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Merge branch 'dev' into orb_slam2 

Former-commit-id: ec147b2c7e
pull/1161/head
Pau Gargallo 2016-05-18 13:09:36 +02:00
rodzic d8b0dc7376 98fa20cb39
commit 2ed473c168
102 zmienionych plików z 2262 dodań i 1368 usunięć
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5
.dockerignore
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@ -1 +1,6 @@
Dockerfile
tests/test_data
SuperBuild/build
SuperBuild/download
SuperBuild/install
SuperBuild/src

4
.gitignore vendored
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@ -7,6 +7,10 @@ share/
src/
download/
SuperBuild/build/
SuperBuild/install/
build/
cmvs.tar.gz
parallel.tar.bz2
LAStools.zip

70
Dockerfile
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@ -4,23 +4,51 @@ MAINTAINER Danilo Bargen <mail@dbrgn.ch>
# Env variables
ENV DEBIAN_FRONTEND noninteractive
# Install git
RUN apt-get update \
&& apt-get install -y git
# Install dependencies
RUN apt-get install -y --install-recommends \
build-essential cmake g++ gcc gFortran perl git autoconf \
curl wget \
unzip \
imagemagick jhead proj-bin libproj-dev\
libjpeg-dev libboost-all-dev libgsl0-dev libx11-dev libxext-dev liblapack-dev \
libeigen3-dev libflann-dev libvtk5-dev libqhull-dev libusb-1.0-0-dev\
libjson-perl \
libzip-dev \
libswitch-perl \
libcv-dev libcvaux-dev libopencv-dev \
libgoogle-glog-dev libatlas-base-dev libsuitesparse-dev \
RUN apt-get update \
&& sudo apt-get remove libdc1394-22-dev \
&& apt-get install -y --install-recommends \
build-essential \
cmake \
git \
python-pip \
libgdal-dev \
libgeotiff-dev \
pkg-config \
libgtk2.0-dev \
libavcodec-dev \
libavformat-dev \
libswscale-dev \
python-dev \
python-numpy \
libtbb2 \
libtbb-dev \
libjpeg-dev \
libpng-dev \
libtiff-dev \
libjasper-dev \
libflann-dev \
libproj-dev \
libxext-dev \
liblapack-dev \
libeigen3-dev \
libvtk5-dev \
python-networkx \
libgoogle-glog-dev \
libsuitesparse-dev \
libboost-filesystem-dev \
libboost-iostreams-dev \
libboost-regex-dev \
libboost-python-dev \
libboost-date-time-dev \
libboost-thread-dev \
python-empy \
python-nose \
python-pyside \
python-pyexiv2 \
python-scipy \
jhead \
liblas-bin \
&& apt-get autoremove \
&& apt-get clean
@ -38,11 +66,15 @@ ADD . /code/
RUN git submodule init && git submodule update
# Build OpenDroneMap
RUN ./install.sh && \
RUN bash ./configure.sh && \
mkdir build && cd build && cmake .. && make && cd .. && \
chown -R odm:odm /code
USER odm
ENV PYTHONPATH=${PYTHONPATH}:/code/SuperBuild/install/lib/python2.7/dist-packages:/code/SuperBuild/src/opensfm \
LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:/code/SuperBuild/install/lib
# Entry point
VOLUME ["/images"]
WORKDIR /images
ENTRYPOINT ["/code/run.pl"]
# WORKDIR /images
ENTRYPOINT ["python", "/code/run.py", "--project-path", "/images"]

674
LICENSE 100644
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@ -0,0 +1,674 @@
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THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM
IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
16. Limitation of Liability.
IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
SUCH DAMAGES.
17. Interpretation of Sections 15 and 16.
If the disclaimer of warranty and limitation of liability provided
above cannot be given local legal effect according to their terms,
reviewing courts shall apply local law that most closely approximates
an absolute waiver of all civil liability in connection with the
Program, unless a warranty or assumption of liability accompanies a
copy of the Program in return for a fee.
END OF TERMS AND CONDITIONS
How to Apply These Terms to Your New Programs
If you develop a new program, and you want it to be of the greatest
possible use to the public, the best way to achieve this is to make it
free software which everyone can redistribute and change under these terms.
To do so, attach the following notices to the program. It is safest
to attach them to the start of each source file to most effectively
state the exclusion of warranty; and each file should have at least
the "copyright" line and a pointer to where the full notice is found.
{one line to give the program's name and a brief idea of what it does.}
Copyright (C) {year} {name of author}
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
Also add information on how to contact you by electronic and paper mail.
If the program does terminal interaction, make it output a short
notice like this when it starts in an interactive mode:
{project} Copyright (C) {year} {fullname}
This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
This is free software, and you are welcome to redistribute it
under certain conditions; type `show c' for details.
The hypothetical commands `show w' and `show c' should show the appropriate
parts of the General Public License. Of course, your program's commands
might be different; for a GUI interface, you would use an "about box".
You should also get your employer (if you work as a programmer) or school,
if any, to sign a "copyright disclaimer" for the program, if necessary.
For more information on this, and how to apply and follow the GNU GPL, see
<http://www.gnu.org/licenses/>.
The GNU General Public License does not permit incorporating your program
into proprietary programs. If your program is a subroutine library, you
may consider it more useful to permit linking proprietary applications with
the library. If this is what you want to do, use the GNU Lesser General
Public License instead of this License. But first, please read
<http://www.gnu.org/philosophy/why-not-lgpl.html>.

197
README.md
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@ -1,9 +1,15 @@
# OpenDroneMap
![](https://opendronemap.github.io/OpenDroneMap/img/odm_image.png)
What is it?
===========
OpenDroneMap is a toolchain for processing raw civilian UAS imagery to other useful products. What kind of products?
OpenDroneMap is an open source toolkit for processing aerial drone imagery. Typical drones use simple point-and-shoot cameras, so the images from drones, while from a different perspective, are similar to any pictures taken from point-and-shoot cameras, i.e. non-metric imagery. OpenDroneMap turns those simple images into three dimensional geographic data that can be used in combination with other geographic datasets.
![](https://opendronemap.github.io/OpenDroneMap/img/tol_ptcloud.png)
In a word, OpenDroneMap is a toolchain for processing raw civilian UAS imagery to other useful products. What kind of products?
1. Point Clouds
2. Digital Surface Models
@ -26,52 +32,116 @@ Developers
Help improve our software!
1. Join our [Gitter](https://gitter.im/OpenDroneMap)
2. Try to keep commits clean and simple
3. Submit a pull request with detailed changes and test results
[![Join the chat at https://gitter.im/OpenDroneMap/OpenDroneMap](https://badges.gitter.im/Join%20Chat.svg)](https://gitter.im/OpenDroneMap/OpenDroneMap?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
1. Try to keep commits clean and simple
2. Submit a pull request with detailed changes and test results
Steps to get OpenDroneMap running:
==================================
(Requires Ubuntu 12.04 or later, see https://github.com/OpenDroneMap/odm_vagrant for running on Windows in a VM)
(Requires Ubuntu 14.04 or later, see https://github.com/OpenDroneMap/odm_vagrant for running on Windows in a VM)
Run install.sh to build.
Support for Ubuntu 12.04 is currently BROKEN with the addition of OpenSfM and Ceres-Solver. We are working hard to get it working again in the future.
./install.sh
#### Building OpenDroneMap using git
From a directory full of your images, run
cd path/to/odm/dir
git clone https://github.com/OpenDroneMap/OpenDroneMap.git .
export PYTHONPATH=$PYTHONPATH:`pwd`/SuperBuild/install/lib/python2.7/dist-packages:`pwd`/SuperBuild/src/opensfm
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:`pwd`/SuperBuild/install/lib
bash configure.sh
mkdir build && cd build && cmake .. && make && cd ..
./run.pl
For Ubuntu 15.10 users, this will help you get running:
An overview of installing and running OpenDroneMap on Ubuntu can be found here: https://www.youtube.com/watch?v=e2qp3o8caPs
sudo apt-get install python-xmltodict
sudo ln -s /usr/lib/x86_64-linux-gnu/libproj.so.9 /usr/lib/libproj.so
#### Running OpenDroneMap
Here are some other videos:
First you need a set of images, which may or may not be georeferenced. There are two ways OpenDroneMap can understand geographic coordinates. First, the images can be geotagged in their EXIF data. This is the default. Alternatively, you can create a GCP file, [a process detailed here](https://github.com/OpenDroneMap/OpenDroneMap/wiki/2.-Running-OpenDroneMap#running-odm-with-ground-control)
Create a project folder and places your images in an "images" directory:
|-- /path/to/project/
|-- images/
|-- img-1234.jpg
|-- ...
Example data can be cloned from https://github.com/OpenDroneMap/odm_data
Then run:
python run.py --project-path /path/to/project
There are many options for tuning your project. See the [wiki](https://github.com/OpenDroneMap/OpenDroneMap/wiki/3.-Run-Time-Parameters) or run `python run.py -h`
When the process finishes, the results will be organized as follows
|-- images/
|-- img-1234.jpg
|-- ...
|-- images_resize/
|-- img-1234.jpg
|-- ...
|-- opensfm/
|-- not much useful in here
|-- pmvs/
|-- recon0/
|-- models/
|-- option-0000.ply # Dense point cloud
|-- odm_meshing/
|-- odm_mesh.ply # A 3D mesh
|-- odm_meshing_log.txt # Output of the meshing task. May point out errors.
|-- odm_texturing/
|-- odm_textured_model.obj # Textured mesh
|-- odm_textured_model_geo.obj # Georeferenced textured mesh
|-- texture_N.jpg # Associated textured images used by the model
|-- odm_georeferencing/
|-- odm_georeferenced_model.ply # A georeferenced dense point cloud
|-- odm_georeferenced_model.ply.laz # LAZ format point cloud
|-- odm_georeferenced_model.csv # XYZ format point cloud
|-- odm_georeferencing_log.txt # Georeferencing log
|-- odm_georeferencing_utm_log.txt # Log for the extract_utm portion
|-- odm_georeferencing/
|-- odm_orthophoto.png # Orthophoto image (no coordinates)
|-- odm_orthophoto.tif # Orthophoto GeoTiff
|-- odm_orthophoto_log.txt # Log file
|-- gdal_translate_log.txt # Log for georeferencing the png file
##### Viewing your results
Any file ending in .obj or .ply can be opened and viewed in [MeshLab](http://meshlab.sourceforge.net/) or similar software. That includes `pmvs/recon0/models/option-000.ply`, `odm_meshing/odm_mesh.ply`, `odm_texturing/odm_textured_model[_geo].obj`, or `odm_georeferencing/odm_georeferenced_model.ply`. Below is an example textured mesh:
![](https://opendronemap.github.io/OpenDroneMap/img/tol_text.png)
You can also view the orthophoto GeoTIFF in QGIS or other mapping software:
![](https://raw.githubusercontent.com/OpenDroneMap/OpenDroneMap/dev/img/bellus_map.png)
#### Using Docker
You can build and run OpenDroneMap in a Docker container:
export IMAGES=/absolute/path/to/your/project
docker build -t opendronemap:latest .
docker run -v $IMAGES:/images opendronemap:latest
Replace /absolute/path/to/your/images with an absolute path to the directory containing your project (where the images are)
To pass in custom parameters to the `run.py` script, simply pass it as arguments to the `docker run` command.
---
Here are some other videos, which may be outdated:
- https://www.youtube.com/watch?v=7ZTufQkODLs (2015-01-30)
- https://www.youtube.com/watch?v=m0i4GQdfl8A (2015-03-15)
Now that texturing is in the code base, you can access the full textured meshes using MeshLab. Open MeshLab, choose `File:Import Mesh` and choose your textured mesh from a location similar to the following: `reconstruction-with-image-size-1200-results\odm_texturing\odm_textured_model.obj`
For Ubuntu 15.10 users, this will help you get running:
```
sudo apt-get install python-xmltodict
sudo ln -s /usr/lib/x86_64-linux-gnu/libproj.so.9 /usr/lib/libproj.so
```
---
Alternatively, you can also run OpenDroneMap in a Docker container:
export IMAGES=/absolute/path/to/your/images
docker build -t opendronemap:latest .
docker run -v $IMAGES:/images opendronemap:latest
To pass in custom parameters to the `run.pl` script, simply pass it as arguments to the `docker run` command.
---
Example data can be found at https://github.com/OpenDroneMap/odm_data
---
Long term, the aim is for the toolchain to also be able to optionally push to a variety of online data repositories, pushing hi-resolution aerials to [OpenAerialMap](http://opentopography.org/), point clouds to [OpenTopography](http://opentopography.org/), and pushing digital elevation models to an emerging global repository (yet to be named...). That leaves only digital surface model meshes and UV textured meshes with no global repository home.
@ -84,68 +154,3 @@ Documentation:
For documentation, please take a look at our [wiki](https://github.com/OpenDroneMap/OpenDroneMap/wiki).
Troubleshooting:
================
Make sure you have enough RAM and CPU. Only lowercase file extension supported now.
If you run ODM with your own camera, it is possible you will see something like this:
```
- configuration:
--cmvs-maxImages: 500
--end-with: pmvs
--match-size: 200
--matcher-ratio: 0.6
--matcher-threshold: 2
--pmvs-csize: 2
--pmvs-level: 1
--pmvs-minImageNum: 3
--pmvs-threshold: 0.7
--pmvs-wsize: 7
--resize-to: 1200
--start-with: resize
- source files - Fri Sep 19 13:47:42 UTC 2014
no CCD width or focal length found for DSC05391.JPG - camera: "SONY DSC-HX5V"
no CCD width or focal length found for DSC05392.JPG - camera: "SONY DSC-HX5V"
no CCD width or focal length found for DSC05393.JPG - camera: "SONY DSC-HX5V"
no CCD width or focal length found for DSC05394.JPG - camera: "SONY DSC-HX5V"
no CCD width or focal length found for DSC05395.JPG - camera: "SONY DSC-HX5V"
no CCD width or focal length found for DSC05396.JPG - camera: "SONY DSC-HX5V"
no CCD width or focal length found for DSC05397.JPG - camera: "SONY DSC-HX5V"
no CCD width or focal length found for DSC05398.JPG - camera: "SONY DSC-HX5V"
no CCD width or focal length found for DSC05399.JPG - camera: "SONY DSC-HX5V"
found no usable images - quitting
Died at ../../OpenDroneMap/./run.pl line 364.
```
This means that your camera is not in the database, https://github.com/OpenDroneMap/OpenDroneMap/blob/gh-pages/ccd_defs.json
This problem is easily remedied. We need to know CCD size in the camera. We'll get these for our Sony Cyber-shot DSC-HX5 from dpreview: http://www.dpreview.com/products/sony/compacts/sony_dschx5/specifications
So, we'll add the following line to our ccd_defs.json:
"SONY DSC-HX5V": 6.104,
To check that ccd_defs.json compiles, run ccd_defs_check.pl
If it prints the message 'CCD_DEFS compiles OK', then you can commit your changes.
And so others can use it, we'll do a pull request to add it to our array for everyone else.
---
Maintainers can run the ccd_defs.json compilation test automatically by creating a
symbolic link in .git/hooks to hooks/pre-commit
cd .git/hooks
ln -s ../../hooks/pre-commit
If ccd_defs.json does not compile, then the pre-commit hook will abort the commit.

