m +no_defs '
jgr@zoe:~/Documentos/sletten16maj2018-exif$ gdalsrsinfo epsg:25832 -o proj4
'+proj=utm +zone=32 +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs '
</syntaxhighlight>

== Make my own OpenDroneMap image ==

=== Fork and clone ODM repository ===

<syntaxhighlight lang="bash">
git clone git@github.com:jgrocha/OpenDroneMap.git
cd OpenDroneMap
git checkout -b generate-laz-output
</syntaxhighlight>

=== Change source ===

=== Build new image ===

<syntaxhighlight lang="bash">
jgr@zoe:~/PycharmProjects/OpenDroneMap$ docker build --no-cache -t odm_altitude_0 .
</syntaxhighlight>

<syntaxhighlight lang="bash">
docker build -t odm_laz_image .
</syntaxhighlight>

=== Run new image ===

<syntaxhighlight lang="bash">
# cd "/mnt/bonn/nextCloud/Photos/DJI MAVIC PRO 2 Paradela/100MEDIA"
cd /mnt/bonn/nextCloud/Photos
ln -s 'DJI MAVIC PRO 2 Paradela/100MEDIA' images
export odmi=`pwd`
docker run --cpus 8 -it --rm -v $odmi/images:/code/images -v $odmi/odm_orthophoto:/code/odm_orthophoto -v $odmi/odm_texturing:/code/odm_texturing -v $odmi/odm_georeferencing:/code/odm_georeferencing -v $odmi/odm_meshing:/code/odm_meshing -v $odmi/opensfm:/code/opensfm -v $odmi/odm_dem:/code/odm_dem odm_altitude_0 --dtm --dsm --force-ccd 13.2
# --orthophoto-resolution 2.0 --mesh-octree-depth 2 --opensfm-processes 8
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd /home/jgr/Documentos/sletten16maj2018-gcp
export odmi=`pwd`
sudo rm -rf odm_georeferencing odm_meshing odm_orthophoto odm_texturing opensfm
docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
odm_laz_image --gcp gcp_list.txt --dtm --dsm
</syntaxhighlight>

The options for rerunning are: 'resize', 'opensfm', 'slam', 'cmvs', 'pmvs', 'odm_meshing', 'mvs_texturing', 'odm_georeferencing', 'odm_orthophoto'

<syntaxhighlight lang="bash">
docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
odm_laz_image --gcp gcp_list.txt --dtm --dsm --rerun-from odm_georeferencing
</syntaxhighlight>

=== Check the output ===

<syntaxhighlight lang="text">
running /code/build/bin/odm_georef -bundleFile /code/opensfm/bundle_r000.out -imagesPath /code/images -imagesListPath /code/opensfm/list_r000.out -inputFile /code/odm_texturing/odm_textured_model.obj -outputFile /code/odm_texturing/odm_textured_model_geo.obj -inputPointCloudFile /code/opensfm/depthmaps/merged.ply -outputPointCloudFile /code/odm_georeferencing/odm_georeferenced_model.ply -logFile /code/odm_georeferencing/odm_georeferencing_log.txt -outputTransformFile /code/odm_georeferencing/odm_georeferencing_transform.txt -georefFileOutputPath /code/odm_georeferencing/odm_georeferencing_model_geo.txt -gcpFile gcp_list.txt -outputCoordFile /code/odm_georeferencing/coords.txt
[DEBUG] running /code/SuperBuild/build/pdal/bin/pdal pipeline -i /code/odm_georeferencing/las.json --readers.ply.filename=/code/odm_georeferencing/odm_georeferenced_model.ply
PDAL: writers.las: Can't write LAZ output. PDAL not built with LASzip or LAZperf.
</syntaxhighlight>

<syntaxhighlight lang="json">
{
"pipeline": [
"untransformed.ply",
{
"type": "writers.las",
"a_srs": "+proj=utm +zone=33 +datum=WGS84 +units=m +no_defs ",
"offset_x": "334230.28164",
"offset_y": "6208095.41529",
"offset_z": "0",
"compression": "laszip",
"filename": "/code/odm_georeferencing/odm_georeferenced_model.laz"
}
]
}
</syntaxhighlight>

[[File:Captura de ecrã de 2018-06-17 14-34-10.png]]

=== Local pdal+LASzip ===

Build from source!

<syntaxhighlight lang="bash">
/usr/local/bin/pdal pipeline -i las.json --readers.ply.filename=odm_georeferenced_model.ply
-rw-r--r-- 1 jgr jgr 22661583 jun 17 11:47 odm_georeferenced_model.laz
-rw-r--r-- 1 jgr jgr 121586206 jun 17 11:42 odm_georeferenced_model.ply
</syntaxhighlight>

==== Previous result ====

[[File:Captura de ecrã de 2018-06-16 12-26-36.png]]

==== New result ====

=== Create Pull Request ===

close #845

=== Other fixes ===

epsg versus EPSG

== Point cloud classification ==

[DEBUG] running pdal info --boundary --filters.hexbin.edge_length=1 --filters.hexbin.threshold=0 /code/odm_georeferencing/odm_georeferenced_model.filtered.las > /code/odm_georeferencing/odm_georeferenced_model.boundary.json
PDAL: Argument references invalid/unused stage: 'filters.hexbin'.

Running OpenDroneMap

2019-02-03T21:50:48Z

Jgrocha: /* Drone Workshop */

=== Drone Workshop ===

1. Flight

2. Data products

2.1 Orthophoto

Discussion: GCP, impact on the elevation model

Swipe tool

Point value: check ortho values

2.2 DEM/DSM

Discussion: difference between

Raster value

Profile tool

Visualization: hillshade

http://plas.io/

https://pdal.io/tutorial/pcl_ground/index.html#pcl-ground

<syntaxhighlight lang="bash">
-- original
pdal translate -i /code/odm_georeferencing/odm_georeferenced_model.laz -o /code/odm_georeferencing/odm_georeferenced_model.laz smrf --filters.smrf.cell=2 --filters.smrf.slope=10 --filters.smrf.window=10

-- VERY GOOD
pdal translate -i odm_georeferencing/odm_georeferenced_model.ply -o odm_georeferencing/odm_georeferenced_model_2.laz smrf --filters.smrf.cell=2 --filters.smrf.window=10

-- good
pdal ground -i odm_georeferencing/odm_georeferenced_model.ply -o odm_georeferencing/odm_georeferenced_model_3.laz
</syntaxhighlight>

2.3 Point cloud

What we get from the software

Visualization tools

https://pdal.io/workshop/exercises/analysis/dtm/dtm.html

3. Processing data products

3.1 Better classification

lasground

3.2 lasheight

3.3 lasclassify

=== DJI Mavic 2 PRO ===

[https://forum.dji.com/thread-167017-1-1.html Sensor size], [https://www.youtube.com/watch?v=xIncVCe6pg0 Video about sensor size]

==== Erro ====

Culpado: <syntaxhighlight lang="bash" inline>/home/jgr/PycharmProjects/OpenDroneMap/modules/odm_extract_utm</syntaxhighlight>

Todas as imagens estão com Exif.GPSInfo.GPSAltitude = 0.0

<syntaxhighlight lang="bash">
if (lon == 0.0 || lat == 0.0 || alt == 0.0) {
std::string error("Failed parsing GPS position for " + imageFilename);
throw UtmExtractorException(error);
}
</syntaxhighlight>

==== Remendo ====

<syntaxhighlight lang="bash">
exiv2 -pa DJI_0210.JPG
Exif.GPSInfo.GPSAltitude Rational 1 0.0 m

exiv2 -M"set Exif.GPSInfo.GPSAltitude Rational 1/10" DJI_0210.JPG
exiv2 -pa DJI_0210.JPG
Exif.GPSInfo.GPSAltitude Rational 1 0.1 m
</syntaxhighlight>

Chamada:

<syntaxhighlight lang="bash">
[INFO] Wrote images database: /code/images.json
[INFO] Found 106 usable images
[DEBUG] running /code/build/bin/odm_extract_utm -imagesPath /code/images/ -imageListFile /code/img_list.txt -outputCoordFile /code/odm_georeferencing/coords.txt -logFile /code/odm_georeferencing/odm_georeferencing_utm_log.txt
Error in OdmExtractUtm:
Failed parsing GPS position for DJI_0301.JPG
For more detailed information, see log file.
</syntaxhighlight>

<syntaxhighlight lang="text">
[INFO] Found 106 usable images
[WARNING] Could not generate coordinates file. Ignore if there is a GCP file. Error: Error in OdmExtractUtm:
Failed parsing GPS position for DJI_0301.JPG
For more detailed information, see log file.

(...)

Building objmodel:
Saving model... done.
Whole texturing procedure took: 225.586s
[INFO] Running ODM Texturing Cell - Finished
[INFO] Running ODM Georeferencing Cell
[WARNING] Georeferencing failed. Make sure your photos have geotags in the EXIF or you have provided a GCP file.
[INFO] Running ODM Georeferencing Cell - Finished
[INFO] Running ODM DEM Cell
[INFO] Classify: True
[INFO] Create DSM: True
[INFO] Create DTM: True
[INFO] DEM input file /code/odm_georeferencing/odm_georeferenced_model.las found: False
[WARNING] DEM will not be generated
[INFO] Running ODM DEM Cell - Finished
[INFO] Running ODM Orthophoto Cell
[DEBUG] running /code/build/bin/odm_orthophoto -inputFile /code/odm_texturing/odm_textured_model.obj -logFile /code/odm_orthophoto/odm_orthophoto_log.txt -outputFile /code/odm_orthophoto/odm_orthophoto.png -resolution 10.0 -outputCornerFile /code/odm_orthophoto/odm_orthophoto_corners.txt
[WARNING] No geo-referenced orthophoto created due to missing geo-referencing or corner coordinates.
[INFO] Running ODM OrthoPhoto Cell - Finished
[INFO] OpenDroneMap app finished - Sat Dec 29 22:12:22 2018
</syntaxhighlight>

=== Running docker OpenDroneMap ===

==== Update to last OpenDroneMap docker image ====

<syntaxhighlight lang="bash">
docker pull opendronemap/opendronemap
</syntaxhighlight>

==== OpenDroneMap docker image ====

# Install docker
# Add you user to docker group
# sudo -H pip install requests

<syntaxhighlight lang="bash">
mkdir OpenDroneMap
cd OpenDroneMap
git clone git@github.com:OpenDroneMap/odm_data_aukerman.git
cd odm_data_aukerman

export odmi=`pwd`
ls -l $odmi

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd /home/jgr/Documentos/sletten16maj2018-gcp
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
opendronemap/opendronemap --gcp gcp_list.txt --dtm --dsm
</syntaxhighlight>

Sem GCP:

<syntaxhighlight lang="bash">
cd ~/Documentos/costanovadoprado/
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm --orthophoto-resolution 10.0
</syntaxhighlight>

Nota: os ortos estão a ficar com muitas interferências do modelo 3D, nas áreas urbanas.

Related problem: http://community.opendronemap.org/t/buildings/929

Será que voar com a câmara a 75 graus ajuda? Fiz um voo com Double Grid, com a camara a 70 graus (default do Pix4d capture).

==== Windows ====

Install Docker

Configure docker (more CPU, more memory)

CPUs: 6

Memory: 12032 Mb

Swap: 4096 Mb

Create the projet folder structure

Project folder:
c:\Users\dlt265\Documents\uav_sckovskolen_feb20018_incl_GCP\

Image folder:
c:\Users\dlt265\Documents\uav_sckovskolen_feb20018_incl_GCP\images

Create folders for the OpenDroneMap output.

<syntaxhighlight lang="bash">
cd Documents\uav_sckovskolen_feb20018_incl_GCP
md odm_orthophoto
md odm_texturing
md odm_georeferencing
md odm_meshing
md opensfm
md odm_dem
</syntaxhighlight>

<syntaxhighlight lang="bash">
docker run -it --rm -v $pwd/images:/code/images -v $pwd/odm_orthophoto:/code/odm_orthophoto -v $pwd/odm_texturing:/code/odm_texturing -v $pwd/odm_georeferencing:/code/odm_georeferencing -v $pwd/odm_meshing:/code/odm_meshing -v $pwd/opensfm:/code/opensfm -v $pwd/odm_dem:/code/odm_dem opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd ~/Documentos/costanovadoprado2xgrid
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm --orthophoto-resolution 10.0 --mesh-octree-depth 10
</syntaxhighlight>

=== OpenSFM viewer (update) ===

<syntaxhighlight lang="bash">
sudo chown -R jgr:jgr *
git clone https://github.com/mapillary/OpenSfM.git
cd OpenSfM/viewer
ln -s ../../images .
python2 -m SimpleHTTPServer 7777
</syntaxhighlight>

=== OpenSFM viewer ===

<syntaxhighlight lang="bash">
jgr@zoe:~/Documentos/costanovadoprado$ sudo chown -R jgr:jgr *
jgr@zoe:~/Documentos/costanovadoprado$ cp -r ~/dev/OpenSfM/viewer opensfm
jgr@zoe:~/Documentos/costanovadoprado$ cd opensfm/
jgr@zoe:~/Documentos/costanovadoprado/opensfm$ ln -s ../images .
jgr@zoe:~/Documentos/costanovadoprado/opensfm$ python -m SimpleHTTPServer
Serving HTTP on 0.0.0.0 port 8000 ...
</syntaxhighlight>

http://localhost:8000/viewer/reconstruction.html#file=/reconstruction.json

==== OpenSFM view images on QGIS ====

/home/jgr/Documentos/costanovadoprado/images/DJI_0595.JPG

-8.7515052, 40.6114774, 22.4100000, 2018:08:23 10:05:11

/home/jgr/Documentos/costanovadoprado/opensfm/reference_lla.json

Centro aproximado do ortophoto resultante (adicionado ao projeto QGIS)

<syntaxhighlight lang="json">
{
"latitude": 40.61272372901514,
"altitude": 0,
"longitude": -8.752983409509966
}
</syntaxhighlight>

<syntaxhighlight lang="json">
"DJI_0595.JPG": {
"orientation": 1,
"camera": "v2 dji fc220 4000 3000 perspective 0.7222",
"gps_position": [
125.10012061257521,
-138.4010433354888,
22.407269606366754
],
"gps_dop": 15.0,
"rotation": [
2.1445873611073996,
-2.2856282209697523,
0.20066193557381898
],
"translation": [
-132.67853610360638,
133.40968771622724,
1.9668907291333997
],
"capture_time": 1535018711.0
},
</syntaxhighlight>

https://github.com/mapillary/OpenSfM/blob/master/opensfm/commands/export_geocoords.py

jgr@zoe:~/Documentos/costanovadoprado/opensfm$ wget https://raw.githubusercontent.com/mapillary/OpenSfM/master/opensfm/commands/export_geocoords.py

NÃO FUNCIONOU...

export_geocoords.py -dataset costanova

Ver: https://github.com/mapillary/OpenSfM/issues/183

=== webODM ===

https://github.com/OpenDroneMap/WebODM

<syntaxhighlight lang="bash">
git clone https://github.com/OpenDroneMap/WebODM --config core.autocrlf=input
cd WebODM
./webodm.sh start
</syntaxhighlight>

jgrocha/xxbatata

=== Tools ===

CloudCompare

QGIS Plugin Photo2Shape

Criar uma shapefile photos

Nas propriedades, no campo <syntaxhighlight inline lang="bash">filepath</syntaxhighlight> mudar para o tipo Fotografia.

=== Ground Control File ===

<syntaxhighlight lang="bash">
echo -7.778152 41.833203 957.575989 | cs2cs +init=epsg:4326 +to +init=epsg:3763
echo 708610.702 6209972.025 26.085 | cs2cs +init=epsg:25832 +to +init=epsg:32633

jgr@zoe:~/Documentos/sletten16maj2018-exif$ gdalsrsinfo epsg:32633 -o proj4
'+proj=utm +zone=33 +datum=WGS84 +units=m +no_defs '
jgr@zoe:~/Documentos/sletten16maj2018-exif$ gdalsrsinfo epsg:25832 -o proj4
'+proj=utm +zone=32 +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs '
</syntaxhighlight>

== Make my own OpenDroneMap image ==

=== Fork and clone ODM repository ===

<syntaxhighlight lang="bash">
git clone git@github.com:jgrocha/OpenDroneMap.git
cd OpenDroneMap
git checkout -b generate-laz-output
</syntaxhighlight>

=== Change source ===

=== Build new image ===

<syntaxhighlight lang="bash">
jgr@zoe:~/PycharmProjects/OpenDroneMap$ docker build --no-cache -t odm_altitude_0 .
</syntaxhighlight>

<syntaxhighlight lang="bash">
docker build -t odm_laz_image .
</syntaxhighlight>

=== Run new image ===

<syntaxhighlight lang="bash">
# cd "/mnt/bonn/nextCloud/Photos/DJI MAVIC PRO 2 Paradela/100MEDIA"
cd /mnt/bonn/nextCloud/Photos
ln -s 'DJI MAVIC PRO 2 Paradela/100MEDIA' images
export odmi=`pwd`
docker run --cpus 8 -it --rm -v $odmi/images:/code/images -v $odmi/odm_orthophoto:/code/odm_orthophoto -v $odmi/odm_texturing:/code/odm_texturing -v $odmi/odm_georeferencing:/code/odm_georeferencing -v $odmi/odm_meshing:/code/odm_meshing -v $odmi/opensfm:/code/opensfm -v $odmi/odm_dem:/code/odm_dem odm_altitude_0 --dtm --dsm --force-ccd 13.2
# --orthophoto-resolution 2.0 --mesh-octree-depth 2 --opensfm-processes 8
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd /home/jgr/Documentos/sletten16maj2018-gcp
export odmi=`pwd`
sudo rm -rf odm_georeferencing odm_meshing odm_orthophoto odm_texturing opensfm
docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
odm_laz_image --gcp gcp_list.txt --dtm --dsm
</syntaxhighlight>

The options for rerunning are: 'resize', 'opensfm', 'slam', 'cmvs', 'pmvs', 'odm_meshing', 'mvs_texturing', 'odm_georeferencing', 'odm_orthophoto'

<syntaxhighlight lang="bash">
docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
odm_laz_image --gcp gcp_list.txt --dtm --dsm --rerun-from odm_georeferencing
</syntaxhighlight>

=== Check the output ===

<syntaxhighlight lang="text">
running /code/build/bin/odm_georef -bundleFile /code/opensfm/bundle_r000.out -imagesPath /code/images -imagesListPath /code/opensfm/list_r000.out -inputFile /code/odm_texturing/odm_textured_model.obj -outputFile /code/odm_texturing/odm_textured_model_geo.obj -inputPointCloudFile /code/opensfm/depthmaps/merged.ply -outputPointCloudFile /code/odm_georeferencing/odm_georeferenced_model.ply -logFile /code/odm_georeferencing/odm_georeferencing_log.txt -outputTransformFile /code/odm_georeferencing/odm_georeferencing_transform.txt -georefFileOutputPath /code/odm_georeferencing/odm_georeferencing_model_geo.txt -gcpFile gcp_list.txt -outputCoordFile /code/odm_georeferencing/coords.txt
[DEBUG] running /code/SuperBuild/build/pdal/bin/pdal pipeline -i /code/odm_georeferencing/las.json --readers.ply.filename=/code/odm_georeferencing/odm_georeferenced_model.ply
PDAL: writers.las: Can't write LAZ output. PDAL not built with LASzip or LAZperf.
</syntaxhighlight>

<syntaxhighlight lang="json">
{
"pipeline": [
"untransformed.ply",
{
"type": "writers.las",
"a_srs": "+proj=utm +zone=33 +datum=WGS84 +units=m +no_defs ",
"offset_x": "334230.28164",
"offset_y": "6208095.41529",
"offset_z": "0",
"compression": "laszip",
"filename": "/code/odm_georeferencing/odm_georeferenced_model.laz"
}
]
}
</syntaxhighlight>

[[File:Captura de ecrã de 2018-06-17 14-34-10.png]]

=== Local pdal+LASzip ===

Build from source!

<syntaxhighlight lang="bash">
/usr/local/bin/pdal pipeline -i las.json --readers.ply.filename=odm_georeferenced_model.ply
-rw-r--r-- 1 jgr jgr 22661583 jun 17 11:47 odm_georeferenced_model.laz
-rw-r--r-- 1 jgr jgr 121586206 jun 17 11:42 odm_georeferenced_model.ply
</syntaxhighlight>

==== Previous result ====

[[File:Captura de ecrã de 2018-06-16 12-26-36.png]]

==== New result ====

=== Create Pull Request ===

close #845

=== Other fixes ===

epsg versus EPSG

== Point cloud classification ==

[DEBUG] running pdal info --boundary --filters.hexbin.edge_length=1 --filters.hexbin.threshold=0 /code/odm_georeferencing/odm_georeferenced_model.filtered.las > /code/odm_georeferencing/odm_georeferenced_model.boundary.json
PDAL: Argument references invalid/unused stage: 'filters.hexbin'.