2
SuperBuild/CMakeLists.txt
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@ -94,7 +94,6 @@ SETUP_EXTERNAL_PROJECT(Ceres ${ODM_Ceres_Version} ${ODM_BUILD_Ceres})
# Clustering Views for Multi-view Stereo (CMVS)
# Catkin
# Ecto
# LAStools
#
set(custom_libs OpenGV
@ -102,6 +101,7 @@ set(custom_libs OpenGV
CMVS
Catkin
Ecto
PDAL
LAStools
Pangolin
ORB_SLAM2)

1
SuperBuild/cmake/External-Catkin.cmake
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@ -14,6 +14,7 @@ ExternalProject_Add(${_proj_name}
#--Configure step-------------
SOURCE_DIR ${SB_SOURCE_DIR}/${_proj_name}
CMAKE_ARGS
-DCATKIN_ENABLE_TESTING=OFF
-DCMAKE_INSTALL_PREFIX:PATH=${SB_INSTALL_DIR}
#--Build step-----------------
BINARY_DIR ${_SB_BINARY_DIR}

9
SuperBuild/cmake/External-Ecto.cmake
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@ -8,13 +8,16 @@ ExternalProject_Add(${_proj_name}
STAMP_DIR ${_SB_BINARY_DIR}/stamp
#--Download step--------------
DOWNLOAD_DIR ${SB_DOWNLOAD_DIR}/${_proj_name}
URL https://github.com/plasmodic/ecto/archive/master.zip
URL_MD5 8cd70c525bcda99d9eba5ac2865e42dd
URL https://github.com/plasmodic/ecto/archive/c6178ed0102a66cebf503a4213c27b0f60cfca69.zip
URL_MD5 A5C4757B656D536D3E3CC1DC240EC158
#--Update/Patch step----------
UPDATE_COMMAND ""
#--Configure step-------------
SOURCE_DIR ${SB_SOURCE_DIR}/${_proj_name}
CMAKE_ARGS
-DBUILD_DOC=OFF
-DBUILD_SAMPLES=OFF
-DCATKIN_ENABLE_TESTING=OFF
-DCMAKE_INSTALL_PREFIX:PATH=${SB_INSTALL_DIR}
#--Build step-----------------
BINARY_DIR ${_SB_BINARY_DIR}
@ -24,4 +27,4 @@ ExternalProject_Add(${_proj_name}
LOG_DOWNLOAD OFF
LOG_CONFIGURE OFF
LOG_BUILD OFF
)
)

26
SuperBuild/cmake/External-LAStools.cmake
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@ -1,26 +0,0 @@
set(_proj_name las-tools)
set(_SB_BINARY_DIR "${SB_BINARY_DIR}/${_proj_name}")
ExternalProject_Add(${_proj_name}
PREFIX ${_SB_BINARY_DIR}
TMP_DIR ${_SB_BINARY_DIR}/tmp
STAMP_DIR ${_SB_BINARY_DIR}/stamp
#--Download step--------------
DOWNLOAD_DIR ${SB_DOWNLOAD_DIR}
URL http://lastools.org/download/LAStools.zip
#--Update/Patch step----------
UPDATE_COMMAND ""
#--Configure step-------------
SOURCE_DIR ${SB_SOURCE_DIR}/${_proj_name}
CONFIGURE_COMMAND ""
WORKING_DIRECTORY "${SB_SOURCE_DIR}/${_proj_name}"
#--Build step-----------------
BUILD_IN_SOURCE 1
#--Install step---------------
INSTALL_DIR ${SB_INSTALL_DIR}
INSTALL_COMMAND ""
#--Output logging-------------
LOG_DOWNLOAD OFF
LOG_CONFIGURE OFF
LOG_BUILD OFF
)

1
SuperBuild/cmake/External-OpenGV.cmake
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@ -8,7 +8,6 @@ ExternalProject_Add(${_proj_name}
#--Download step--------------
DOWNLOAD_DIR ${SB_DOWNLOAD_DIR}
URL https://github.com/paulinus/opengv/archive/python-wrapper.zip
URL_MD5 6afd5dfbec8f11b556e794d009bbbcc2
#--Update/Patch step----------
UPDATE_COMMAND ""
#--Configure step-------------

46
SuperBuild/cmake/External-PDAL.cmake 100644
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@ -0,0 +1,46 @@
set(_proj_name pdal)
set(_SB_BINARY_DIR "${SB_BINARY_DIR}/${_proj_name}")
ExternalProject_Add(${_proj_name}
PREFIX ${_SB_BINARY_DIR}
TMP_DIR ${_SB_BINARY_DIR}/tmp
STAMP_DIR ${_SB_BINARY_DIR}/stamp
#--Download step--------------
DOWNLOAD_DIR ${SB_DOWNLOAD_DIR}
URL https://github.com/PDAL/PDAL/archive/d242c6704aafe85fd49fda11adae63d07ce11b76.zip
URL_MD5 14a7319e1f8483808eb93732cfa6511a
#--Update/Patch step----------
UPDATE_COMMAND ""
#--Configure step-------------
SOURCE_DIR ${SB_SOURCE_DIR}/${_proj_name}
CMAKE_ARGS
-BUILD_PGPOINTCLOUD_TESTS=OFF
-BUILD_PLUGIN_PCL=ON
-BUILD_PLUGIN_PGPOINTCLOUD=ON
-DBUILD_PLUGIN_CPD=OFF
-DBUILD_PLUGIN_GREYHOUND=OFF
-DBUILD_PLUGIN_HEXBIN=OFF
-DBUILD_PLUGIN_ICEBRIDGE=OFF
-DBUILD_PLUGIN_MRSID=OFF
-DBUILD_PLUGIN_NITF=OFF
-DBUILD_PLUGIN_OCI=OFF
-DBUILD_PLUGIN_P2G=OFF
-DBUILD_PLUGIN_SQLITE=OFF
-DBUILD_PLUGIN_RIVLIB=OFF
-DBUILD_PLUGIN_PYTHON=OFF
-DENABLE_CTEST=OFF
-DWITH_APPS=ON
-DWITH_LAZPERF=OFF
-DWITH_GEOTIFF=ON
-DWITH_LASZIP=ON
-DWITH_TESTS=OFF
-DCMAKE_INSTALL_PREFIX:PATH=${SB_INSTALL_DIR}
#--Build step-----------------
BINARY_DIR ${_SB_BINARY_DIR}
#--Install step---------------
INSTALL_DIR ${SB_INSTALL_DIR}
#--Output logging-------------
LOG_DOWNLOAD OFF
LOG_CONFIGURE OFF
LOG_BUILD OFF
)

33
configure.sh
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@ -11,9 +11,9 @@ fi
echo -e "\e[1;34mUpdating the system\e[0;39m"
sudo apt-get update
END_CMD1=$?
sudo apt-get upgrade -y
END_CMD2=$?
if [ $END_CMD1 -ne 0 -o $END_CMD2 -ne 0 ]
# sudo apt-get upgrade -y
# END_CMD2=$?
if [ $END_CMD1 -ne 0 ]
then
echo -e "\e[1;31mERROR: \e[39mWhen Updating the system\e[0m"
exit 1
@ -25,7 +25,10 @@ sudo apt-get install build-essential \
cmake \
git \
python-pip \
pkg-config -y
libgdal-dev \
gdal-bin \
libgeotiff-dev \
pkg-config -y -qq
if [ $? -ne 0 ]
then
echo -e "\e[1;31mERROR: \e[39mWhen Installing Required Requisites\e[0m"
@ -51,7 +54,7 @@ sudo apt-get install libgtk2.0-dev \
libxext-dev \
liblapack-dev \
libeigen3-dev \
libvtk5-dev -y
libvtk5-dev -y -qq
if [ $? -ne 0 ]
then
echo -e "\e[1;31mERROR: \e[39mError when Installing Dependencies Requisites\e[0m"
@ -67,12 +70,12 @@ echo -e "\e[1;34mInstalling OpenSfM Dependencies\e[0;39m"
sudo apt-get install python-networkx \
libgoogle-glog-dev \
libsuitesparse-dev \
libboost-filesystem1.55-dev \
libboost-iostreams1.55-dev \
libboost-regex1.55-dev \
libboost-python1.55-dev \
#libboost1.55-all-dev \
libboost-python-dev -y
libboost-filesystem-dev \
libboost-iostreams-dev \
libboost-regex-dev \
libboost-python-dev \
libboost-date-time-dev \
libboost-thread-dev -y -qq
sudo pip install -U PyYAML \
exifread \
@ -89,7 +92,7 @@ echo -e "\e[1;34mInstalling Ecto Dependencies\e[0;39m"
sudo pip install -U catkin-pkg
sudo apt-get install python-empy \
python-nose \
python-pyside -y
python-pyside -y -qq
if [ $? -ne 0 ]
then
echo -e "\e[1;31mERROR: \e[39mError when Installing Ecto Dependencies\e[0m"
@ -101,7 +104,7 @@ echo -e "\e[1;34mInstalling OpenDroneMap Dependencies\e[0;39m"
sudo apt-get install python-pyexiv2 \
python-scipy \
jhead \
liblas-bin -y
liblas-bin -y -qq
if [ $? -ne 0 ]
then
echo -e "\e[1;31mERROR: \e[39mError when Installing OpenDroneMap Dependencies\e[0m"
@ -115,11 +118,11 @@ NUM_CORES=`grep -c processor /proc/cpuinfo`
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:`pwd`/SuperBuild/install/lib
## Add SuperBuild path to the python path
export PYTHONPATH=$PYTHONPATH:`pwd`/SuperBuild/install/lib/python2.7/dist-packages
export PYTHONPATH=$PYTHONPATH:`pwd`/SuperBuild/install/lib/python2.7/dist-packages:`pwd`/SuperBuild/src/opensfm
## Compile SuperBuild
cd SuperBuild
mkdir -p build && cd build
cmake .. && make -j ${NUM_CORES}
cmake .. && make -j${NUM_CORES}
echo -e "\e[1;34mScript finished\e[0;39m"

319
data/ccd_defs.json
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@ -1,319 +0,0 @@
{
"Apple iPhone 5s": 8.46,
"Asahi Optical Co.,Ltd. PENTAX Optio330RS": 7.176,
"Canon Canon DIGITAL IXUS 400": 7.176,
"Canon Canon DIGITAL IXUS 40": 5.76,
"Canon Canon DIGITAL IXUS 430": 6.18,
"Canon Canon DIGITAL IXUS 500": 7.176,
"Canon Canon DIGITAL IXUS 50": 5.76,
"Canon Canon DIGITAL IXUS 55": 5.76,
"Canon Canon DIGITAL IXUS 60": 5.76,
"Canon Canon DIGITAL IXUS 65": 5.76,
"Canon Canon DIGITAL IXUS 700": 7.176,
"Canon Canon DIGITAL IXUS 750": 7.176,
"Canon Canon DIGITAL IXUS 800 IS": 5.76,
"Canon Canon DIGITAL IXUS II": 5.27,
"Canon Canon EOS 10D": 22.7,
"Canon Canon EOS-1D Mark II": 28.7,
"Canon Canon EOS-1Ds Mark II": 35.95,
"Canon Canon EOS 20D": 22.5,
"Canon Canon EOS 20D": 22.5,
"Canon Canon EOS 300D DIGITAL": 22.66,
"Canon Canon EOS 30D": 22.5,
"Canon Canon EOS 350D DIGITAL": 22.2,
"Canon Canon EOS 400D DIGITAL": 22.2,
"Canon Canon EOS 40D": 22.2,
"Canon Canon EOS 5D": 35.8,
"Canon Canon EOS 5D Mark II": 36.0,
"Canon Canon EOS DIGITAL REBEL": 22.66,
"Canon Canon EOS DIGITAL REBEL XT": 22.2,
"Canon Canon EOS DIGITAL REBEL XTi": 22.2,
"Canon Canon EOS Kiss Digital": 22.66,
"Canon Canon IXY DIGITAL 600": 7.176,
"Canon Canon PowerShot A10": 5.23,
"Canon Canon PowerShot A20": 7.176,
"Canon Canon PowerShot A400": 4.54,
"Canon Canon PowerShot A40": 5.27,
"Canon Canon PowerShot A510": 5.76,
"Canon Canon PowerShot A520": 5.76,
"Canon Canon PowerShot A530": 5.76,
"Canon Canon PowerShot A60": 5.27,
"Canon Canon PowerShot A620": 7.176,
"Canon Canon PowerShot A630": 7.176,
"Canon Canon PowerShot A640": 7.176,
"Canon Canon PowerShot A700": 5.76,
"Canon Canon PowerShot A70": 5.27,
"Canon Canon PowerShot A710 IS": 5.76,
"Canon Canon PowerShot A75": 5.27,
"Canon Canon PowerShot A80": 7.176,
"Canon Canon PowerShot A85": 5.27,
"Canon Canon PowerShot A95": 7.176,
"Canon Canon PowerShot G12": 7.44,
"Canon Canon PowerShot G1": 7.176,
"Canon Canon PowerShot G2": 7.176,
"Canon Canon PowerShot G3": 7.176,
"Canon Canon PowerShot G5": 7.176,
"Canon Canon PowerShot G6": 7.176,
"Canon Canon PowerShot G7": 7.176,
"Canon Canon PowerShot G9": 7.6,
"Canon Canon PowerShot Pro1": 8.8,
"Canon Canon PowerShot S100": 7.44,
"Canon Canon PowerShot S110": 5.27,
"Canon Canon PowerShot S1 IS": 5.27,
"Canon Canon PowerShot S200": 5.27,
"Canon Canon PowerShot S2 IS": 5.76,
"Canon Canon PowerShot S30": 7.176,
"Canon Canon PowerShot S3 IS": 5.76,
"Canon Canon PowerShot S400": 7.176,
"Canon Canon PowerShot S40": 7.176,
"Canon Canon PowerShot S410": 7.176,
"Canon Canon PowerShot S45": 7.176,
"Canon Canon PowerShot S500": 7.176,
"Canon Canon PowerShot S50": 7.176,
"Canon Canon PowerShot S60": 7.176,
"Canon Canon PowerShot S70": 7.176,
"Canon Canon PowerShot S80": 7.176,
"Canon Canon PowerShot SD1000": 5.75,
"Canon Canon PowerShot SD100": 5.27,
"Canon Canon PowerShot SD10": 5.75,
"Canon Canon PowerShot SD110": 5.27,
"Canon Canon PowerShot SD200": 5.76,
"Canon Canon PowerShot SD300": 5.76,
"Canon Canon PowerShot SD400": 5.76,
"Canon Canon PowerShot SD450": 5.76,
"Canon Canon PowerShot SD500": 7.176,
"Canon Canon PowerShot SD550": 7.176,
"Canon Canon PowerShot SD600": 5.76,
"Canon Canon PowerShot SD630": 5.76,
"Canon Canon PowerShot SD700 IS": 5.76,
"Canon Canon PowerShot SD750": 5.75,
"Canon Canon PowerShot SD800 IS": 5.76,
"Canon Canon PowerShot SX260 HS": 6.2,
"Canon EOS 300D DIGITAL": 22.66,
"Canon EOS DIGITAL REBEL": 22.66,
"Canon PowerShot A510": 5.76,
"Canon PowerShot S30": 7.176,
"CASIO COMPUTER CO.,LTD. EX-S500": 5.76,
"CASIO COMPUTER CO.,LTD. EX-Z1000": 7.716,
"CASIO COMPUTER CO.,LTD EX-Z30": 5.76,
"CASIO COMPUTER CO.,LTD. EX-Z600": 5.76,
"CASIO COMPUTER CO.,LTD. EX-Z60": 7.176,
"CASIO COMPUTER CO.,LTD EX-Z750": 7.176,
"CASIO COMPUTER CO.,LTD. EX-Z850": 7.176,
"DJI FC300S": 6.16,
"DJI FC300X": 6.2,
"DJI FC350": 6.17,
"DJI PHANTOM VISION FC200": 6.17,
"EASTMAN KODAK COMPANY KODAK CX7330 ZOOM DIGITAL CAMERA": 5.27,
"EASTMAN KODAK COMPANY KODAK CX7530 ZOOM DIGITAL CAMERA": 5.76,
"EASTMAN KODAK COMPANY KODAK DX3900 ZOOM DIGITAL CAMERA": 7.176,
"EASTMAN KODAK COMPANY KODAK DX4900 ZOOM DIGITAL CAMERA": 7.176,
"EASTMAN KODAK COMPANY KODAK DX6340 ZOOM DIGITAL CAMERA": 5.27,
"EASTMAN KODAK COMPANY KODAK DX6490 ZOOM DIGITAL CAMERA": 5.76,
"EASTMAN KODAK COMPANY KODAK DX7630 ZOOM DIGITAL CAMERA": 7.176,
"EASTMAN KODAK COMPANY KODAK Z650 ZOOM DIGITAL CAMERA": 5.76,
"EASTMAN KODAK COMPANY KODAK Z700 ZOOM DIGITAL CAMERA": 5.76,
"EASTMAN KODAK COMPANY KODAK Z740 ZOOM DIGITAL CAMERA": 5.76,
"FUJIFILM FinePix2600Zoom": 5.27,
"FUJIFILM FinePix40i": 7.6,
"FUJIFILM FinePix A310": 5.27,
"FUJIFILM FinePix A330": 5.27,
"FUJIFILM FinePix A600": 7.6,
"FUJIFILM FinePix E500": 5.76,
"FUJIFILM FinePix E510": 5.76,
"FUJIFILM FinePix E550": 7.6,
"FUJIFILM FinePix E900": 7.78,
"FUJIFILM FinePix F10": 7.6,
"FUJIFILM FinePix F30": 7.6,
"FUJIFILM FinePix F450": 5.76,
"FUJIFILM FinePix F601 ZOOM": 7.6,
"FUJIFILM FinePix S3Pro": 23,
"FUJIFILM FinePix S5000": 5.27,
"FUJIFILM FinePix S5200": 5.76,
"FUJIFILM FinePix S5500": 5.27,
"FUJIFILM FinePix S6500fd": 7.6,
"FUJIFILM FinePix S7000": 7.6,
"FUJIFILM FinePix Z2": 5.76,
"Garmin VIRB": 6.17,
"GoPro HD2 U": 5.8,
"Gopro HD3": 5.76,
"GoPro HERO4 Black": 6.17,
"GoPro HERO4 Silver":6.17,
"Hewlett-Packard hp 635 Digital Camera": 4.54,
"Hewlett-Packard hp PhotoSmart 43x series": 5.27,
"Hewlett-Packard HP PhotoSmart 618 (V1.1)": 5.27,
"Hewlett-Packard HP PhotoSmart C945 (V01.61)": 7.176,
"Hewlett-Packard HP PhotoSmart R707 (V01.00)": 7.176,
"KONICA MILOLTA DYNAX 5D": 23.5,
"Konica Minolta Camera, Inc. DiMAGE A2": 8.8,
"KONICA MINOLTA CAMERA, Inc. DiMAGE G400": 5.76,
"Konica Minolta Camera, Inc. DiMAGE Z2": 5.76,
"KONICA MINOLTA DiMAGE A200": 8.8,
"KONICA MINOLTA DiMAGE X1": 7.176,
"KONICA MINOLTA DYNAX 5D": 23.5,
"Minolta Co., Ltd. DiMAGE F100": 7.176,
"Minolta Co., Ltd. DiMAGE Xi": 5.27,
"Minolta Co., Ltd. DiMAGE Xt": 5.27,
"Minolta Co., Ltd. DiMAGE Z1": 5.27,
"Mobius Action Cam": 2.1,
"NIKON COOLPIX L3": 5.76,
"NIKON COOLPIX P2": 7.176,
"NIKON COOLPIX P7700": 7.44,
"NIKON COOLPIX S4": 5.76,
"NIKON COOLPIX S7c": 5.76,
"NIKON COOLPIX S8000": 6.17,
"NIKON CORPORATION NIKON 1 J4": 13.2,
"NIKON CORPORATION NIKON D100": 23.7,
"NIKON CORPORATION NIKON D1": 23.7,
"NIKON CORPORATION NIKON D1H": 23.7,
"NIKON CORPORATION NIKON D200": 23.6,
"NIKON CORPORATION NIKON D2H": 23.3,
"NIKON CORPORATION NIKON D2X": 23.7,
"NIKON CORPORATION NIKON D40": 23.7,
"NIKON CORPORATION NIKON D50": 23.7,
"NIKON CORPORATION NIKON D60": 23.6,
"NIKON CORPORATION NIKON D700": 36,
"NIKON CORPORATION NIKON D70": 23.7,
"NIKON CORPORATION NIKON D70s": 23.7,
"NIKON CORPORATION NIKON D80": 23.6,
"NIKON CORPORATION NIKON D5300": 23.5,
"NIKON D5100": 23.6,
"NIKON E2500": 5.27,
"NIKON E3100": 5.27,
"NIKON E3200": 5.27,
"NIKON E3700": 5.27,
"NIKON E4200": 7.176,
"NIKON E4300": 7.18,
"NIKON E4500": 7.176,
"NIKON E4600": 5.76,
"NIKON E5000": 8.8,
"NIKON E5200": 7.176,
"NIKON E5400": 7.176,
"NIKON E5600": 5.76,
"NIKON E5700": 8.8,
"NIKON E5900": 7.176,
"NIKON E7600": 7.176,
"NIKON E775": 5.27,
"NIKON E7900": 7.176,
"NIKON E8800": 8.8,
"NIKON E990": 7.176,
"NIKON E995": 7.176,
"NIKON S1": 5.76,
"Nokia N80": 5.27,
"Nokia N93": 4.536,
"Nokia N95": 5.7,
"OLYMPUS CORPORATION C-5000Z": 7.176,
"OLYMPUS CORPORATION C5060WZ": 7.176,
"OLYMPUS CORPORATION C750UZ": 5.27,
"OLYMPUS CORPORATION C765UZ": 5.76,
"OLYMPUS CORPORATION C8080WZ": 8.8,
"OLYMPUS CORPORATION X250,D560Z,C350Z": 5.76,
"OLYMPUS CORPORATION X-3,C-60Z": 7.176,
"OLYMPUS CORPORATION X400,D580Z,C460Z": 5.27,
"OLYMPUS IMAGING CORP. E-500": 17.3,
"OLYMPUS IMAGING CORP. E-510": 17.3,
"OLYMPUS IMAGING CORP. FE115,X715": 5.76,
"OLYMPUS IMAGING CORP. SP310": 7.176,
"OLYMPUS IMAGING CORP. SP510UZ": 5.75,
"OLYMPUS IMAGING CORP. SP550UZ": 5.76,
"OLYMPUS IMAGING CORP. uD600,S600": 5.75,
"OLYMPUS_IMAGING_CORP. X450,D535Z,C370Z": 5.27,
"OLYMPUS IMAGING CORP. X550,D545Z,C480Z": 5.76,
"Olympus E-M10": 17.3,
"Olympus E-PL5": 17.3,
"Olympus E-PL6": 17.3,
"OLYMPUS OPTICAL CO.,LTD C2040Z": 6.4,
"OLYMPUS OPTICAL CO.,LTD C211Z": 5.27,
"OLYMPUS OPTICAL CO.,LTD C2Z,D520Z,C220Z": 4.54,
"OLYMPUS OPTICAL CO.,LTD C3000Z": 7.176,
"OLYMPUS OPTICAL CO.,LTD C300Z,D550Z": 5.4,
"OLYMPUS OPTICAL CO.,LTD C4100Z,C4000Z": 7.176,
"OLYMPUS OPTICAL CO.,LTD C750UZ": 5.27,
"OLYMPUS OPTICAL CO.,LTD X-2,C-50Z": 7.176,
"OLYMPUS SP550UZ": 5.76,
"OLYMPUS X100,D540Z,C310Z": 5.27,
"Panasonic DMC-FX01": 5.76,
"Panasonic DMC-FX07": 5.75,
"Panasonic DMC-FX9": 5.76,
"Panasonic DMC-FZ20": 5.76,
"Panasonic DMC-FZ2": 4.54,
"Panasonic DMC-FZ30": 7.176,
"Panasonic DMC-FZ50": 7.176,
"Panasonic DMC-FZ5": 5.76,
"Panasonic DMC-FZ7": 5.76,
"Panasonic DMC-LC1": 8.8,
"Panasonic DMC-LC33": 5.76,
"Panasonic DMC-LX1": 8.5,
"Panasonic DMC-LZ2": 5.76,
"Panasonic DMC-TS4": 6.08,
"Panasonic DMC-TZ1": 5.75,
"Panasonic DMC-TZ3": 5.68,
"Panasonic DMC-TZ5": 6.12,
"PENTAX Corporation PENTAX *ist DL": 23.5,
"PENTAX Corporation PENTAX *ist DS2": 23.5,
"PENTAX Corporation PENTAX *ist DS": 23.5,
"PENTAX Corporation PENTAX K100D": 23.5,
"PENTAX Corporation PENTAX Optio 450": 7.176,
"PENTAX Corporation PENTAX Optio 550": 7.176,
"PENTAX Corporation PENTAX Optio E10": 5.76,
"PENTAX Corporation PENTAX Optio S40": 5.76,
"PENTAX Corporation PENTAX Optio S4": 5.76,
"PENTAX Corporation PENTAX Optio S50": 5.76,
"PENTAX Corporation PENTAX Optio S5i": 5.76,
"PENTAX Corporation PENTAX Optio S5z": 5.76,
"PENTAX Corporation PENTAX Optio SV": 5.76,
"PENTAX Corporation PENTAX Optio WP": 5.75,
"PHANTOM VISION FC200": 6.17,
"RICOH CaplioG3 modelM": 5.27,
"RICOH Caplio GX": 7.176,
"RICOH Caplio R30": 5.75,
"Samsung Digimax 301": 5.27,
"Samsung Techwin <Digimax i5, Samsung #1>": 5.76,
"SAMSUNG TECHWIN Pro 815": 8.8,
"SONY A7": 35.9,
"SONY A7R": 35.9,
"SONY DSC-F828": 8.8,
"SONY DSC-H1": 6.104,
"SONY DSC-H2": 5.744,
"SONY DSC-H3": 5.744,
"SONY DSC-H5": 5.744,
"SONY DSC-H7": 5.744,
"SONY DSC-H9": 5.744,
"SONY DSC-HX5V": 6.104,
"SONY DSC-HX50V": 6.17,
"SONY DSC-N12": 7.176,
"SONY DSC-P100": 7.176,
"SONY DSC-P10": 7.176,
"SONY DSC-P12": 7.176,
"SONY DSC-P150": 7.176,
"SONY DSC-P200": 7.176,
"SONY DSC-P52": 5.27,
"SONY DSC-P72": 5.27,
"SONY DSC-P73": 5.27,
"SONY DSC-P8": 5.27,
"SONY DSC-R1": 21.5,
"SONY DSC-S40": 5.27,
"SONY DSC-S600": 5.76,
"SONY DSC-T9": 7.18,
"SONY DSC-V1": 7.176,
"SONY DSC-W1": 7.176,
"SONY DSC-W30": 5.76,
"SONY DSC-W50": 5.75,
"SONY DSC-W5": 7.176,
"SONY DSC-W7": 7.176,
"SONY DSC-W80": 5.75,
"SONY ILCE-7S": 35.8,
"SONY ILCE-5100": 23.5,
"SONY NEX-5T": 23.4,
"SONY NEX-5R": 23.4,
"SONY NEX-7": 23.5,
"SONY SLT-A55": 23.5,
"SONY SLT-A57": 23.5,
"SONY SLT-A65": 23.5,
"SONY SLT-A77": 23.5,
"SONY SLT-A77 II": 23.5,
"SONY SLT-A77V": 23.5,
"SONY SLT-A99": 35.8,
"Vexcel UltraCam": 28.00,
"Mantis i23": 45.00
}