Running OpenDroneMap

2019-02-03T18:04:45Z

Jgrocha: /* Drone Workshop */

=== Drone Workshop ===

1. Flight

2. Data products

2.1 Orthophoto

Discussion: GCP, impact on the elevation model

Swipe tool

Point value: check ortho values

2.2 DEM/DSM

Discussion: difference between

Raster value

Profile tool

Visualization: hillshade

http://plas.io/

https://pdal.io/tutorial/pcl_ground/index.html#pcl-ground

<syntaxhighlight lang="bash">
-- original
pdal translate -i /code/odm_georeferencing/odm_georeferenced_model.laz -o /code/odm_georeferencing/odm_georeferenced_model.laz smrf --filters.smrf.cell=2 --filters.smrf.slope=10 --filters.smrf.window=10

-- VERY GOOD
pdal translate -i odm_georeferencing/odm_georeferenced_model.ply -o odm_georeferencing/odm_georeferenced_model_2.laz smrf --filters.smrf.cell=2 --filters.smrf.window=10

-- good
pdal ground -i odm_georeferencing/odm_georeferenced_model.ply -o odm_georeferencing/odm_georeferenced_model_3.laz
</syntaxhighlight>

2.3 Point cloud

What we get from the software

Visualization tools

3. Processing data products

3.1 Better classification

lasground

3.2 lasheight

3.3 lasclassify

=== DJI Mavic 2 PRO ===

[https://forum.dji.com/thread-167017-1-1.html Sensor size], [https://www.youtube.com/watch?v=xIncVCe6pg0 Video about sensor size]

==== Erro ====

Culpado: <syntaxhighlight lang="bash" inline>/home/jgr/PycharmProjects/OpenDroneMap/modules/odm_extract_utm</syntaxhighlight>

Todas as imagens estão com Exif.GPSInfo.GPSAltitude = 0.0

<syntaxhighlight lang="bash">
if (lon == 0.0 || lat == 0.0 || alt == 0.0) {
std::string error("Failed parsing GPS position for " + imageFilename);
throw UtmExtractorException(error);
}
</syntaxhighlight>

==== Remendo ====

<syntaxhighlight lang="bash">
exiv2 -pa DJI_0210.JPG
Exif.GPSInfo.GPSAltitude Rational 1 0.0 m

exiv2 -M"set Exif.GPSInfo.GPSAltitude Rational 1/10" DJI_0210.JPG
exiv2 -pa DJI_0210.JPG
Exif.GPSInfo.GPSAltitude Rational 1 0.1 m
</syntaxhighlight>

Chamada:

<syntaxhighlight lang="bash">
[INFO] Wrote images database: /code/images.json
[INFO] Found 106 usable images
[DEBUG] running /code/build/bin/odm_extract_utm -imagesPath /code/images/ -imageListFile /code/img_list.txt -outputCoordFile /code/odm_georeferencing/coords.txt -logFile /code/odm_georeferencing/odm_georeferencing_utm_log.txt
Error in OdmExtractUtm:
Failed parsing GPS position for DJI_0301.JPG
For more detailed information, see log file.
</syntaxhighlight>

<syntaxhighlight lang="text">
[INFO] Found 106 usable images
[WARNING] Could not generate coordinates file. Ignore if there is a GCP file. Error: Error in OdmExtractUtm:
Failed parsing GPS position for DJI_0301.JPG
For more detailed information, see log file.

(...)

Building objmodel:
Saving model... done.
Whole texturing procedure took: 225.586s
[INFO] Running ODM Texturing Cell - Finished
[INFO] Running ODM Georeferencing Cell
[WARNING] Georeferencing failed. Make sure your photos have geotags in the EXIF or you have provided a GCP file.
[INFO] Running ODM Georeferencing Cell - Finished
[INFO] Running ODM DEM Cell
[INFO] Classify: True
[INFO] Create DSM: True
[INFO] Create DTM: True
[INFO] DEM input file /code/odm_georeferencing/odm_georeferenced_model.las found: False
[WARNING] DEM will not be generated
[INFO] Running ODM DEM Cell - Finished
[INFO] Running ODM Orthophoto Cell
[DEBUG] running /code/build/bin/odm_orthophoto -inputFile /code/odm_texturing/odm_textured_model.obj -logFile /code/odm_orthophoto/odm_orthophoto_log.txt -outputFile /code/odm_orthophoto/odm_orthophoto.png -resolution 10.0 -outputCornerFile /code/odm_orthophoto/odm_orthophoto_corners.txt
[WARNING] No geo-referenced orthophoto created due to missing geo-referencing or corner coordinates.
[INFO] Running ODM OrthoPhoto Cell - Finished
[INFO] OpenDroneMap app finished - Sat Dec 29 22:12:22 2018
</syntaxhighlight>

=== Running docker OpenDroneMap ===

==== Update to last OpenDroneMap docker image ====

<syntaxhighlight lang="bash">
docker pull opendronemap/opendronemap
</syntaxhighlight>

==== OpenDroneMap docker image ====

# Install docker
# Add you user to docker group
# sudo -H pip install requests

<syntaxhighlight lang="bash">
mkdir OpenDroneMap
cd OpenDroneMap
git clone git@github.com:OpenDroneMap/odm_data_aukerman.git
cd odm_data_aukerman

export odmi=`pwd`
ls -l $odmi

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd /home/jgr/Documentos/sletten16maj2018-gcp
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
opendronemap/opendronemap --gcp gcp_list.txt --dtm --dsm
</syntaxhighlight>

Sem GCP:

<syntaxhighlight lang="bash">
cd ~/Documentos/costanovadoprado/
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm --orthophoto-resolution 10.0
</syntaxhighlight>

Nota: os ortos estão a ficar com muitas interferências do modelo 3D, nas áreas urbanas.

Related problem: http://community.opendronemap.org/t/buildings/929

Será que voar com a câmara a 75 graus ajuda? Fiz um voo com Double Grid, com a camara a 70 graus (default do Pix4d capture).

==== Windows ====

Install Docker

Configure docker (more CPU, more memory)

CPUs: 6

Memory: 12032 Mb

Swap: 4096 Mb

Create the projet folder structure

Project folder:
c:\Users\dlt265\Documents\uav_sckovskolen_feb20018_incl_GCP\

Image folder:
c:\Users\dlt265\Documents\uav_sckovskolen_feb20018_incl_GCP\images

Create folders for the OpenDroneMap output.

<syntaxhighlight lang="bash">
cd Documents\uav_sckovskolen_feb20018_incl_GCP
md odm_orthophoto
md odm_texturing
md odm_georeferencing
md odm_meshing
md opensfm
md odm_dem
</syntaxhighlight>

<syntaxhighlight lang="bash">
docker run -it --rm -v $pwd/images:/code/images -v $pwd/odm_orthophoto:/code/odm_orthophoto -v $pwd/odm_texturing:/code/odm_texturing -v $pwd/odm_georeferencing:/code/odm_georeferencing -v $pwd/odm_meshing:/code/odm_meshing -v $pwd/opensfm:/code/opensfm -v $pwd/odm_dem:/code/odm_dem opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd ~/Documentos/costanovadoprado2xgrid
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm --orthophoto-resolution 10.0 --mesh-octree-depth 10
</syntaxhighlight>

=== OpenSFM viewer (update) ===

<syntaxhighlight lang="bash">
sudo chown -R jgr:jgr *
git clone https://github.com/mapillary/OpenSfM.git
cd OpenSfM/viewer
ln -s ../../images .
python2 -m SimpleHTTPServer 7777
</syntaxhighlight>

=== OpenSFM viewer ===

<syntaxhighlight lang="bash">
jgr@zoe:~/Documentos/costanovadoprado$ sudo chown -R jgr:jgr *
jgr@zoe:~/Documentos/costanovadoprado$ cp -r ~/dev/OpenSfM/viewer opensfm
jgr@zoe:~/Documentos/costanovadoprado$ cd opensfm/
jgr@zoe:~/Documentos/costanovadoprado/opensfm$ ln -s ../images .
jgr@zoe:~/Documentos/costanovadoprado/opensfm$ python -m SimpleHTTPServer
Serving HTTP on 0.0.0.0 port 8000 ...
</syntaxhighlight>

http://localhost:8000/viewer/reconstruction.html#file=/reconstruction.json

==== OpenSFM view images on QGIS ====

/home/jgr/Documentos/costanovadoprado/images/DJI_0595.JPG

-8.7515052, 40.6114774, 22.4100000, 2018:08:23 10:05:11

/home/jgr/Documentos/costanovadoprado/opensfm/reference_lla.json

Centro aproximado do ortophoto resultante (adicionado ao projeto QGIS)

<syntaxhighlight lang="json">
{
"latitude": 40.61272372901514,
"altitude": 0,
"longitude": -8.752983409509966
}
</syntaxhighlight>

<syntaxhighlight lang="json">
"DJI_0595.JPG": {
"orientation": 1,
"camera": "v2 dji fc220 4000 3000 perspective 0.7222",
"gps_position": [
125.10012061257521,
-138.4010433354888,
22.407269606366754
],
"gps_dop": 15.0,
"rotation": [
2.1445873611073996,
-2.2856282209697523,
0.20066193557381898
],
"translation": [
-132.67853610360638,
133.40968771622724,
1.9668907291333997
],
"capture_time": 1535018711.0
},
</syntaxhighlight>

https://github.com/mapillary/OpenSfM/blob/master/opensfm/commands/export_geocoords.py

jgr@zoe:~/Documentos/costanovadoprado/opensfm$ wget https://raw.githubusercontent.com/mapillary/OpenSfM/master/opensfm/commands/export_geocoords.py

NÃO FUNCIONOU...

export_geocoords.py -dataset costanova

Ver: https://github.com/mapillary/OpenSfM/issues/183

=== webODM ===

https://github.com/OpenDroneMap/WebODM

<syntaxhighlight lang="bash">
git clone https://github.com/OpenDroneMap/WebODM --config core.autocrlf=input
cd WebODM
./webodm.sh start
</syntaxhighlight>

jgrocha/xxbatata

=== Tools ===

CloudCompare

QGIS Plugin Photo2Shape

Criar uma shapefile photos

Nas propriedades, no campo <syntaxhighlight inline lang="bash">filepath</syntaxhighlight> mudar para o tipo Fotografia.

=== Ground Control File ===

<syntaxhighlight lang="bash">
echo -7.778152 41.833203 957.575989 | cs2cs +init=epsg:4326 +to +init=epsg:3763
echo 708610.702 6209972.025 26.085 | cs2cs +init=epsg:25832 +to +init=epsg:32633

jgr@zoe:~/Documentos/sletten16maj2018-exif$ gdalsrsinfo epsg:32633 -o proj4
'+proj=utm +zone=33 +datum=WGS84 +units=m +no_defs '
jgr@zoe:~/Documentos/sletten16maj2018-exif$ gdalsrsinfo epsg:25832 -o proj4
'+proj=utm +zone=32 +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs '
</syntaxhighlight>

== Make my own OpenDroneMap image ==

=== Fork and clone ODM repository ===

<syntaxhighlight lang="bash">
git clone git@github.com:jgrocha/OpenDroneMap.git
cd OpenDroneMap
git checkout -b generate-laz-output
</syntaxhighlight>

=== Change source ===

=== Build new image ===

<syntaxhighlight lang="bash">
jgr@zoe:~/PycharmProjects/OpenDroneMap$ docker build --no-cache -t odm_altitude_0 .
</syntaxhighlight>

<syntaxhighlight lang="bash">
docker build -t odm_laz_image .
</syntaxhighlight>

=== Run new image ===

<syntaxhighlight lang="bash">
# cd "/mnt/bonn/nextCloud/Photos/DJI MAVIC PRO 2 Paradela/100MEDIA"
cd /mnt/bonn/nextCloud/Photos
ln -s 'DJI MAVIC PRO 2 Paradela/100MEDIA' images
export odmi=`pwd`
docker run --cpus 8 -it --rm -v $odmi/images:/code/images -v $odmi/odm_orthophoto:/code/odm_orthophoto -v $odmi/odm_texturing:/code/odm_texturing -v $odmi/odm_georeferencing:/code/odm_georeferencing -v $odmi/odm_meshing:/code/odm_meshing -v $odmi/opensfm:/code/opensfm -v $odmi/odm_dem:/code/odm_dem odm_altitude_0 --dtm --dsm --force-ccd 13.2
# --orthophoto-resolution 2.0 --mesh-octree-depth 2 --opensfm-processes 8
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd /home/jgr/Documentos/sletten16maj2018-gcp
export odmi=`pwd`
sudo rm -rf odm_georeferencing odm_meshing odm_orthophoto odm_texturing opensfm
docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
odm_laz_image --gcp gcp_list.txt --dtm --dsm
</syntaxhighlight>

The options for rerunning are: 'resize', 'opensfm', 'slam', 'cmvs', 'pmvs', 'odm_meshing', 'mvs_texturing', 'odm_georeferencing', 'odm_orthophoto'

<syntaxhighlight lang="bash">
docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
odm_laz_image --gcp gcp_list.txt --dtm --dsm --rerun-from odm_georeferencing
</syntaxhighlight>

=== Check the output ===

<syntaxhighlight lang="text">
running /code/build/bin/odm_georef -bundleFile /code/opensfm/bundle_r000.out -imagesPath /code/images -imagesListPath /code/opensfm/list_r000.out -inputFile /code/odm_texturing/odm_textured_model.obj -outputFile /code/odm_texturing/odm_textured_model_geo.obj -inputPointCloudFile /code/opensfm/depthmaps/merged.ply -outputPointCloudFile /code/odm_georeferencing/odm_georeferenced_model.ply -logFile /code/odm_georeferencing/odm_georeferencing_log.txt -outputTransformFile /code/odm_georeferencing/odm_georeferencing_transform.txt -georefFileOutputPath /code/odm_georeferencing/odm_georeferencing_model_geo.txt -gcpFile gcp_list.txt -outputCoordFile /code/odm_georeferencing/coords.txt
[DEBUG] running /code/SuperBuild/build/pdal/bin/pdal pipeline -i /code/odm_georeferencing/las.json --readers.ply.filename=/code/odm_georeferencing/odm_georeferenced_model.ply
PDAL: writers.las: Can't write LAZ output. PDAL not built with LASzip or LAZperf.
</syntaxhighlight>

<syntaxhighlight lang="json">
{
"pipeline": [
"untransformed.ply",
{
"type": "writers.las",
"a_srs": "+proj=utm +zone=33 +datum=WGS84 +units=m +no_defs ",
"offset_x": "334230.28164",
"offset_y": "6208095.41529",
"offset_z": "0",
"compression": "laszip",
"filename": "/code/odm_georeferencing/odm_georeferenced_model.laz"
}
]
}
</syntaxhighlight>

[[File:Captura de ecrã de 2018-06-17 14-34-10.png]]

=== Local pdal+LASzip ===

Build from source!

<syntaxhighlight lang="bash">
/usr/local/bin/pdal pipeline -i las.json --readers.ply.filename=odm_georeferenced_model.ply
-rw-r--r-- 1 jgr jgr 22661583 jun 17 11:47 odm_georeferenced_model.laz
-rw-r--r-- 1 jgr jgr 121586206 jun 17 11:42 odm_georeferenced_model.ply
</syntaxhighlight>

==== Previous result ====

[[File:Captura de ecrã de 2018-06-16 12-26-36.png]]

==== New result ====

=== Create Pull Request ===

close #845

=== Other fixes ===

epsg versus EPSG

== Point cloud classification ==

[DEBUG] running pdal info --boundary --filters.hexbin.edge_length=1 --filters.hexbin.threshold=0 /code/odm_georeferencing/odm_georeferenced_model.filtered.las > /code/odm_georeferencing/odm_georeferenced_model.boundary.json
PDAL: Argument references invalid/unused stage: 'filters.hexbin'.

Running OpenDroneMap

2019-02-03T17:59:00Z

Jgrocha: /* Drone Workshop */

=== Drone Workshop ===

1. Flight

2. Data products

2.1 Orthophoto

Discussion: GCP, impact on the elevation model

Swipe tool

Point value: check ortho values

2.2 DEM/DSM

Discussion: difference between

Raster value

Profile tool

Visualization: hillshade

http://plas.io/

https://pdal.io/tutorial/pcl_ground/index.html#pcl-ground

<syntaxhighlight lang="bash">
-- original
pdal translate -i /code/odm_georeferencing/odm_georeferenced_model.laz -o /code/odm_georeferencing/odm_georeferenced_model.laz smrf --filters.smrf.cell=2 --filters.smrf.slope=10 --filters.smrf.window=10

-- testing: not working! The original odm_georeferenced_model.laz is lost
pdal translate -i odm_georeferencing/odm_georeferenced_model.ply -o odm_georeferencing/odm_georeferenced_model_2.laz smrf --filters.smrf.cell=2 --filters.smrf.window=10

pdal ground -i odm_georeferencing/odm_georeferenced_model.ply -o odm_georeferencing/odm_georeferenced_model_3.laz
</syntaxhighlight>

2.3 Point cloud

What we get from the software

Visualization tools

3. Processing data products

3.1 Better classification

lasground

3.2 lasheight

3.3 lasclassify

=== DJI Mavic 2 PRO ===

[https://forum.dji.com/thread-167017-1-1.html Sensor size], [https://www.youtube.com/watch?v=xIncVCe6pg0 Video about sensor size]

==== Erro ====

Culpado: <syntaxhighlight lang="bash" inline>/home/jgr/PycharmProjects/OpenDroneMap/modules/odm_extract_utm</syntaxhighlight>

Todas as imagens estão com Exif.GPSInfo.GPSAltitude = 0.0

<syntaxhighlight lang="bash">
if (lon == 0.0 || lat == 0.0 || alt == 0.0) {
std::string error("Failed parsing GPS position for " + imageFilename);
throw UtmExtractorException(error);
}
</syntaxhighlight>

==== Remendo ====

<syntaxhighlight lang="bash">
exiv2 -pa DJI_0210.JPG
Exif.GPSInfo.GPSAltitude Rational 1 0.0 m

exiv2 -M"set Exif.GPSInfo.GPSAltitude Rational 1/10" DJI_0210.JPG
exiv2 -pa DJI_0210.JPG
Exif.GPSInfo.GPSAltitude Rational 1 0.1 m
</syntaxhighlight>

Chamada:

<syntaxhighlight lang="bash">
[INFO] Wrote images database: /code/images.json
[INFO] Found 106 usable images
[DEBUG] running /code/build/bin/odm_extract_utm -imagesPath /code/images/ -imageListFile /code/img_list.txt -outputCoordFile /code/odm_georeferencing/coords.txt -logFile /code/odm_georeferencing/odm_georeferencing_utm_log.txt
Error in OdmExtractUtm:
Failed parsing GPS position for DJI_0301.JPG
For more detailed information, see log file.
</syntaxhighlight>

<syntaxhighlight lang="text">
[INFO] Found 106 usable images
[WARNING] Could not generate coordinates file. Ignore if there is a GCP file. Error: Error in OdmExtractUtm:
Failed parsing GPS position for DJI_0301.JPG
For more detailed information, see log file.

(...)

Building objmodel:
Saving model... done.
Whole texturing procedure took: 225.586s
[INFO] Running ODM Texturing Cell - Finished
[INFO] Running ODM Georeferencing Cell
[WARNING] Georeferencing failed. Make sure your photos have geotags in the EXIF or you have provided a GCP file.
[INFO] Running ODM Georeferencing Cell - Finished
[INFO] Running ODM DEM Cell
[INFO] Classify: True
[INFO] Create DSM: True
[INFO] Create DTM: True
[INFO] DEM input file /code/odm_georeferencing/odm_georeferenced_model.las found: False
[WARNING] DEM will not be generated
[INFO] Running ODM DEM Cell - Finished
[INFO] Running ODM Orthophoto Cell
[DEBUG] running /code/build/bin/odm_orthophoto -inputFile /code/odm_texturing/odm_textured_model.obj -logFile /code/odm_orthophoto/odm_orthophoto_log.txt -outputFile /code/odm_orthophoto/odm_orthophoto.png -resolution 10.0 -outputCornerFile /code/odm_orthophoto/odm_orthophoto_corners.txt
[WARNING] No geo-referenced orthophoto created due to missing geo-referencing or corner coordinates.
[INFO] Running ODM OrthoPhoto Cell - Finished
[INFO] OpenDroneMap app finished - Sat Dec 29 22:12:22 2018
</syntaxhighlight>

=== Running docker OpenDroneMap ===

==== Update to last OpenDroneMap docker image ====

<syntaxhighlight lang="bash">
docker pull opendronemap/opendronemap
</syntaxhighlight>

==== OpenDroneMap docker image ====

# Install docker
# Add you user to docker group
# sudo -H pip install requests

<syntaxhighlight lang="bash">
mkdir OpenDroneMap
cd OpenDroneMap
git clone git@github.com:OpenDroneMap/odm_data_aukerman.git
cd odm_data_aukerman

export odmi=`pwd`
ls -l $odmi

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd /home/jgr/Documentos/sletten16maj2018-gcp
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
opendronemap/opendronemap --gcp gcp_list.txt --dtm --dsm
</syntaxhighlight>

Sem GCP:

<syntaxhighlight lang="bash">
cd ~/Documentos/costanovadoprado/
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm --orthophoto-resolution 10.0
</syntaxhighlight>

Nota: os ortos estão a ficar com muitas interferências do modelo 3D, nas áreas urbanas.