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modules/odm_georef/src/Georef.cpp
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@ -28,7 +28,7 @@ GeorefGCP::~GeorefGCP()
void GeorefGCP::extractGCP(std::istringstream &gcpStream)
{
gcpStream >> x_ >> y_ >> z_ >> pixelY_ >> pixelX_ >> image_;
gcpStream >> x_ >> y_ >> z_ >> pixelX_ >> pixelY_ >> image_;
}
Vec3 GeorefGCP::getPos()
@ -865,7 +865,7 @@ void Georef::performGeoreferencingWithGCP()
if (nrGCPUsable < 3)
{
throw GeorefException("Less than 3 GCPs have correspondences in the generated model.");
throw GeorefException("Fewer than 3 GCPs have correspondences in the generated model.");
}
size_t gcp0; size_t gcp1; size_t gcp2;

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opendm/config.py
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@ -1,228 +1,255 @@
import argparse
import context
# parse arguments
processopts = ['resize', 'opensfm', 'slam', 'cmvs', 'pmvs',
'odm_meshing', 'odm_texturing', 'odm_georeferencing',
'odm_orthophoto']
class RerunFrom(argparse.Action):
def __call__(self, parser, namespace, values, option_string=None):
setattr(namespace, self.dest, processopts[processopts.index(values):])
parser = argparse.ArgumentParser(description='OpenDroneMap')
parser.add_argument('--project-path',
metavar='<string>',
help='Path to the project to process')
def config():
parser.add_argument('--project-path',
metavar='<string>',
help='Path to the project to process')
parser.add_argument('--resize-to', # currently doesn't support 'orig'
metavar='<integer>',
default=2400,
type=int,
help='resizes images by the largest side')
parser.add_argument('--resize-to', # currently doesn't support 'orig'
metavar='<integer>',
default=2400,
type=int,
help='resizes images by the largest side')
parser.add_argument('--start-with', '-s',
metavar='<string>',
default='resize',
choices=processopts,
help=('Can be one of: ' + ' | '.join(processopts)))
parser.add_argument('--start-with', '-s',
metavar='<string>',
default='resize',
choices=processopts,
help=('Can be one of: ' + ' | '.join(processopts)))
parser.add_argument('--end-with', '-e',
metavar='<string>',
default='odm_orthophoto',
choices=processopts,
help=('Can be one of:' + ' | '.join(processopts)))
parser.add_argument('--end-with', '-e',
metavar='<string>',
default='odm_orthophoto',
choices=processopts,
help=('Can be one of:' + ' | '.join(processopts)))
parser.add_argument('--rerun', '-r',
metavar='<string>',
choices=processopts,
help=('Can be one of:' + ' | '.join(processopts)))
rerun = parser.add_mutually_exclusive_group()
parser.add_argument('--video',
metavar='<string>',
help='Path to the video file to process')
rerun.add_argument('--rerun', '-r',
metavar='<string>',
choices=processopts,
help=('Can be one of:' + ' | '.join(processopts)))
parser.add_argument('--slam-config',
metavar='<string>',
help='Path to config file for orb-slam')
rerun.add_argument('--rerun-all',
action='store_true',
default=False,
help='force rerun of all tasks')
parser.add_argument('--force-focal',
metavar='<positive float>',
type=float,
help=('Override the focal length information for the '
'images'))
rerun.add_argument('--rerun-from',
action=RerunFrom,
metavar='<string>',
choices=processopts,
help=('Can be one of:' + ' | '.join(processopts)))
parser.add_argument('--force-ccd',
metavar='<positive float>',
type=float,
help='Override the ccd width information for the images')
parser.add_argument('--video',
metavar='<string>',
help='Path to the video file to process')
parser.add_argument('--min-num-features',
metavar='<integer>',
default=4000,
type=int,
help=('Minimum number of features to extract per image. '
'More features leads to better results but slower '
'execution. Default: %(default)s'))
parser.add_argument('--slam-config',
metavar='<string>',
help='Path to config file for orb-slam')
parser.add_argument('--matcher-threshold',
metavar='<percent>',
default=2.0,
type=float,
help=('Ignore matched keypoints if the two images share '
'less than <float> percent of keypoints. Default:'
' $(default)s'))
parser.add_argument('--force-focal',
metavar='<positive float>',
type=float,
help=('Override the focal length information for the '
'images'))
parser.add_argument('--matcher-ratio',
metavar='<float>',
default=0.6,
type=float,
help=('Ratio of the distance to the next best matched '
'keypoint. Default: %(default)s'))
parser.add_argument('--force-ccd',
metavar='<positive float>',
type=float,
help='Override the ccd width information for the images')
parser.add_argument('--matcher-neighbors',
type=int,
metavar='<integer>',
default=8,
help='Number of nearest images to pre-match based on GPS '
'exif data. Set to 0 to skip pre-matching. '
'Neighbors works together with Distance parameter, '
'set both to 0 to not use pre-matching. OpenSFM '
'uses both parameters at the same time, Bundler '
'uses only one which has value, prefering the '
'Neighbors parameter. Default: %(default)s')
parser.add_argument('--min-num-features',
metavar='<integer>',
default=4000,
type=int,
help=('Minimum number of features to extract per image. '
'More features leads to better results but slower '
'execution. Default: %(default)s'))
parser.add_argument('--matcher-distance',
metavar='<integer>',
default=0,
type=int,
help='Distance threshold in meters to find pre-matching '
'images based on GPS exif data. Set to 0 to skip '
'pre-matching. Default: %(default)s')
parser.add_argument('--matcher-threshold',
metavar='<percent>',
default=2.0,
type=float,
help=('Ignore matched keypoints if the two images share '
'less than <float> percent of keypoints. Default:'
' $(default)s'))
parser.add_argument('--cmvs-maxImages',
metavar='<integer>',
default=500,
type=int,
help='The maximum number of images per cluster. '
parser.add_argument('--matcher-ratio',
metavar='<float>',
default=0.6,
type=float,
help=('Ratio of the distance to the next best matched '
'keypoint. Default: %(default)s'))
parser.add_argument('--matcher-neighbors',
type=int,
metavar='<integer>',
default=8,
help='Number of nearest images to pre-match based on GPS '
'exif data. Set to 0 to skip pre-matching. '
'Neighbors works together with Distance parameter, '
'set both to 0 to not use pre-matching. OpenSFM '
'uses both parameters at the same time, Bundler '
'uses only one which has value, prefering the '
'Neighbors parameter. Default: %(default)s')
parser.add_argument('--matcher-distance',
metavar='<integer>',
default=0,
type=int,
help='Distance threshold in meters to find pre-matching '
'images based on GPS exif data. Set to 0 to skip '
'pre-matching. Default: %(default)s')
parser.add_argument('--cmvs-maxImages',
metavar='<integer>',
default=500,
type=int,
help='The maximum number of images per cluster. '
'Default: %(default)s')
parser.add_argument('--pmvs-level',
metavar='<positive integer>',
default=1,
type=int,
help=('The level in the image pyramid that is used '
'for the computation. see '
'http://www.di.ens.fr/pmvs/documentation.html for '
'more pmvs documentation. Default: %(default)s'))
parser.add_argument('--pmvs-level',
metavar='<positive integer>',
default=1,
type=int,
help=('The level in the image pyramid that is used '
'for the computation. see '
'http://www.di.ens.fr/pmvs/documentation.html for '
'more pmvs documentation. Default: %(default)s'))
parser.add_argument('--pmvs-csize',
metavar='< positive integer>',
default=2,
type=int,
help='Cell size controls the density of reconstructions'
parser.add_argument('--pmvs-csize',
metavar='< positive integer>',
default=2,
type=int,
help='Cell size controls the density of reconstructions'
'Default: %(default)s')
parser.add_argument('--pmvs-threshold',
metavar='<float: -1.0 <= x <= 1.0>',
default=0.7,
type=float,
help=('A patch reconstruction is accepted as a success '
'and kept if its associated photometric consistency '
'measure is above this threshold. Default: %(default)s'))
parser.add_argument('--pmvs-threshold',
metavar='<float: -1.0 <= x <= 1.0>',
default=0.7,
type=float,
help=('A patch reconstruction is accepted as a success '
'and kept if its associated photometric consistency '
'measure is above this threshold. Default: %(default)s'))
parser.add_argument('--pmvs-wsize',
metavar='<positive integer>',
default=7,
type=int,
help='pmvs samples wsize x wsize pixel colors from '
'each image to compute photometric consistency '
'score. For example, when wsize=7, 7x7=49 pixel '
'colors are sampled in each image. Increasing the '
'value leads to more stable reconstructions, but '
'the program becomes slower. Default: %(default)s')
parser.add_argument('--pmvs-wsize',
metavar='<positive integer>',
default=7,
type=int,
help='pmvs samples wsize x wsize pixel colors from '
'each image to compute photometric consistency '
'score. For example, when wsize=7, 7x7=49 pixel '
'colors are sampled in each image. Increasing the '
'value leads to more stable reconstructions, but '
'the program becomes slower. Default: %(default)s')
parser.add_argument('--pmvs-minImageNum',
metavar='<positive integer>',
default=3,
type=int,
help=('Each 3D point must be visible in at least '
'minImageNum images for being reconstructed. 3 is '
'suggested in general. Default: %(default)s'))
parser.add_argument('--pmvs-minImageNum',
metavar='<positive integer>',
default=3,
type=int,
help=('Each 3D point must be visible in at least '
'minImageNum images for being reconstructed. 3 is '
'suggested in general. Default: %(default)s'))
parser.add_argument('--pmvs-num-cores',
metavar='<positive integer>',
default=1,
type=int,
help=('The maximum number of cores to use in dense '
'reconstruction. Default: %(default)s'))
parser.add_argument('--pmvs-num-cores',
metavar='<positive integer>',
default=context.num_cores,
type=int,
help=('The maximum number of cores to use in dense '
'reconstruction. Default: %(default)s'))
parser.add_argument('--odm_meshing-maxVertexCount',
metavar='<positive integer>',
default=100000,
type=int,
help=('The maximum vertex count of the output mesh '
'Default: %(default)s'))
parser.add_argument('--odm_meshing-maxVertexCount',
metavar='<positive integer>',
default=100000,
type=int,
help=('The maximum vertex count of the output mesh '
'Default: %(default)s'))
parser.add_argument('--odm_meshing-octreeDepth',
metavar='<positive integer>',
default=9,
type=int,
help=('Oct-tree depth used in the mesh reconstruction, '
'increase to get more vertices, recommended '
'values are 8-12. Default: %(default)s'))
parser.add_argument('--odm_meshing-octreeDepth',
metavar='<positive integer>',
default=9,
type=int,
help=('Oct-tree depth used in the mesh reconstruction, '
'increase to get more vertices, recommended '
'values are 8-12. Default: %(default)s'))
parser.add_argument('--odm_meshing-samplesPerNode',
metavar='<float >= 1.0>',
default=1.0,
type=float,
help=('Number of points per octree node, recommended '
'and default value: %(default)s'))
parser.add_argument('--odm_meshing-samplesPerNode',
metavar='<float >= 1.0>',
default=1.0,
type=float,
help=('Number of points per octree node, recommended '
'and default value: %(default)s'))
parser.add_argument('--odm_meshing-solverDivide',
metavar='<positive integer>',
default=9,
type=int,
help=('Oct-tree depth at which the Laplacian equation '
'is solved in the surface reconstruction step. '
'Increasing this value increases computation '
'times slightly but helps reduce memory usage. '
'Default: %(default)s'))
parser.add_argument('--odm_meshing-solverDivide',
metavar='<positive integer>',
default=9,
type=int,
help=('Oct-tree depth at which the Laplacian equation '
'is solved in the surface reconstruction step. '
'Increasing this value increases computation '
'times slightly but helps reduce memory usage. '
'Default: %(default)s'))
parser.add_argument('--odm_texturing-textureResolution',
metavar='<positive integer>',
default=4096,
type=int,
help=('The resolution of the output textures. Must be '
'greater than textureWithSize. Default: %(default)s'))
parser.add_argument('--odm_texturing-textureResolution',
metavar='<positive integer>',
default=4096,
type=int,
help=('The resolution of the output textures. Must be '
'greater than textureWithSize. Default: %(default)s'))
parser.add_argument('--odm_texturing-textureWithSize',
metavar='<positive integer>',
default=3600,
type=int,
help=('The resolution to rescale the images performing '
'the texturing. Default: %(default)s'))
parser.add_argument('--odm_texturing-textureWithSize',
metavar='<positive integer>',
default=3600,
type=int,
help=('The resolution to rescale the images performing '
'the texturing. Default: %(default)s'))
parser.add_argument('--odm_georeferencing-gcpFile',
metavar='<path string>',
default='gcp_list.txt',
help=('path to the file containing the ground control '
'points used for georeferencing. Default: '
'%(default)s. The file needs to '
'be on the following line format: \neasting '
'northing height pixelrow pixelcol imagename'))
parser.add_argument('--odm_georeferencing-gcpFile',
metavar='<path string>',
default='gcp_list.txt',
help=('path to the file containing the ground control '
'points used for georeferencing. Default: '
'%(default)s. The file needs to '
'be on the following line format: \neasting '
'northing height pixelrow pixelcol imagename'))
parser.add_argument('--odm_georeferencing-useGcp',
action = 'store_true',
default = False,
help = 'Enabling GCPs from the file above. The GCP file '
parser.add_argument('--odm_georeferencing-useGcp',
action='store_true',
default=False,
help='Enabling GCPs from the file above. The GCP file '
'is not used by default.')
parser.add_argument('--odm_orthophoto-resolution',
metavar='<float > 0.0>',
default=20.0,
type=float,
help=('Orthophoto ground resolution in pixels/meter'
'Default: %(default)s'))
parser.add_argument('--odm_orthophoto-resolution',
metavar='<float > 0.0>',
default=20.0,
type=float,
help=('Orthophoto ground resolution in pixels/meter'
'Default: %(default)s'))
parser.add_argument('--zip-results',
action='store_true',
default=False,
help='compress the results using gunzip')
parser.add_argument('--zip-results',
action='store_true',
default=False,
help='compress the results using gunzip')
args = vars(parser.parse_args())
parser.add_argument('--time',
action='store_true',
default=False,
help='Generates a benchmark file with runtime info\n'
'Default: %(default)s')
return parser.parse_args()

5
opendm/context.py
Wyświetl plik

@ -7,7 +7,8 @@ scripts_path = os.path.abspath(os.path.dirname(__file__))
root_path, _ = os.path.split(scripts_path)
superbuild_path = os.path.join(root_path, 'SuperBuild')
ccd_widths_path = os.path.join(root_path, 'data/ccd_defs.json')
tests_path = os.path.join(root_path, 'tests')
tests_data_path = os.path.join(root_path, 'tests/test_data')
# add opencv to python path
pyopencv_path = os.path.join(superbuild_path, 'install/lib/python2.7/dist-packages')
@ -15,6 +16,7 @@ sys.path.append(pyopencv_path)
# define opensfm path
opensfm_path = os.path.join(superbuild_path, "src/opensfm")
ccd_widths_path = os.path.join(opensfm_path, 'opensfm/data/sensor_data.json')
# define orb_slam2 path
orb_slam2_path = os.path.join(superbuild_path, "src/orb_slam2")
@ -26,6 +28,7 @@ pmvs2_path = os.path.join(superbuild_path, "install/bin/pmvs2")
# define txt2las path
txt2las_path = os.path.join(superbuild_path, 'src/las-tools/bin')
pdal_path = os.path.join(superbuild_path, 'build/pdal/bin')
# define odm modules path
odm_modules_path = os.path.join(root_path, "build/bin")

11
opendm/io.py
Wyświetl plik

@ -1,25 +1,32 @@
import os
def get_files_list(path_dir):
return os.listdir(path_dir)
def absolute_path_file(path_file):
return os.path.abspath(path_file)
def extract_file_from_path_file(path_file):
path, file = os.path.split(path_file)
return file
def extract_path_from_file(file):
path_file = os.path.abspath(os.path.dirname(file))
path, file = os.path.split(path_file)
return path
def join_paths(path1, path2):
return os.path.join(path1, path2)
def file_exists(path_file):
return os.path.isfile(path_file)
return os.path.isfile(path_file)
def dir_exists(dirname):
return os.path.isdir(dirname)
return os.path.isdir(dirname)

31
opendm/log.py
Wyświetl plik

@ -1,3 +1,5 @@
import logging
HEADER = '\033[95m'
OKBLUE = '\033[94m'
OKGREEN = '\033[92m'
@ -5,14 +7,33 @@ WARNING = '\033[93m'
FAIL = '\033[91m'
ENDC = '\033[0m'
# TODO add file handling
logging.addLevelName(logging.INFO, '%s[%s]' % (OKBLUE, logging.getLevelName(logging.INFO)))
logging.addLevelName(logging.WARNING, '%s[%s]' % (WARNING, logging.getLevelName(logging.WARNING)))
logging.addLevelName(logging.ERROR, '%s[%s]' % (FAIL, logging.getLevelName(logging.ERROR)))
logging.addLevelName(logging.DEBUG, '%s[%s]' % (OKGREEN, logging.getLevelName(logging.DEBUG)))
logging.basicConfig(level=logging.DEBUG,
format='%(levelname)-14s %(message)s' + ENDC)
def ODM_INFO(str):
print OKBLUE + '[INFO] ' + str + ENDC
logging.info(str)
def ODM_WARNING(str):
print WARNING + '[WARNING] ' + str + ENDC
logging.warning(str)
def ODM_ERROR(str):
print FAIL + '[ERROR] ' + str + ENDC
logging.error(str)
def ODM_EXCEPTION(str):
logging.exception(str)
def ODM_DEBUG(str):
print OKGREEN + '[DEBUG] ' + str + ENDC
logging.debug(str)

55
opendm/system.py
Wyświetl plik

@ -4,14 +4,17 @@ import json
import datetime
import sys
import subprocess
import string
from opendm import context
from opendm import log
def get_ccd_widths():
"""Return the CCD Width of the camera listed in the JSON defs file."""
with open(context.ccd_widths_path) as jsonFile:
return json.load(jsonFile)
with open(context.ccd_widths_path) as f:
sensor_data = json.loads(f.read())
return dict(zip(map(string.lower, sensor_data.keys()), sensor_data.values()))
def run(cmd):
"""Run a system command"""
@ -19,14 +22,31 @@ def run(cmd):
returnCode = os.system(cmd)
if (returnCode != 0):
# TODO(edgar): add as log.ODM_ERROR
sys.exit("\nquitting cause: \n\t" + cmd + "\nreturned with code " +
log.ODM_ERROR("quitting cause: \n\t" + cmd + "\nreturned with code " +
str(returnCode) + ".\n")
sys.exit('An error occurred. Check stdout above or the logs.')
def now():
"""Return the current time"""
return datetime.datetime.now().strftime('%a %b %d %H:%M:%S %Z %Y')
def now_raw():
return datetime.datetime.now()
def benchmark(start, benchmarking_file, process):
"""
runs a benchmark with a start datetime object
:return: the running time (delta)
"""
# Write to benchmark file
delta = (datetime.datetime.now() - start).total_seconds()
with open(benchmarking_file, 'a') as b:
b.write('%s runtime: %s seconds\n' % (process, delta))
def run_and_return(cmdSrc, cmdDest=None):
"""Run a system command and return the output"""
process = subprocess.Popen(cmdSrc, stdout=subprocess.PIPE, shell=True)
@ -35,8 +55,8 @@ def run_and_return(cmdSrc, cmdDest=None):
def mkdir_p(path):
'''Make a directory including parent directories.
'''
"""Make a directory including parent directories.
"""
try:
os.makedirs(path)
except os.error as exc:
@ -50,26 +70,3 @@ def calculate_EPSG(utmZone, south):
return 32700 + utmZone
else:
return 32600 + utmZone
def parse_coordinate_system():
"""Write attributes to jobOptions from coord file"""
if os.path.isfile(jobOptions['jobDir'] +
'/odm_georeferencing/coordFile.txt'):
with open(jobOptions['jobDir'] + '/odm_georeferencing/coordFile.txt') as f:
for lineNumber, line in enumerate(f):
if lineNumber == 0:
tokens = line.split(' ')
if len(tokens) == 3:
utmZoneString = tokens[2][0:len(tokens[2])-2].strip()
utmSouthBool = (tokens[2][len(tokens[2])-2].strip() == 'S')
jobOptions['csString'] = '+datum=WGS84 +proj=utm +zone=' \
+ utmZoneString + (' +south' if utmSouthBool else '')
jobOptions['epsg'] = calculate_EPSG(int(utmZoneString), utmSouthBool)
elif lineNumber == 1:
tokens = line.split(' ')
if len(tokens) == 2:
jobOptions['utmEastOffset'] = int(tokens[0].strip())
jobOptions['utmNorthOffset'] = int(tokens[1].strip())
else:
break