Related problem: http://community.opendronemap.org/t/buildings/929

Será que voar com a câmara a 75 graus ajuda? Fiz um voo com Double Grid, com a camara a 70 graus (default do Pix4d capture).

==== Windows ====

Install Docker

Configure docker (more CPU, more memory)

CPUs: 6

Memory: 12032 Mb

Swap: 4096 Mb

Create the projet folder structure

Project folder:
c:\Users\dlt265\Documents\uav_sckovskolen_feb20018_incl_GCP\

Image folder:
c:\Users\dlt265\Documents\uav_sckovskolen_feb20018_incl_GCP\images

Create folders for the OpenDroneMap output.

<syntaxhighlight lang="bash">
cd Documents\uav_sckovskolen_feb20018_incl_GCP
md odm_orthophoto
md odm_texturing
md odm_georeferencing
md odm_meshing
md opensfm
md odm_dem
</syntaxhighlight>

<syntaxhighlight lang="bash">
docker run -it --rm -v $pwd/images:/code/images -v $pwd/odm_orthophoto:/code/odm_orthophoto -v $pwd/odm_texturing:/code/odm_texturing -v $pwd/odm_georeferencing:/code/odm_georeferencing -v $pwd/odm_meshing:/code/odm_meshing -v $pwd/opensfm:/code/opensfm -v $pwd/odm_dem:/code/odm_dem opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd ~/Documentos/costanovadoprado2xgrid
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm --orthophoto-resolution 10.0 --mesh-octree-depth 10
</syntaxhighlight>

=== OpenSFM viewer (update) ===

<syntaxhighlight lang="bash">
sudo chown -R jgr:jgr *
git clone https://github.com/mapillary/OpenSfM.git
cd OpenSfM/viewer
ln -s ../../images .
python2 -m SimpleHTTPServer 7777
</syntaxhighlight>

=== OpenSFM viewer ===

<syntaxhighlight lang="bash">
jgr@zoe:~/Documentos/costanovadoprado$ sudo chown -R jgr:jgr *
jgr@zoe:~/Documentos/costanovadoprado$ cp -r ~/dev/OpenSfM/viewer opensfm
jgr@zoe:~/Documentos/costanovadoprado$ cd opensfm/
jgr@zoe:~/Documentos/costanovadoprado/opensfm$ ln -s ../images .
jgr@zoe:~/Documentos/costanovadoprado/opensfm$ python -m SimpleHTTPServer
Serving HTTP on 0.0.0.0 port 8000 ...
</syntaxhighlight>

http://localhost:8000/viewer/reconstruction.html#file=/reconstruction.json

==== OpenSFM view images on QGIS ====

/home/jgr/Documentos/costanovadoprado/images/DJI_0595.JPG

-8.7515052, 40.6114774, 22.4100000, 2018:08:23 10:05:11

/home/jgr/Documentos/costanovadoprado/opensfm/reference_lla.json

Centro aproximado do ortophoto resultante (adicionado ao projeto QGIS)

<syntaxhighlight lang="json">
{
"latitude": 40.61272372901514,
"altitude": 0,
"longitude": -8.752983409509966
}
</syntaxhighlight>

<syntaxhighlight lang="json">
"DJI_0595.JPG": {
"orientation": 1,
"camera": "v2 dji fc220 4000 3000 perspective 0.7222",
"gps_position": [
125.10012061257521,
-138.4010433354888,
22.407269606366754
],
"gps_dop": 15.0,
"rotation": [
2.1445873611073996,
-2.2856282209697523,
0.20066193557381898
],
"translation": [
-132.67853610360638,
133.40968771622724,
1.9668907291333997
],
"capture_time": 1535018711.0
},
</syntaxhighlight>

https://github.com/mapillary/OpenSfM/blob/master/opensfm/commands/export_geocoords.py

jgr@zoe:~/Documentos/costanovadoprado/opensfm$ wget https://raw.githubusercontent.com/mapillary/OpenSfM/master/opensfm/commands/export_geocoords.py

NÃO FUNCIONOU...

export_geocoords.py -dataset costanova

Ver: https://github.com/mapillary/OpenSfM/issues/183

=== webODM ===

https://github.com/OpenDroneMap/WebODM

<syntaxhighlight lang="bash">
git clone https://github.com/OpenDroneMap/WebODM --config core.autocrlf=input
cd WebODM
./webodm.sh start
</syntaxhighlight>

jgrocha/xxbatata

=== Tools ===

CloudCompare

QGIS Plugin Photo2Shape

Criar uma shapefile photos

Nas propriedades, no campo <syntaxhighlight inline lang="bash">filepath</syntaxhighlight> mudar para o tipo Fotografia.

=== Ground Control File ===

<syntaxhighlight lang="bash">
echo -7.778152 41.833203 957.575989 | cs2cs +init=epsg:4326 +to +init=epsg:3763
echo 708610.702 6209972.025 26.085 | cs2cs +init=epsg:25832 +to +init=epsg:32633

jgr@zoe:~/Documentos/sletten16maj2018-exif$ gdalsrsinfo epsg:32633 -o proj4
'+proj=utm +zone=33 +datum=WGS84 +units=m +no_defs '
jgr@zoe:~/Documentos/sletten16maj2018-exif$ gdalsrsinfo epsg:25832 -o proj4
'+proj=utm +zone=32 +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs '
</syntaxhighlight>

== Make my own OpenDroneMap image ==

=== Fork and clone ODM repository ===

<syntaxhighlight lang="bash">
git clone git@github.com:jgrocha/OpenDroneMap.git
cd OpenDroneMap
git checkout -b generate-laz-output
</syntaxhighlight>

=== Change source ===

=== Build new image ===

<syntaxhighlight lang="bash">
jgr@zoe:~/PycharmProjects/OpenDroneMap$ docker build --no-cache -t odm_altitude_0 .
</syntaxhighlight>

<syntaxhighlight lang="bash">
docker build -t odm_laz_image .
</syntaxhighlight>

=== Run new image ===

<syntaxhighlight lang="bash">
# cd "/mnt/bonn/nextCloud/Photos/DJI MAVIC PRO 2 Paradela/100MEDIA"
cd /mnt/bonn/nextCloud/Photos
ln -s 'DJI MAVIC PRO 2 Paradela/100MEDIA' images
export odmi=`pwd`
docker run --cpus 8 -it --rm -v $odmi/images:/code/images -v $odmi/odm_orthophoto:/code/odm_orthophoto -v $odmi/odm_texturing:/code/odm_texturing -v $odmi/odm_georeferencing:/code/odm_georeferencing -v $odmi/odm_meshing:/code/odm_meshing -v $odmi/opensfm:/code/opensfm -v $odmi/odm_dem:/code/odm_dem odm_altitude_0 --dtm --dsm --force-ccd 13.2
# --orthophoto-resolution 2.0 --mesh-octree-depth 2 --opensfm-processes 8
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd /home/jgr/Documentos/sletten16maj2018-gcp
export odmi=`pwd`
sudo rm -rf odm_georeferencing odm_meshing odm_orthophoto odm_texturing opensfm
docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
odm_laz_image --gcp gcp_list.txt --dtm --dsm
</syntaxhighlight>

The options for rerunning are: 'resize', 'opensfm', 'slam', 'cmvs', 'pmvs', 'odm_meshing', 'mvs_texturing', 'odm_georeferencing', 'odm_orthophoto'

<syntaxhighlight lang="bash">
docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
odm_laz_image --gcp gcp_list.txt --dtm --dsm --rerun-from odm_georeferencing
</syntaxhighlight>

=== Check the output ===

<syntaxhighlight lang="text">
running /code/build/bin/odm_georef -bundleFile /code/opensfm/bundle_r000.out -imagesPath /code/images -imagesListPath /code/opensfm/list_r000.out -inputFile /code/odm_texturing/odm_textured_model.obj -outputFile /code/odm_texturing/odm_textured_model_geo.obj -inputPointCloudFile /code/opensfm/depthmaps/merged.ply -outputPointCloudFile /code/odm_georeferencing/odm_georeferenced_model.ply -logFile /code/odm_georeferencing/odm_georeferencing_log.txt -outputTransformFile /code/odm_georeferencing/odm_georeferencing_transform.txt -georefFileOutputPath /code/odm_georeferencing/odm_georeferencing_model_geo.txt -gcpFile gcp_list.txt -outputCoordFile /code/odm_georeferencing/coords.txt
[DEBUG] running /code/SuperBuild/build/pdal/bin/pdal pipeline -i /code/odm_georeferencing/las.json --readers.ply.filename=/code/odm_georeferencing/odm_georeferenced_model.ply
PDAL: writers.las: Can't write LAZ output. PDAL not built with LASzip or LAZperf.
</syntaxhighlight>

<syntaxhighlight lang="json">
{
"pipeline": [
"untransformed.ply",
{
"type": "writers.las",
"a_srs": "+proj=utm +zone=33 +datum=WGS84 +units=m +no_defs ",
"offset_x": "334230.28164",
"offset_y": "6208095.41529",
"offset_z": "0",
"compression": "laszip",
"filename": "/code/odm_georeferencing/odm_georeferenced_model.laz"
}
]
}
</syntaxhighlight>

[[File:Captura de ecrã de 2018-06-17 14-34-10.png]]

=== Local pdal+LASzip ===

Build from source!

<syntaxhighlight lang="bash">
/usr/local/bin/pdal pipeline -i las.json --readers.ply.filename=odm_georeferenced_model.ply
-rw-r--r-- 1 jgr jgr 22661583 jun 17 11:47 odm_georeferenced_model.laz
-rw-r--r-- 1 jgr jgr 121586206 jun 17 11:42 odm_georeferenced_model.ply
</syntaxhighlight>

==== Previous result ====

[[File:Captura de ecrã de 2018-06-16 12-26-36.png]]

==== New result ====

=== Create Pull Request ===

close #845

=== Other fixes ===

epsg versus EPSG

== Point cloud classification ==

[DEBUG] running pdal info --boundary --filters.hexbin.edge_length=1 --filters.hexbin.threshold=0 /code/odm_georeferencing/odm_georeferenced_model.filtered.las > /code/odm_georeferencing/odm_georeferenced_model.boundary.json
PDAL: Argument references invalid/unused stage: 'filters.hexbin'.

Running OpenDroneMap

2019-02-03T17:39:21Z

Jgrocha: /* Drone Workshop */

=== Drone Workshop ===

1. Flight

2. Data products

2.1 Orthophoto

Discussion: GCP, impact on the elevation model

Swipe tool

Point value: check ortho values

2.2 DEM/DSM

Discussion: difference between

Raster value

Profile tool

Visualization: hillshade

<syntaxhighlight lang="bash">
-- original
pdal translate -i /code/odm_georeferencing/odm_georeferenced_model.laz -o /code/odm_georeferencing/odm_georeferenced_model.laz smrf --filters.smrf.cell=2 --filters.smrf.slope=10 --filters.smrf.window=10

-- testing: not working! The original odm_georeferenced_model.laz is lost
pdal translate -i odm_georeferencing/odm_georeferenced_model.laz -o odm_georeferencing/odm_georeferenced_model.laz smrf --filters.smrf.cell=2 --filters.smrf.slope=10 --filters.smrf.window=10
</syntaxhighlight>

2.3 Point cloud

What we get from the software

Visualization tools

3. Processing data products

3.1 Better classification

lasground

3.2 lasheight

3.3 lasclassify

=== DJI Mavic 2 PRO ===

[https://forum.dji.com/thread-167017-1-1.html Sensor size], [https://www.youtube.com/watch?v=xIncVCe6pg0 Video about sensor size]

==== Erro ====

Culpado: <syntaxhighlight lang="bash" inline>/home/jgr/PycharmProjects/OpenDroneMap/modules/odm_extract_utm</syntaxhighlight>

Todas as imagens estão com Exif.GPSInfo.GPSAltitude = 0.0

<syntaxhighlight lang="bash">
if (lon == 0.0 || lat == 0.0 || alt == 0.0) {
std::string error("Failed parsing GPS position for " + imageFilename);
throw UtmExtractorException(error);
}
</syntaxhighlight>

==== Remendo ====

<syntaxhighlight lang="bash">
exiv2 -pa DJI_0210.JPG
Exif.GPSInfo.GPSAltitude Rational 1 0.0 m

exiv2 -M"set Exif.GPSInfo.GPSAltitude Rational 1/10" DJI_0210.JPG
exiv2 -pa DJI_0210.JPG
Exif.GPSInfo.GPSAltitude Rational 1 0.1 m
</syntaxhighlight>

Chamada:

<syntaxhighlight lang="bash">
[INFO] Wrote images database: /code/images.json
[INFO] Found 106 usable images
[DEBUG] running /code/build/bin/odm_extract_utm -imagesPath /code/images/ -imageListFile /code/img_list.txt -outputCoordFile /code/odm_georeferencing/coords.txt -logFile /code/odm_georeferencing/odm_georeferencing_utm_log.txt
Error in OdmExtractUtm:
Failed parsing GPS position for DJI_0301.JPG
For more detailed information, see log file.
</syntaxhighlight>

<syntaxhighlight lang="text">
[INFO] Found 106 usable images
[WARNING] Could not generate coordinates file. Ignore if there is a GCP file. Error: Error in OdmExtractUtm:
Failed parsing GPS position for DJI_0301.JPG
For more detailed information, see log file.

(...)

Building objmodel:
Saving model... done.
Whole texturing procedure took: 225.586s
[INFO] Running ODM Texturing Cell - Finished
[INFO] Running ODM Georeferencing Cell
[WARNING] Georeferencing failed. Make sure your photos have geotags in the EXIF or you have provided a GCP file.
[INFO] Running ODM Georeferencing Cell - Finished
[INFO] Running ODM DEM Cell
[INFO] Classify: True
[INFO] Create DSM: True
[INFO] Create DTM: True
[INFO] DEM input file /code/odm_georeferencing/odm_georeferenced_model.las found: False
[WARNING] DEM will not be generated
[INFO] Running ODM DEM Cell - Finished
[INFO] Running ODM Orthophoto Cell
[DEBUG] running /code/build/bin/odm_orthophoto -inputFile /code/odm_texturing/odm_textured_model.obj -logFile /code/odm_orthophoto/odm_orthophoto_log.txt -outputFile /code/odm_orthophoto/odm_orthophoto.png -resolution 10.0 -outputCornerFile /code/odm_orthophoto/odm_orthophoto_corners.txt
[WARNING] No geo-referenced orthophoto created due to missing geo-referencing or corner coordinates.
[INFO] Running ODM OrthoPhoto Cell - Finished
[INFO] OpenDroneMap app finished - Sat Dec 29 22:12:22 2018
</syntaxhighlight>

=== Running docker OpenDroneMap ===

==== Update to last OpenDroneMap docker image ====

<syntaxhighlight lang="bash">
docker pull opendronemap/opendronemap
</syntaxhighlight>

==== OpenDroneMap docker image ====

# Install docker
# Add you user to docker group
# sudo -H pip install requests

<syntaxhighlight lang="bash">
mkdir OpenDroneMap
cd OpenDroneMap
git clone git@github.com:OpenDroneMap/odm_data_aukerman.git
cd odm_data_aukerman

export odmi=`pwd`
ls -l $odmi

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd /home/jgr/Documentos/sletten16maj2018-gcp
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
opendronemap/opendronemap --gcp gcp_list.txt --dtm --dsm
</syntaxhighlight>

Sem GCP:

<syntaxhighlight lang="bash">
cd ~/Documentos/costanovadoprado/
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm --orthophoto-resolution 10.0
</syntaxhighlight>

Nota: os ortos estão a ficar com muitas interferências do modelo 3D, nas áreas urbanas.

Related problem: http://community.opendronemap.org/t/buildings/929

Será que voar com a câmara a 75 graus ajuda? Fiz um voo com Double Grid, com a camara a 70 graus (default do Pix4d capture).

==== Windows ====

Install Docker

Configure docker (more CPU, more memory)

CPUs: 6

Memory: 12032 Mb

Swap: 4096 Mb

Create the projet folder structure

Project folder:
c:\Users\dlt265\Documents\uav_sckovskolen_feb20018_incl_GCP\

Image folder:
c:\Users\dlt265\Documents\uav_sckovskolen_feb20018_incl_GCP\images

Create folders for the OpenDroneMap output.

<syntaxhighlight lang="bash">
cd Documents\uav_sckovskolen_feb20018_incl_GCP
md odm_orthophoto
md odm_texturing
md odm_georeferencing
md odm_meshing
md opensfm
md odm_dem
</syntaxhighlight>

<syntaxhighlight lang="bash">
docker run -it --rm -v $pwd/images:/code/images -v $pwd/odm_orthophoto:/code/odm_orthophoto -v $pwd/odm_texturing:/code/odm_texturing -v $pwd/odm_georeferencing:/code/odm_georeferencing -v $pwd/odm_meshing:/code/odm_meshing -v $pwd/opensfm:/code/opensfm -v $pwd/odm_dem:/code/odm_dem opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd ~/Documentos/costanovadoprado2xgrid
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm --orthophoto-resolution 10.0 --mesh-octree-depth 10
</syntaxhighlight>

=== OpenSFM viewer (update) ===

<syntaxhighlight lang="bash">
sudo chown -R jgr:jgr *
git clone https://github.com/mapillary/OpenSfM.git
cd OpenSfM/viewer
ln -s ../../images .
python2 -m SimpleHTTPServer 7777
</syntaxhighlight>

=== OpenSFM viewer ===

<syntaxhighlight lang="bash">
jgr@zoe:~/Documentos/costanovadoprado$ sudo chown -R jgr:jgr *
jgr@zoe:~/Documentos/costanovadoprado$ cp -r ~/dev/OpenSfM/viewer opensfm
jgr@zoe:~/Documentos/costanovadoprado$ cd opensfm/
jgr@zoe:~/Documentos/costanovadoprado/opensfm$ ln -s ../images .
jgr@zoe:~/Documentos/costanovadoprado/opensfm$ python -m SimpleHTTPServer
Serving HTTP on 0.0.0.0 port 8000 ...
</syntaxhighlight>

http://localhost:8000/viewer/reconstruction.html#file=/reconstruction.json

==== OpenSFM view images on QGIS ====

/home/jgr/Documentos/costanovadoprado/images/DJI_0595.JPG

-8.7515052, 40.6114774, 22.4100000, 2018:08:23 10:05:11

/home/jgr/Documentos/costanovadoprado/opensfm/reference_lla.json

Centro aproximado do ortophoto resultante (adicionado ao projeto QGIS)

<syntaxhighlight lang="json">
{
"latitude": 40.61272372901514,
"altitude": 0,
"longitude": -8.752983409509966
}
</syntaxhighlight>

<syntaxhighlight lang="json">
"DJI_0595.JPG": {
"orientation": 1,
"camera": "v2 dji fc220 4000 3000 perspective 0.7222",
"gps_position": [
125.10012061257521,
-138.4010433354888,
22.407269606366754
],
"gps_dop": 15.0,
"rotation": [
2.1445873611073996,
-2.2856282209697523,
0.20066193557381898
],
"translation": [
-132.67853610360638,
133.40968771622724,
1.9668907291333997
],
"capture_time": 1535018711.0
},
</syntaxhighlight>

https://github.com/mapillary/OpenSfM/blob/master/opensfm/commands/export_geocoords.py

jgr@zoe:~/Documentos/costanovadoprado/opensfm$ wget https://raw.githubusercontent.com/mapillary/OpenSfM/master/opensfm/commands/export_geocoords.py

NÃO FUNCIONOU...

export_geocoords.py -dataset costanova

Ver: https://github.com/mapillary/OpenSfM/issues/183

=== webODM ===

https://github.com/OpenDroneMap/WebODM

<syntaxhighlight lang="bash">
git clone https://github.com/OpenDroneMap/WebODM --config core.autocrlf=input
cd WebODM
./webodm.sh start
</syntaxhighlight>

jgrocha/xxbatata

=== Tools ===

CloudCompare

QGIS Plugin Photo2Shape

Criar uma shapefile photos

Nas propriedades, no campo <syntaxhighlight inline lang="bash">filepath</syntaxhighlight> mudar para o tipo Fotografia.