229
opendm/tasks.py
Wyświetl plik

@ -8,143 +8,144 @@ from scripts.resize import resize
from scripts.opensfm import opensfm
# Define pipeline tasks
tasks_dict = { '1': 'resize',
'2': 'opensfm',
'3': 'cmvs',
'4': 'pmvs',
'5': 'odm_meshing',
'6': 'odm_texturing',
'7': 'odm_georeferencing',
'8': 'odm_orthophoto',
'9': 'zip_results' }
tasks_dict = {'1': 'resize',
'2': 'opensfm',
'3': 'cmvs',
'4': 'pmvs',
'5': 'odm_meshing',
'6': 'odm_texturing',
'7': 'odm_georeferencing',
'8': 'odm_orthophoto',
'9': 'zip_results'}
class ODMTaskManager(object):
"""docstring for ODMTaskManager"""
def __init__(self, odm_app):
self.odm_app = odm_app
self.initial_task_id = 0
self.current_task_id = 0
self.final_task_id = len(tasks_dict)
self.tasks = self.init_tasks(tasks_dict, self.odm_app)
"""docstring for ODMTaskManager"""
def init_tasks(self, _tasks_dict, _odm_app):
# dict to store tasks objects
tasks = {}
# loop over tasks dict
for key, in _tasks_dict:
# instantiate and append ODMTask
task_name = _tasks_dict[key]
tasks[key] = ODMTask(key, task_name)
def __init__(self, odm_app):
self.odm_app = odm_app
self.initial_task_id = 0
self.current_task_id = 0
self.final_task_id = len(tasks_dict)
self.tasks = self.init_tasks(tasks_dict, self.odm_app)
# setup tasks
if task_name == 'resize':
# setup this task
command = resize
inputs = { 'project_path': _odm_app.project_path,
'args': _odm_app.args,
'photos': _odm_app.photos }
def init_tasks(self, _tasks_dict, _odm_app):
# dict to store tasks objects
tasks = {}
# loop over tasks dict
for key, in _tasks_dict:
# instantiate and append ODMTask
task_name = _tasks_dict[key]
tasks[key] = ODMTask(key, task_name)
elif task_name == 'opensfm':
# setup this task
command = opensfm
inputs = { 'project_path': _odm_app.project_path,
'args': _odm_app.args,
'photos': _odm_app.photos }
# setup tasks
if task_name == 'resize':
# setup this task
command = resize
inputs = {'project_path': _odm_app.project_path,
'args': _odm_app.args,
'photos': _odm_app.photos}
elif task_name == 'cmvs':
# setup this task
command = None
inputs = {}
elif task_name == 'opensfm':
# setup this task
command = opensfm
inputs = {'project_path': _odm_app.project_path,
'args': _odm_app.args,
'photos': _odm_app.photos}
elif task_name == 'pmvs':
# setup this task
command = None
inputs = {}
elif task_name == 'cmvs':
# setup this task
command = None
inputs = {}
elif task_name == 'odm_meshing':
# setup this task
command = None
inputs = {}
elif task_name == 'pmvs':
# setup this task
command = None
inputs = {}
elif task_name == 'odm_texturing':
# setup this task
command = None
inputs = {}
elif task_name == 'odm_meshing':
# setup this task
command = None
inputs = {}
elif task_name == 'odm_georeferencing':
# setup this task
command = None
inputs = {}
elif task_name == 'odm_texturing':
# setup this task
command = None
inputs = {}
elif task_name == 'odm_orthophoto':
# setup this task
command = None
inputs = {}
elif task_name == 'odm_georeferencing':
# setup this task
command = None
inputs = {}
elif task_name == 'zip_results':
# setup this task
command = None
inputs = {}
elif task_name == 'odm_orthophoto':
# setup this task
command = None
inputs = {}
else:
log.ODM_ERROR('task_name %s is not valid' % task_name)
elif task_name == 'zip_results':
# setup this task
command = None
inputs = {}
# setup task configuration
task = tasks[key]
task.command = command
task.inputs = inputs
else:
log.ODM_ERROR('task_name %s is not valid' % task_name)
return tasks
# setup task configuration
task = tasks[key]
task.command = command
task.inputs = inputs
def run_tasks(self):
return tasks
#curr_task = self.tasks['resize']
def run_tasks(self):
#self.tasks['resize']
# curr_task = self.tasks['resize']
for id in range(self.initial_task_id, self.final_task_id + 1):
# catch task with current id
task = self.tasks[str(id)]
# update task tracking
log.ODM_INFO('Running task %s: %s' % (task.id, task.name))
self.current_task_id = task.id
# run task
task.state = task.run()
if task.state == 2:
log.ODM_INFO('Succeeded task %s: %s - %s' % (task.id, task.name, system.now()))
else:
log.ODM_ERROR('Aborted task %s: %s' % (task.id, task.name))
# self.tasks['resize']
for id in range(self.initial_task_id, self.final_task_id + 1):
# catch task with current id
task = self.tasks[str(id)]
# update task tracking
log.ODM_INFO('Running task %s: %s' % (task.id, task.name))
self.current_task_id = task.id
# run task
task.state = task.run()
if task.state == 2:
log.ODM_INFO('Succeeded task %s: %s - %s' % (task.id, task.name, system.now()))
else:
log.ODM_ERROR('Aborted task %s: %s' % (task.id, task.name))
class ODMTask(object):
"""docstring for ODMTask"""
def __init__(self, id, name):
# task definition
self.id = id
self.name = name
# task i/o
self.command = None
self.inputs = {}
# Current task state (0:waiting, 1:running, 2:succeded: 3:failed)
# By default we set a task in waiting state
self.state = 0
"""docstring for ODMTask"""
# Launch task
def run(self):
# while doing something
self.state = 1
return self.launch_command()
def __init__(self, id, name):
# task definition
self.id = id
self.name = name
# task i/o
self.command = None
self.inputs = {}
# Current task state (0:waiting, 1:running, 2:succeded: 3:failed)
# By default we set a task in waiting state
self.state = 0
def launch_command(self):
if self.command is None:
log.ODM_ERROR('Call method for task %s not defined' % self.name)
return 3 # failed
# run conmmand
try:
succeed = self.command(**self.inputs)
return 2 if succeed else 3 # 2:succeed, 3:failed
except Exception, e:
log.ODM_ERROR(str(e))
return 3 # failed
# Launch task
def run(self):
# while doing something
self.state = 1
return self.launch_command()
def launch_command(self):
if self.command is None:
log.ODM_ERROR('Call method for task %s not defined' % self.name)
return 3 # failed
# run conmmand
try:
succeed = self.command(**self.inputs)
return 2 if succeed else 3 # 2:succeed, 3:failed
except Exception, e:
log.ODM_ERROR(str(e))
return 3 # failed

278
opendm/types.py
Wyświetl plik

@ -1,18 +1,19 @@
import os
import cv2
import pyexiv2
import subprocess
import re
from fractions import Fraction
from opensfm.exif import sensor_string
import log
import io
import system
import context
class ODM_Photo:
""" ODMPhoto - a class for ODMPhotos
"""
def __init__(self, path_file, force_focal, force_ccd):
# general purpose
self.path_file = path_file
@ -26,14 +27,15 @@ class ODM_Photo:
# other attributes
self.camera_make = None
self.camera_model = None
self.make_model = None
# parse values from metadata
self.parse_pyexiv2_values(self.path_file, force_focal, force_ccd)
# compute focal lenght into pixels
# compute focal length into pixels
self.update_focal()
# print log message
log.ODM_DEBUG('Loaded %s | dimensions: %s x %s | focal: %s | ccd: %s' % \
(self.filename, self.width, self.height, self.focal_length, self.ccd_width))
log.ODM_DEBUG('Loaded %s | camera: %s | dimensions: %s x %s | focal: %s | ccd: %s' %
(self.filename, self.make_model, self.width, self.height, self.focal_length, self.ccd_width))
def update_focal(self):
# compute focal length in pixels
@ -59,36 +61,46 @@ class ODM_Photo:
try:
val = metadata[key].value
# parse tag names
if key == 'Exif.Image.Make': self.camera_make = val
elif key == 'Exif.Image.Model': self.camera_model = val
elif key == 'Exif.Photo.FocalLength': self.focal_length = float(val)
except Exception, e:
if key == 'Exif.Image.Make':
self.camera_make = val
elif key == 'Exif.Image.Model':
self.camera_model = val
elif key == 'Exif.Photo.FocalLength':
self.focal_length = float(val)
except (pyexiv2.ExifValueError, ValueError) as e:
pass
self.make_model = sensor_string(self.camera_make, self.camera_model)
# needed to do that since sometimes metadata contains wrong data
img = cv2.imread(_path_file)
self.width = img.shape[1]
self.height = img.shape[0]
# force focal and ccd_width with user parameter
if _force_focal: self.focal_length = _force_focal
if _force_ccd: self.ccd_width = _force_ccd
if _force_focal:
self.focal_length = _force_focal
if _force_ccd:
self.ccd_width = _force_ccd
# find ccd_width from file if needed
if self.ccd_width is None and self.camera_model is not None:
# load ccd_widths from file
ccd_widths = system.get_ccd_widths()
# search ccd by camera model
key = [x for x in ccd_widths.keys() if self.camera_model in x]
key = [x for x in ccd_widths.keys() if self.make_model in x]
# convert to float if found
if key: self.ccd_width = float(ccd_widths[key[0]])
# else:
# log.ODM_ERROR('Could not find ccd_width in file')
if key:
self.ccd_width = float(ccd_widths[key[0]])
else:
log.ODM_WARNING('Could not find ccd_width in file. Use --force-ccd or edit the sensor_data.json '
'file to manually input ccd width')
# TODO: finish this class
class ODM_Reconstruction(object):
"""docstring for ODMReconstruction"""
def __init__(self, arg):
super(ODMReconstruction, self).__init__()
self.arg = arg
@ -96,6 +108,7 @@ class ODM_Reconstruction(object):
class ODM_GCPoint(object):
"""docstring for ODMPoint"""
def __init__(self, x, y, z):
self.x = x
self.y = y
@ -104,6 +117,7 @@ class ODM_GCPoint(object):
class ODM_GeoRef(object):
"""docstring for ODMUtmZone"""
def __init__(self):
self.datum = 'WGS84'
self.epsg = None
@ -123,40 +137,86 @@ class ODM_GeoRef(object):
log.ODM_ERROR('Unknown pole format %s' % _pole)
return
def coord_to_fractions(self, coord, refs):
deg_dec = abs(float(coord))
deg = int(deg_dec)
minute_dec = (deg_dec-deg)*60
minute = int(minute_dec)
def convert_to_las(self, _file):
sec_dec = (minute_dec-minute)*60
sec_dec = round(sec_dec,3)
sec_denominator = 1000
sec_numerator = int(sec_dec*sec_denominator)
if float(coord) >= 0:
latRef = refs[0]
else:
latRef = refs[1]
output = str(deg) + '/1 ' + str(minute) + '/1 ' + str(sec_numerator) + '/' + str(sec_denominator)
return output, latRef
def convert_to_las(self, _file, pdalXML):
if not self.epsg:
log.ODM_ERROR('Empty EPSG: Could not convert to LAS')
return
kwargs = { 'bin': context.txt2las_path,
'f_in': _file,
'f_out': _file + '.laz',
'east': self.utm_east_offset,
'north': self.utm_north_offset,
'epsg': self.epsg }
kwargs = {'bin': context.pdal_path,
'f_in': _file,
'f_out': _file + '.las',
'east': self.utm_east_offset,
'north': self.utm_north_offset,
'epsg': self.epsg,
'xml': pdalXML}
# call txt2las
system.run('{bin}/txt2las -i {f_in} -o {f_out} -skip 30 -parse xyzRGBssss ' \
'-set_scale 0.01 0.01 0.01 -set_offset {east} {north} 0 ' \
'-translate_xyz 0 -epsg {epsg}'.format(**kwargs))
# system.run('{bin}/txt2las -i {f_in} -o {f_out} -skip 30 -parse xyzRGBssss ' \
# '-set_scale 0.01 0.01 0.01 -set_offset {east} {north} 0 ' \
# '-translate_xyz 0 -epsg {epsg}'.format(**kwargs))
#
# create pipeline file transform.xml to enable transformation
pipelineXml = '<?xml version=\"1.0\" encoding=\"utf-8\"?>'
pipelineXml += '<Pipeline version=\"1.0\">'
pipelineXml += ' <Writer type=\"writers.las\">'
pipelineXml += ' <Option name=\"filename\">'
pipelineXml += ' transformed.las'
pipelineXml += ' </Option>'
pipelineXml += ' <Filter type=\"filters.transformation\">'
pipelineXml += ' <Option name=\"matrix\">'
pipelineXml += ' 1 0 0 {east}'.format(**kwargs)
pipelineXml += ' 0 1 0 {north}'.format(**kwargs)
pipelineXml += ' 0 0 1 0'
pipelineXml += ' 0 0 0 1'
pipelineXml += ' </Option>'
pipelineXml += ' <Reader type=\"readers.ply\">'
pipelineXml += ' <Option name=\"filename\">'
pipelineXml += ' untransformed.ply'
pipelineXml += ' </Option>'
pipelineXml += ' </Reader>'
pipelineXml += ' </Filter>'
pipelineXml += ' </Writer>'
pipelineXml += '</Pipeline>'
with open(pdalXML, 'w') as f:
f.write(pipelineXml)
# call pdal
system.run('{bin}/pdal pipeline -i {xml} --readers.ply.filename={f_in} '
'--writers.las.filename={f_out}'.format(**kwargs))
def utm_to_latlon(self, _file, _photo, idx):
gcp = self.gcps[idx]
kwargs = { 'datum': self.datum,
'zone': self.utm_zone,
'file': _file,
'x': gcp.x + self.utm_east_offset,
'y': gcp.y + self.utm_north_offset,
'z': gcp.z }
kwargs = {'epsg': self.epsg,
'file': _file,
'x': gcp.x + self.utm_east_offset,
'y': gcp.y + self.utm_north_offset,
'z': gcp.z}
latlon = system.run_and_return('echo {x} {y} | cs2cs +proj=utm ' \
'+datum={datum} +ellps={datum} +zone={zone} +units=m +to ' \
'+proj=latlon +ellps={datum}'.format(**kwargs)).split()
latlon = system.run_and_return('echo {x} {y} {z} '.format(**kwargs),
'gdaltransform -s_srs \"EPSG:{epsg}\" '
'-t_srs \"EPSG:4326\"'.format(**kwargs)).split()
# Example: 83d18'16.285"W
# Example: 41d2'11.789"N
@ -169,104 +229,110 @@ class ODM_GeoRef(object):
alt_str = ''
else:
log.ODM_ERROR('Something went wrong %s' % latlon)
tokens = re.split("[d '\"]+", lon_str)
if len(tokens) >= 4:
lon_deg, lon_min, lon_sec = tokens[:3]
lon_sec_frac = Fraction(lon_sec)
lon_sec_numerator = str(lon_sec_frac._numerator)
lon_sec_denominator = str(lon_sec_frac._denominator)
lon_ref = tokens[3]
tokens = re.split("[d '\"]+", lat_str)
if len(tokens) >= 4:
lat_deg, lat_min, lat_sec = tokens[:3]
lat_sec_frac = Fraction(lat_sec)
lat_sec_numerator = str(lat_sec_frac._numerator)
lat_sec_denominator = str(lat_sec_frac._denominator)
lat_ref = tokens[3]
alt_numerator = arc_denominator = 0 # BUG: arc_denominator is never used
if alt_str:
alt_frac = Fraction(alt_str)
alt_numerator = alt_frac._numerator
alt_denominator = alt_frac._denominator
lat_frac = self.coord_to_fractions(latlon[1], ['N', 'S'])
lon_frac = self.coord_to_fractions(latlon[0], ['E', 'W'])
# read image metadata
metadata = pyexiv2.ImageMetadata(_photo.path_file)
metadata.read()
## set values
# set values
# GPS latitude
key = 'Exif.GPSInfo.GPSLatitude'
value = [Fraction(int(lat_deg), 1), Fraction(int(lat_min), 1), \
Fraction(int(lat_sec_numerator), int(lat_sec_denominator))]
metadata[key] = pyexiv2.ExifTag(key, value)
value = lat_frac[0].split(' ')
log.ODM_DEBUG('lat_frac: %s %s %s' % (value[0], value[1], value[2]))
metadata[key] = pyexiv2.ExifTag(key,
[Fraction(value[0]),
Fraction(value[1]),
Fraction(value[2])])
key = 'Exif.GPSInfo.GPSLatitudeRef'
value = '%s' % lat_ref
value = lat_frac[1]
metadata[key] = pyexiv2.ExifTag(key, value)
# GPS longitude
key = 'Exif.GPSInfo.GPSLongitude'
value = [Fraction(int(lon_deg), 1), Fraction(int(lon_min), 1), \
Fraction(int(lon_sec_numerator), int(lon_sec_denominator))]
metadata[key] = pyexiv2.ExifTag(key, value)
value = lon_frac[0].split(' ')
metadata[key] = pyexiv2.ExifTag(key,
[Fraction(value[0]),
Fraction(value[1]),
Fraction(value[2])])
key = 'Exif.GPSInfo.GPSLongitudeRef'
value = '%s' % lon_ref
value = lon_frac[1]
metadata[key] = pyexiv2.ExifTag(key, value)
# GPS altitude
altitude = abs(int(float(latlon[2])*100))
key = 'Exif.GPSInfo.GPSAltitude'
value = Fraction(int(gcp.z), 1)
value = Fraction(altitude, 1)
metadata[key] = pyexiv2.ExifTag(key, value)
if latlon[2] >= 0:
altref = '0'
else:
altref = '1'
key = 'Exif.GPSInfo.GPSAltitudeRef'
metadata[key] = pyexiv2.ExifTag(key, '0')
metadata[key] = pyexiv2.ExifTag(key, altref)
## write values
# write values
metadata.write()
def parse_coordinate_system(self, _file):
"""Write attributes to jobOptions from coord file"""
# check for coordinate file existence
if not io.file_exists(_file):
log.ODM_ERROR('Could not find file %s' % _coords_file)
log.ODM_ERROR('Could not find file %s' % _file)
return
with open(_file) as f:
# extract reference system and utm zone from first line.
# We will assume the following format:
# 'WGS84 UTM 17N'
line = f.readline().split(' ')
self.datum = line[0]
self.utm_pole = line[2][len(line)-1]
self.utm_zone = int(line[2][:len(line)-1])
# extract east and west offsets from second line.
# We will assume the following format:
# '440143 4588391'
line = f.readline().split(' ')
self.utm_east_offset = int(line[0])
self.utm_north_offset = int(line[1])
line = f.readline()
log.ODM_DEBUG('Line: %s' % line)
ref = line.split(' ')
# match_wgs_utm = re.search('WGS84 UTM (\d{1,2})(N|S)', line, re.I)
if ref[0] == 'WGS84' and ref[1] == 'UTM': # match_wgs_utm:
self.datum = ref[0]
self.utm_pole = ref[2][len(ref) - 1]
self.utm_zone = int(ref[2][:len(ref) - 1])
# extract east and west offsets from second line.
# We will assume the following format:
# '440143 4588391'
# update EPSG
self.epsg = self.calculate_EPSG(self.utm_zone, self.utm_pole)
# If the first line looks like "EPSG:n" or "epsg:n"
elif ref[0].split(':')[0].lower() == 'epsg':
self.epsg = line.split(':')[1]
else:
log.ODM_ERROR('Could not parse coordinates. Bad CRS supplied: %s' % line)
return
offsets = f.readline().split(' ')
self.utm_east_offset = int(offsets[0])
self.utm_north_offset = int(offsets[1])
# parse coordinates
lines = f.readlines()
for l in lines:
x, y, z = l.split(' ')[:3]
xyz = l.split(' ')
if len(xyz) == 3:
x, y, z = xyz[:3]
elif len(xyz) == 2:
x, y = xyz[:2]
z = 0
self.gcps.append(ODM_GCPoint(float(x), float(y), float(z)))
# update EPSG
self.epsg = self.calculate_EPSG(self.utm_zone, self.utm_pole)
class ODM_Tree(object):
def __init__(self, root_path):
### root path to the project
# root path to the project
self.root_path = io.absolute_path_file(root_path)
### modules paths
# modules paths
# here are defined where all modules should be located in
# order to keep track all files al directories during the
@ -279,9 +345,13 @@ class ODM_Tree(object):
self.odm_texturing = io.join_paths(self.root_path, 'odm_texturing')
self.odm_georeferencing = io.join_paths(self.root_path, 'odm_georeferencing')
self.odm_orthophoto = io.join_paths(self.root_path, 'odm_orthophoto')
self.odm_pdal = io.join_paths(self.root_path, 'pdal')
# important files paths
# benchmarking
self.benchmarking = io.join_paths(self.root_path, 'benchmark.txt')
### important files paths
# opensfm
self.opensfm_bundle = io.join_paths(self.opensfm, 'bundle_r000.out')
self.opensfm_bundle_list = io.join_paths(self.opensfm, 'list_r000.out')
@ -294,11 +364,11 @@ class ODM_Tree(object):
self.pmvs_visdat = io.join_paths(self.pmvs_rec_path, 'vis.dat')
self.pmvs_options = io.join_paths(self.pmvs_rec_path, 'pmvs_options.txt')
self.pmvs_model = io.join_paths(self.pmvs_rec_path, 'models/option-0000.ply')
# odm_meshing
self.odm_mesh = io.join_paths(self.odm_meshing, 'odm_mesh.ply')
self.odm_meshing_log = io.join_paths(self.odm_meshing, 'odm_meshing_log.txt')
# odm_texturing
self.odm_texturing_undistorted_image_path = io.join_paths(
self.odm_texturing, 'undistorted')
@ -306,14 +376,6 @@ class ODM_Tree(object):
self.odm_texturing, 'odm_textured_model.obj')
self.odm_textured_model_mtl = io.join_paths(
self.odm_texturing, 'odm_textured_model.mtl')
self.odm_textured_model_txt_geo = io.join_paths(
self.odm_texturing, 'odm_textured_model_geo.txt')
self.odm_textured_model_ply_geo = io.join_paths(
self.odm_texturing, 'odm_textured_model_geo.ply')
self.odm_textured_model_obj_geo = io.join_paths(
self.odm_texturing, 'odm_textured_model_geo.obj')
self.odm_textured_model_mtl_geo = io.join_paths(
self.odm_texturing, 'odm_textured_model_geo.mtl')
self.odm_texuring_log = io.join_paths(
self.odm_texturing, 'odm_texturing_log.txt')
@ -328,14 +390,22 @@ class ODM_Tree(object):
self.odm_georeferencing, 'odm_georeferencing_utm_log.txt')
self.odm_georeferencing_log = io.join_paths(
self.odm_georeferencing, 'odm_georeferencing_log.txt')
self.odm_georeferencing_model_txt_geo = io.join_paths(
self.odm_georeferencing, 'odm_georeferencing_model_geo.txt')
self.odm_georeferencing_model_ply_geo = io.join_paths(
self.odm_georeferencing, 'odm_georeferenced_model.ply')
self.odm_georeferencing_model_obj_geo = io.join_paths(
self.odm_texturing, 'odm_textured_model_geo.obj') # these files will be kept in odm_texturing/
self.odm_georeferencing_model_mtl_geo = io.join_paths(
self.odm_texturing, 'odm_textured_model_geo.mtl') # these files will be kept in odm_texturing/
self.odm_georeferencing_xyz_file = io.join_paths(
self.odm_georeferencing, 'odm_georeferenced_model.csv')
self.odm_georeferencing_pdal = io.join_paths(
self.odm_georeferencing, 'pipeline.xml')
# odm_orthophoto
self.odm_orthophoto_file = io.join_paths(self.odm_orthophoto, 'odm_orthophoto.png')
self.odm_orthophoto_tif = io.join_paths(self.odm_orthophoto, 'odm_orthophoto.tif')
self.odm_orthophoto_corners = io.join_paths(self.odm_orthophoto, 'odm_orthphoto_corners.txt')
self.odm_orthophoto_log = io.join_paths(self.odm_orthophoto, 'odm_orthophoto_log.txt')
self.odm_orthophoto_tif_log = io.join_paths(self.odm_orthophoto, 'gdal_translate_log.txt')

38
run.py
Wyświetl plik

@ -9,28 +9,32 @@ import ecto
from scripts.odm_app import ODMApp
def usage():
log.ODM_ERROR('USAGE: %s --project-path [project_path]' % sys.argv[0])
log.ODM_ERROR('OpenDroneMap app finished - %s' % system.now())
sys.exit(0)
log.ODM_ERROR('USAGE: %s --project-path [project_path]' % sys.argv[0])
log.ODM_ERROR('OpenDroneMap app finished - %s' % system.now())
sys.exit(0)
if __name__ == '__main__':
log.ODM_INFO('Initializing OpenDroneMap app - %s' % system.now())
log.ODM_INFO('Initializing OpenDroneMap app - %s' % system.now())
# Force to provide the images path
if config.args.get('project_path') is None:
usage()
args = config.config()
# create an instance of my App BlackBox
# internally configure all tasks
app = ODMApp(args=config.args)
# Force to provide the images path
if args.project_path is None:
usage()
# create a plasm that only contains the BlackBox
plasm = ecto.Plasm()
plasm.insert(app)
# create an instance of my App BlackBox
# internally configure all tasks
app = ODMApp(args=args)
# execute the plasm
plasm.execute(niter=1)
# create a plasm that only contains the BlackBox
plasm = ecto.Plasm()
plasm.insert(app)
log.ODM_INFO('OpenDroneMap app finished - %s' % system.now())
# execute the plasm
plasm.execute(niter=1)
log.ODM_INFO('OpenDroneMap app finished - %s' % system.now())