=== Ground Control File ===

<syntaxhighlight lang="bash">
echo -7.778152 41.833203 957.575989 | cs2cs +init=epsg:4326 +to +init=epsg:3763
echo 708610.702 6209972.025 26.085 | cs2cs +init=epsg:25832 +to +init=epsg:32633

jgr@zoe:~/Documentos/sletten16maj2018-exif$ gdalsrsinfo epsg:32633 -o proj4
'+proj=utm +zone=33 +datum=WGS84 +units=m +no_defs '
jgr@zoe:~/Documentos/sletten16maj2018-exif$ gdalsrsinfo epsg:25832 -o proj4
'+proj=utm +zone=32 +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs '
</syntaxhighlight>

== Make my own OpenDroneMap image ==

=== Fork and clone ODM repository ===

<syntaxhighlight lang="bash">
git clone git@github.com:jgrocha/OpenDroneMap.git
cd OpenDroneMap
git checkout -b generate-laz-output
</syntaxhighlight>

=== Change source ===

=== Build new image ===

<syntaxhighlight lang="bash">
jgr@zoe:~/PycharmProjects/OpenDroneMap$ docker build --no-cache -t odm_altitude_0 .
</syntaxhighlight>

<syntaxhighlight lang="bash">
docker build -t odm_laz_image .
</syntaxhighlight>

=== Run new image ===

<syntaxhighlight lang="bash">
# cd "/mnt/bonn/nextCloud/Photos/DJI MAVIC PRO 2 Paradela/100MEDIA"
cd /mnt/bonn/nextCloud/Photos
ln -s 'DJI MAVIC PRO 2 Paradela/100MEDIA' images
export odmi=`pwd`
docker run --cpus 8 -it --rm -v $odmi/images:/code/images -v $odmi/odm_orthophoto:/code/odm_orthophoto -v $odmi/odm_texturing:/code/odm_texturing -v $odmi/odm_georeferencing:/code/odm_georeferencing -v $odmi/odm_meshing:/code/odm_meshing -v $odmi/opensfm:/code/opensfm -v $odmi/odm_dem:/code/odm_dem odm_altitude_0 --dtm --dsm --force-ccd 13.2
# --orthophoto-resolution 2.0 --mesh-octree-depth 2 --opensfm-processes 8
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd /home/jgr/Documentos/sletten16maj2018-gcp
export odmi=`pwd`
sudo rm -rf odm_georeferencing odm_meshing odm_orthophoto odm_texturing opensfm
docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
odm_laz_image --gcp gcp_list.txt --dtm --dsm
</syntaxhighlight>

The options for rerunning are: 'resize', 'opensfm', 'slam', 'cmvs', 'pmvs', 'odm_meshing', 'mvs_texturing', 'odm_georeferencing', 'odm_orthophoto'

<syntaxhighlight lang="bash">
docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
odm_laz_image --gcp gcp_list.txt --dtm --dsm --rerun-from odm_georeferencing
</syntaxhighlight>

=== Check the output ===

<syntaxhighlight lang="text">
running /code/build/bin/odm_georef -bundleFile /code/opensfm/bundle_r000.out -imagesPath /code/images -imagesListPath /code/opensfm/list_r000.out -inputFile /code/odm_texturing/odm_textured_model.obj -outputFile /code/odm_texturing/odm_textured_model_geo.obj -inputPointCloudFile /code/opensfm/depthmaps/merged.ply -outputPointCloudFile /code/odm_georeferencing/odm_georeferenced_model.ply -logFile /code/odm_georeferencing/odm_georeferencing_log.txt -outputTransformFile /code/odm_georeferencing/odm_georeferencing_transform.txt -georefFileOutputPath /code/odm_georeferencing/odm_georeferencing_model_geo.txt -gcpFile gcp_list.txt -outputCoordFile /code/odm_georeferencing/coords.txt
[DEBUG] running /code/SuperBuild/build/pdal/bin/pdal pipeline -i /code/odm_georeferencing/las.json --readers.ply.filename=/code/odm_georeferencing/odm_georeferenced_model.ply
PDAL: writers.las: Can't write LAZ output. PDAL not built with LASzip or LAZperf.
</syntaxhighlight>

<syntaxhighlight lang="json">
{
"pipeline": [
"untransformed.ply",
{
"type": "writers.las",
"a_srs": "+proj=utm +zone=33 +datum=WGS84 +units=m +no_defs ",
"offset_x": "334230.28164",
"offset_y": "6208095.41529",
"offset_z": "0",
"compression": "laszip",
"filename": "/code/odm_georeferencing/odm_georeferenced_model.laz"
}
]
}
</syntaxhighlight>

[[File:Captura de ecrã de 2018-06-17 14-34-10.png]]

=== Local pdal+LASzip ===

Build from source!

<syntaxhighlight lang="bash">
/usr/local/bin/pdal pipeline -i las.json --readers.ply.filename=odm_georeferenced_model.ply
-rw-r--r-- 1 jgr jgr 22661583 jun 17 11:47 odm_georeferenced_model.laz
-rw-r--r-- 1 jgr jgr 121586206 jun 17 11:42 odm_georeferenced_model.ply
</syntaxhighlight>

==== Previous result ====

[[File:Captura de ecrã de 2018-06-16 12-26-36.png]]

==== New result ====

=== Create Pull Request ===

close #845

=== Other fixes ===

epsg versus EPSG

== Point cloud classification ==

[DEBUG] running pdal info --boundary --filters.hexbin.edge_length=1 --filters.hexbin.threshold=0 /code/odm_georeferencing/odm_georeferenced_model.filtered.las > /code/odm_georeferencing/odm_georeferenced_model.boundary.json
PDAL: Argument references invalid/unused stage: 'filters.hexbin'.

Running OpenDroneMap

2019-02-03T17:34:14Z

Jgrocha: /* Drone Workshop */

=== Drone Workshop ===

1. Flight

2. Data products

2.1 Orthophoto

Discussion: GCP, impact on the elevation model

Swipe tool

Point value: check ortho values

2.2 DEM/DSM

Discussion: difference between

Raster value

Profile tool

Visualization: hillshade

<syntaxhighlight lang="bash">
pdal translate -i /code/odm_georeferencing/odm_georeferenced_model.laz -o /code/odm_georeferencing/odm_georeferenced_model.laz smrf --filters.smrf.cell=2 --filters.smrf.slope=10 --filters.smrf.window=10
</syntaxhighlight>

2.3 Point cloud

What we get from the software

Visualization tools

3. Processing data products

3.1 Better classification

lasground

3.2 lasheight

3.3 lasclassify

=== DJI Mavic 2 PRO ===

[https://forum.dji.com/thread-167017-1-1.html Sensor size], [https://www.youtube.com/watch?v=xIncVCe6pg0 Video about sensor size]

==== Erro ====

Culpado: <syntaxhighlight lang="bash" inline>/home/jgr/PycharmProjects/OpenDroneMap/modules/odm_extract_utm</syntaxhighlight>

Todas as imagens estão com Exif.GPSInfo.GPSAltitude = 0.0

<syntaxhighlight lang="bash">
if (lon == 0.0 || lat == 0.0 || alt == 0.0) {
std::string error("Failed parsing GPS position for " + imageFilename);
throw UtmExtractorException(error);
}
</syntaxhighlight>

==== Remendo ====

<syntaxhighlight lang="bash">
exiv2 -pa DJI_0210.JPG
Exif.GPSInfo.GPSAltitude Rational 1 0.0 m

exiv2 -M"set Exif.GPSInfo.GPSAltitude Rational 1/10" DJI_0210.JPG
exiv2 -pa DJI_0210.JPG
Exif.GPSInfo.GPSAltitude Rational 1 0.1 m
</syntaxhighlight>

Chamada:

<syntaxhighlight lang="bash">
[INFO] Wrote images database: /code/images.json
[INFO] Found 106 usable images
[DEBUG] running /code/build/bin/odm_extract_utm -imagesPath /code/images/ -imageListFile /code/img_list.txt -outputCoordFile /code/odm_georeferencing/coords.txt -logFile /code/odm_georeferencing/odm_georeferencing_utm_log.txt
Error in OdmExtractUtm:
Failed parsing GPS position for DJI_0301.JPG
For more detailed information, see log file.
</syntaxhighlight>

<syntaxhighlight lang="text">
[INFO] Found 106 usable images
[WARNING] Could not generate coordinates file. Ignore if there is a GCP file. Error: Error in OdmExtractUtm:
Failed parsing GPS position for DJI_0301.JPG
For more detailed information, see log file.

(...)

Building objmodel:
Saving model... done.
Whole texturing procedure took: 225.586s
[INFO] Running ODM Texturing Cell - Finished
[INFO] Running ODM Georeferencing Cell
[WARNING] Georeferencing failed. Make sure your photos have geotags in the EXIF or you have provided a GCP file.
[INFO] Running ODM Georeferencing Cell - Finished
[INFO] Running ODM DEM Cell
[INFO] Classify: True
[INFO] Create DSM: True
[INFO] Create DTM: True
[INFO] DEM input file /code/odm_georeferencing/odm_georeferenced_model.las found: False
[WARNING] DEM will not be generated
[INFO] Running ODM DEM Cell - Finished
[INFO] Running ODM Orthophoto Cell
[DEBUG] running /code/build/bin/odm_orthophoto -inputFile /code/odm_texturing/odm_textured_model.obj -logFile /code/odm_orthophoto/odm_orthophoto_log.txt -outputFile /code/odm_orthophoto/odm_orthophoto.png -resolution 10.0 -outputCornerFile /code/odm_orthophoto/odm_orthophoto_corners.txt
[WARNING] No geo-referenced orthophoto created due to missing geo-referencing or corner coordinates.
[INFO] Running ODM OrthoPhoto Cell - Finished
[INFO] OpenDroneMap app finished - Sat Dec 29 22:12:22 2018
</syntaxhighlight>

=== Running docker OpenDroneMap ===

==== Update to last OpenDroneMap docker image ====

<syntaxhighlight lang="bash">
docker pull opendronemap/opendronemap
</syntaxhighlight>

==== OpenDroneMap docker image ====

# Install docker
# Add you user to docker group
# sudo -H pip install requests

<syntaxhighlight lang="bash">
mkdir OpenDroneMap
cd OpenDroneMap
git clone git@github.com:OpenDroneMap/odm_data_aukerman.git
cd odm_data_aukerman

export odmi=`pwd`
ls -l $odmi

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd /home/jgr/Documentos/sletten16maj2018-gcp
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
opendronemap/opendronemap --gcp gcp_list.txt --dtm --dsm
</syntaxhighlight>

Sem GCP:

<syntaxhighlight lang="bash">
cd ~/Documentos/costanovadoprado/
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm --orthophoto-resolution 10.0
</syntaxhighlight>

Nota: os ortos estão a ficar com muitas interferências do modelo 3D, nas áreas urbanas.

Related problem: http://community.opendronemap.org/t/buildings/929

Será que voar com a câmara a 75 graus ajuda? Fiz um voo com Double Grid, com a camara a 70 graus (default do Pix4d capture).

==== Windows ====

Install Docker

Configure docker (more CPU, more memory)

CPUs: 6

Memory: 12032 Mb

Swap: 4096 Mb

Create the projet folder structure

Project folder:
c:\Users\dlt265\Documents\uav_sckovskolen_feb20018_incl_GCP\

Image folder:
c:\Users\dlt265\Documents\uav_sckovskolen_feb20018_incl_GCP\images

Create folders for the OpenDroneMap output.

<syntaxhighlight lang="bash">
cd Documents\uav_sckovskolen_feb20018_incl_GCP
md odm_orthophoto
md odm_texturing
md odm_georeferencing
md odm_meshing
md opensfm
md odm_dem
</syntaxhighlight>

<syntaxhighlight lang="bash">
docker run -it --rm -v $pwd/images:/code/images -v $pwd/odm_orthophoto:/code/odm_orthophoto -v $pwd/odm_texturing:/code/odm_texturing -v $pwd/odm_georeferencing:/code/odm_georeferencing -v $pwd/odm_meshing:/code/odm_meshing -v $pwd/opensfm:/code/opensfm -v $pwd/odm_dem:/code/odm_dem opendronemap/opendronemap --dtm --dsm
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd ~/Documentos/costanovadoprado2xgrid
export odmi=`pwd`

docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
-v $odmi/odm_dem:/code/odm_dem \
opendronemap/opendronemap --dtm --dsm --orthophoto-resolution 10.0 --mesh-octree-depth 10
</syntaxhighlight>

=== OpenSFM viewer (update) ===

<syntaxhighlight lang="bash">
sudo chown -R jgr:jgr *
git clone https://github.com/mapillary/OpenSfM.git
cd OpenSfM/viewer
ln -s ../../images .
python2 -m SimpleHTTPServer 7777
</syntaxhighlight>

=== OpenSFM viewer ===

<syntaxhighlight lang="bash">
jgr@zoe:~/Documentos/costanovadoprado$ sudo chown -R jgr:jgr *
jgr@zoe:~/Documentos/costanovadoprado$ cp -r ~/dev/OpenSfM/viewer opensfm
jgr@zoe:~/Documentos/costanovadoprado$ cd opensfm/
jgr@zoe:~/Documentos/costanovadoprado/opensfm$ ln -s ../images .
jgr@zoe:~/Documentos/costanovadoprado/opensfm$ python -m SimpleHTTPServer
Serving HTTP on 0.0.0.0 port 8000 ...
</syntaxhighlight>

http://localhost:8000/viewer/reconstruction.html#file=/reconstruction.json

==== OpenSFM view images on QGIS ====

/home/jgr/Documentos/costanovadoprado/images/DJI_0595.JPG

-8.7515052, 40.6114774, 22.4100000, 2018:08:23 10:05:11

/home/jgr/Documentos/costanovadoprado/opensfm/reference_lla.json

Centro aproximado do ortophoto resultante (adicionado ao projeto QGIS)

<syntaxhighlight lang="json">
{
"latitude": 40.61272372901514,
"altitude": 0,
"longitude": -8.752983409509966
}
</syntaxhighlight>

<syntaxhighlight lang="json">
"DJI_0595.JPG": {
"orientation": 1,
"camera": "v2 dji fc220 4000 3000 perspective 0.7222",
"gps_position": [
125.10012061257521,
-138.4010433354888,
22.407269606366754
],
"gps_dop": 15.0,
"rotation": [
2.1445873611073996,
-2.2856282209697523,
0.20066193557381898
],
"translation": [
-132.67853610360638,
133.40968771622724,
1.9668907291333997
],
"capture_time": 1535018711.0
},
</syntaxhighlight>

https://github.com/mapillary/OpenSfM/blob/master/opensfm/commands/export_geocoords.py

jgr@zoe:~/Documentos/costanovadoprado/opensfm$ wget https://raw.githubusercontent.com/mapillary/OpenSfM/master/opensfm/commands/export_geocoords.py

NÃO FUNCIONOU...

export_geocoords.py -dataset costanova

Ver: https://github.com/mapillary/OpenSfM/issues/183

=== webODM ===

https://github.com/OpenDroneMap/WebODM

<syntaxhighlight lang="bash">
git clone https://github.com/OpenDroneMap/WebODM --config core.autocrlf=input
cd WebODM
./webodm.sh start
</syntaxhighlight>

jgrocha/xxbatata

=== Tools ===

CloudCompare

QGIS Plugin Photo2Shape

Criar uma shapefile photos

Nas propriedades, no campo <syntaxhighlight inline lang="bash">filepath</syntaxhighlight> mudar para o tipo Fotografia.

=== Ground Control File ===

<syntaxhighlight lang="bash">
echo -7.778152 41.833203 957.575989 | cs2cs +init=epsg:4326 +to +init=epsg:3763
echo 708610.702 6209972.025 26.085 | cs2cs +init=epsg:25832 +to +init=epsg:32633

jgr@zoe:~/Documentos/sletten16maj2018-exif$ gdalsrsinfo epsg:32633 -o proj4
'+proj=utm +zone=33 +datum=WGS84 +units=m +no_defs '
jgr@zoe:~/Documentos/sletten16maj2018-exif$ gdalsrsinfo epsg:25832 -o proj4
'+proj=utm +zone=32 +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs '
</syntaxhighlight>

== Make my own OpenDroneMap image ==

=== Fork and clone ODM repository ===

<syntaxhighlight lang="bash">
git clone git@github.com:jgrocha/OpenDroneMap.git
cd OpenDroneMap
git checkout -b generate-laz-output
</syntaxhighlight>

=== Change source ===

=== Build new image ===

<syntaxhighlight lang="bash">
jgr@zoe:~/PycharmProjects/OpenDroneMap$ docker build --no-cache -t odm_altitude_0 .
</syntaxhighlight>

<syntaxhighlight lang="bash">
docker build -t odm_laz_image .
</syntaxhighlight>

=== Run new image ===

<syntaxhighlight lang="bash">
# cd "/mnt/bonn/nextCloud/Photos/DJI MAVIC PRO 2 Paradela/100MEDIA"
cd /mnt/bonn/nextCloud/Photos
ln -s 'DJI MAVIC PRO 2 Paradela/100MEDIA' images
export odmi=`pwd`
docker run --cpus 8 -it --rm -v $odmi/images:/code/images -v $odmi/odm_orthophoto:/code/odm_orthophoto -v $odmi/odm_texturing:/code/odm_texturing -v $odmi/odm_georeferencing:/code/odm_georeferencing -v $odmi/odm_meshing:/code/odm_meshing -v $odmi/opensfm:/code/opensfm -v $odmi/odm_dem:/code/odm_dem odm_altitude_0 --dtm --dsm --force-ccd 13.2
# --orthophoto-resolution 2.0 --mesh-octree-depth 2 --opensfm-processes 8
</syntaxhighlight>

<syntaxhighlight lang="bash">
cd /home/jgr/Documentos/sletten16maj2018-gcp
export odmi=`pwd`
sudo rm -rf odm_georeferencing odm_meshing odm_orthophoto odm_texturing opensfm
docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
odm_laz_image --gcp gcp_list.txt --dtm --dsm
</syntaxhighlight>

The options for rerunning are: 'resize', 'opensfm', 'slam', 'cmvs', 'pmvs', 'odm_meshing', 'mvs_texturing', 'odm_georeferencing', 'odm_orthophoto'

<syntaxhighlight lang="bash">
docker run -it --rm \
-v $odmi/images:/code/images \
-v $odmi/gcp_list.txt:/code/gcp_list.txt \
-v $odmi/odm_orthophoto:/code/odm_orthophoto \
-v $odmi/odm_texturing:/code/odm_texturing \
-v $odmi/odm_georeferencing:/code/odm_georeferencing \
-v $odmi/odm_meshing:/code/odm_meshing \
-v $odmi/opensfm:/code/opensfm \
odm_laz_image --gcp gcp_list.txt --dtm --dsm --rerun-from odm_georeferencing
</syntaxhighlight>

=== Check the output ===

<syntaxhighlight lang="text">
running /code/build/bin/odm_georef -bundleFile /code/opensfm/bundle_r000.out -imagesPath /code/images -imagesListPath /code/opensfm/list_r000.out -inputFile /code/odm_texturing/odm_textured_model.obj -outputFile /code/odm_texturing/odm_textured_model_geo.obj -inputPointCloudFile /code/opensfm/depthmaps/merged.ply -outputPointCloudFile /code/odm_georeferencing/odm_georeferenced_model.ply -logFile /code/odm_georeferencing/odm_georeferencing_log.txt -outputTransformFile /code/odm_georeferencing/odm_georeferencing_transform.txt -georefFileOutputPath /code/odm_georeferencing/odm_georeferencing_model_geo.txt -gcpFile gcp_list.txt -outputCoordFile /code/odm_georeferencing/coords.txt
[DEBUG] running /code/SuperBuild/build/pdal/bin/pdal pipeline -i /code/odm_georeferencing/las.json --readers.ply.filename=/code/odm_georeferencing/odm_georeferenced_model.ply
PDAL: writers.las: Can't write LAZ output. PDAL not built with LASzip or LAZperf.
</syntaxhighlight>

<syntaxhighlight lang="json">
{
"pipeline": [
"untransformed.ply",
{
"type": "writers.las",
"a_srs": "+proj=utm +zone=33 +datum=WGS84 +units=m +no_defs ",
"offset_x": "334230.28164",
"offset_y": "6208095.41529",
"offset_z": "0",
"compression": "laszip",
"filename": "/code/odm_georeferencing/odm_georeferenced_model.laz"
}
]
}
</syntaxhighlight>

[[File:Captura de ecrã de 2018-06-17 14-34-10.png]]

=== Local pdal+LASzip ===

Build from source!

<syntaxhighlight lang="bash">
/usr/local/bin/pdal pipeline -i las.json --readers.ply.filename=odm_georeferenced_model.ply
-rw-r--r-- 1 jgr jgr 22661583 jun 17 11:47 odm_georeferenced_model.laz
-rw-r--r-- 1 jgr jgr 121586206 jun 17 11:42 odm_georeferenced_model.ply
</syntaxhighlight>

==== Previous result ====

[[File:Captura de ecrã de 2018-06-16 12-26-36.png]]

==== New result ====

=== Create Pull Request ===

close #845

=== Other fixes ===

epsg versus EPSG

== Point cloud classification ==

[DEBUG] running pdal info --boundary --filters.hexbin.edge_length=1 --filters.hexbin.threshold=0 /code/odm_georeferencing/odm_georeferenced_model.filtered.las > /code/odm_georeferencing/odm_georeferenced_model.boundary.json
PDAL: Argument references invalid/unused stage: 'filters.hexbin'.