7
run.sh 100755
Wyświetl plik

@ -0,0 +1,7 @@
#!/bin/bash
RUNPATH="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
export PYTHONPATH=$RUNPATH/SuperBuild/install/lib/python2.7/dist-packages:$RUNPATH/SuperBuild/src/opensfm:$PYTHONPATH
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$RUNPATH/SuperBuild/install/lib
python $RUNPATH/run.py "$@"

24
scripts/cmvs.py
Wyświetl plik

@ -5,6 +5,7 @@ from opendm import log
from opendm import system
from opendm import context
class ODMCmvsCell(ecto.Cell):
def declare_params(self, params):
@ -20,19 +21,25 @@ class ODMCmvsCell(ecto.Cell):
outputs.declare("reconstruction", "list of ODMReconstructions", [])
def process(self, inputs, outputs):
# Benchmarking
start_time = system.now_raw()
log.ODM_INFO('Running OMD CMVS Cell')
log.ODM_INFO('Running ODM CMVS Cell')
# get inputs
args = self.inputs.args
tree = self.inputs.tree
# check if we rerun cell or not
rerun_cell = args['rerun'] is not None \
and args['rerun'] == 'cmvs'
rerun_cell = (args.rerun is not None and
args.rerun == 'cmvs') or \
(args.rerun_all) or \
(args.rerun_from is not None and
'cmvs' in args.rerun_from)
if not io.file_exists(tree.pmvs_bundle) or rerun_cell:
log.ODM_DEBUG('Writting CMVS vis in: %s' % tree.pmvs_bundle)
log.ODM_DEBUG('Writing CMVS vis in: %s' % tree.pmvs_bundle)
# copy bundle file to pmvs dir
from shutil import copyfile
@ -50,7 +57,10 @@ class ODMCmvsCell(ecto.Cell):
system.run('{bin} {prefix}/ {max_images} {cores}'.format(**kwargs))
else:
log.ODM_WARNING('Found a valid CMVS file in: %s' %
(tree.pmvs_bundle))
tree.pmvs_bundle)
log.ODM_INFO('Running OMD CMVS Cell - Finished')
return ecto.OK if args['end_with'] != 'cmvs' else ecto.QUIT
if args.time:
system.benchmark(start_time, tree.benchmarking, 'CMVS')
log.ODM_INFO('Running ODM CMVS Cell - Finished')
return ecto.OK if args.end_with != 'cmvs' else ecto.QUIT

7
scripts/dataset.py
Wyświetl plik

@ -6,13 +6,14 @@ from opendm import io
from opendm import types
from opendm import log
class ODMLoadDatasetCell(ecto.Cell):
def declare_params(self, params):
params.declare("force_focal", 'Override the focal length information for the '
'images', None)
'images', None)
params.declare("force_ccd", 'Override the ccd widht information for the '
'images', None)
'images', None)
def declare_io(self, params, inputs, outputs):
inputs.declare("tree", "Struct with paths", [])
@ -65,4 +66,4 @@ class ODMLoadDatasetCell(ecto.Cell):
outputs.photos = photos
log.ODM_INFO('Running ODM Load Dataset Cell - Finished')
return ecto.OK
return ecto.OK

161
scripts/odm_app.py
Wyświetl plik

@ -1,8 +1,11 @@
import ecto
import os
from opendm import context
from opendm import types
from opendm import config
from opendm import io
from opendm import system
from dataset import ODMLoadDatasetCell
from resize import ODMResizeCell
@ -15,11 +18,14 @@ from odm_texturing import ODMTexturingCell
from odm_georeferencing import ODMGeoreferencingCell
from odm_orthophoto import ODMOrthoPhotoCell
class ODMApp(ecto.BlackBox):
''' ODMApp - a class for ODM Activities
'''
"""ODMApp - a class for ODM Activities
"""
def __init__(self, *args, **kwargs):
ecto.BlackBox.__init__(self, *args, **kwargs)
self.tree = None
@staticmethod
def declare_direct_params(p):
@ -31,107 +37,114 @@ class ODMApp(ecto.BlackBox):
Implement the virtual function from the base class
Only cells from which something is forwarded have to be declared
"""
cells = { 'args': ecto.Constant(value=p.args),
'dataset': ODMLoadDatasetCell(force_focal=p.args['force_focal'],
force_ccd=p.args['force_ccd']),
'resize': ODMResizeCell(resize_to=p.args['resize_to']),
'opensfm': ODMOpenSfMCell(use_exif_size=False,
feature_process_size=p.args['resize_to'],
feature_min_frames=p.args['min_num_features'],
processes=context.num_cores,
matching_gps_neighbors=p.args['matcher_neighbors'],
matching_gps_distance=p.args['matcher_distance']),
'slam': ODMSlamCell(),
'cmvs': ODMCmvsCell(max_images=p.args['cmvs_maxImages']),
'pmvs': ODMPmvsCell(level=p.args['pmvs_level'],
csize=p.args['pmvs_csize'],
thresh=p.args['pmvs_threshold'],
wsize=p.args['pmvs_wsize'],
min_imgs=p.args['pmvs_minImageNum'],
cores=p.args['pmvs_num_cores']),
'meshing': ODMeshingCell(max_vertex=p.args['odm_meshing_maxVertexCount'],
oct_tree=p.args['odm_meshing_octreeDepth'],
samples=p.args['odm_meshing_samplesPerNode'],
solver=p.args['odm_meshing_solverDivide']),
'texturing': ODMTexturingCell(resize=p.args['resize_to'],
resolution=p.args['odm_texturing_textureResolution'],
size=p.args['odm_texturing_textureWithSize']),
'georeferencing': ODMGeoreferencingCell(img_size=p.args['resize_to'],
gcp_file=p.args['odm_georeferencing_gcpFile'],
use_gcp=p.args['odm_georeferencing_useGcp']),
'orthophoto': ODMOrthoPhotoCell(resolution=p.args['odm_orthophoto_resolution'])
cells = {'args': ecto.Constant(value=p.args),
'dataset': ODMLoadDatasetCell(force_focal=p.args.force_focal,
force_ccd=p.args.force_ccd),
'resize': ODMResizeCell(resize_to=p.args.resize_to),
'opensfm': ODMOpenSfMCell(use_exif_size=False,
feature_process_size=p.args.resize_to,
feature_min_frames=p.args.min_num_features,
processes=context.num_cores,
matching_gps_neighbors=p.args.matcher_neighbors,
matching_gps_distance=p.args.matcher_distance),
'slam': ODMSlamCell(),
'cmvs': ODMCmvsCell(max_images=p.args.cmvs_maxImages),
'pmvs': ODMPmvsCell(level=p.args.pmvs_level,
csize=p.args.pmvs_csize,
thresh=p.args.pmvs_threshold,
wsize=p.args.pmvs_wsize,
min_imgs=p.args.pmvs_minImageNum,
cores=p.args.pmvs_num_cores),
'meshing': ODMeshingCell(max_vertex=p.args.odm_meshing_maxVertexCount,
oct_tree=p.args.odm_meshing_octreeDepth,
samples=p.args.odm_meshing_samplesPerNode,
solver=p.args.odm_meshing_solverDivide),
'texturing': ODMTexturingCell(resize=p.args.resize_to,
resolution=p.args.odm_texturing_textureResolution,
size=p.args.odm_texturing_textureWithSize),
'georeferencing': ODMGeoreferencingCell(img_size=p.args.resize_to,
gcp_file=p.args.odm_georeferencing_gcpFile,
use_gcp=p.args.odm_georeferencing_useGcp),
'orthophoto': ODMOrthoPhotoCell(resolution=p.args.odm_orthophoto_resolution)
}
}
return cells
return cells
def configure(self, p, _i, _o):
tree = types.ODM_Tree(p.args['project_path'])
tree = types.ODM_Tree(p.args.project_path)
self.tree = ecto.Constant(value=tree)
# TODO(dakota) put this somewhere better maybe
if p.args.time and io.file_exists(tree.benchmarking):
# Delete the previously made file
os.remove(tree.benchmarking)
with open(tree.benchmarking, 'a') as b:
b.write('ODM Benchmarking file created %s\nNumber of Cores: %s\n\n' % (system.now(), context.num_cores))
def connections(self, _p):
run_slam = _p.args.get('video') is not None
# define initial task
initial_task = _p.args['start_with']
initial_task_id = config.processopts.index(initial_task)
# TODO: What is this?
# initial_task = _p.args['start_with']
# initial_task_id = config.processopts.index(initial_task)
## define the connections like you would for the plasm
# define the connections like you would for the plasm
connections = []
if run_slam:
# run slam cell
connections += [ self.tree[:] >> self.slam['tree'],
self.args[:] >> self.slam['args'] ]
connections += [self.tree[:] >> self.slam['tree'],
self.args[:] >> self.slam['args']]
# run cmvs
connections += [ self.tree[:] >> self.cmvs['tree'],
self.args[:] >> self.cmvs['args'],
self.slam['reconstruction'] >> self.cmvs['reconstruction'] ]
connections += [self.tree[:] >> self.cmvs['tree'],
self.args[:] >> self.cmvs['args'],
self.slam['reconstruction'] >> self.cmvs['reconstruction']]
else:
# load the dataset
connections = [ self.tree[:] >> self.dataset['tree'] ]
connections = [self.tree[:] >> self.dataset['tree']]
# run resize cell
connections += [ self.tree[:] >> self.resize['tree'],
self.args[:] >> self.resize['args'],
self.dataset['photos'] >> self.resize['photos'] ]
connections += [self.tree[:] >> self.resize['tree'],
self.args[:] >> self.resize['args'],
self.dataset['photos'] >> self.resize['photos']]
# run opensfm with images from load dataset
connections += [ self.tree[:] >> self.opensfm['tree'],
self.args[:] >> self.opensfm['args'],
self.resize['photos'] >> self.opensfm['photos'] ]
connections += [self.tree[:] >> self.opensfm['tree'],
self.args[:] >> self.opensfm['args'],
self.resize['photos'] >> self.opensfm['photos']]
# run cmvs
connections += [ self.tree[:] >> self.cmvs['tree'],
self.args[:] >> self.cmvs['args'],
self.opensfm['reconstruction'] >> self.cmvs['reconstruction'] ]
connections += [self.tree[:] >> self.cmvs['tree'],
self.args[:] >> self.cmvs['args'],
self.opensfm['reconstruction'] >> self.cmvs['reconstruction']]
# run pmvs
connections += [ self.tree[:] >> self.pmvs['tree'],
self.args[:] >> self.pmvs['args'],
self.cmvs['reconstruction'] >> self.pmvs['reconstruction'] ]
connections += [self.tree[:] >> self.pmvs['tree'],
self.args[:] >> self.pmvs['args'],
self.cmvs['reconstruction'] >> self.pmvs['reconstruction']]
# create odm mesh
connections += [ self.tree[:] >> self.meshing['tree'],
self.args[:] >> self.meshing['args'],
self.pmvs['reconstruction'] >> self.meshing['reconstruction'] ]
connections += [self.tree[:] >> self.meshing['tree'],
self.args[:] >> self.meshing['args'],
self.pmvs['reconstruction'] >> self.meshing['reconstruction']]
# create odm texture
connections += [ self.tree[:] >> self.texturing['tree'],
self.args[:] >> self.texturing['args'],
self.meshing['reconstruction'] >> self.texturing['reconstruction'] ]
connections += [self.tree[:] >> self.texturing['tree'],
self.args[:] >> self.texturing['args'],
self.meshing['reconstruction'] >> self.texturing['reconstruction']]
if not run_slam:
# create odm georeference
connections += [ self.tree[:] >> self.georeferencing['tree'],
self.args[:] >> self.georeferencing['args'],
self.dataset['photos'] >> self.georeferencing['photos'],
self.texturing['reconstruction'] >> self.georeferencing['reconstruction'] ]
connections += [self.tree[:] >> self.georeferencing['tree'],
self.args[:] >> self.georeferencing['args'],
self.dataset['photos'] >> self.georeferencing['photos'],
self.texturing['reconstruction'] >> self.georeferencing['reconstruction']]
## create odm orthophoto
connections += [ self.tree[:] >> self.orthophoto['tree'],
self.args[:] >> self.orthophoto['args'],
self.georeferencing['reconstruction'] >> self.orthophoto['reconstruction'] ]
# create odm orthophoto
connections += [self.tree[:] >> self.orthophoto['tree'],
self.args[:] >> self.orthophoto['args'],
self.georeferencing['reconstruction'] >> self.orthophoto['reconstruction']]
return connections

261
scripts/odm_georeferencing.py
Wyświetl plik

@ -1,4 +1,5 @@
import ecto
import csv
from opendm import io
from opendm import log
@ -6,6 +7,7 @@ from opendm import types
from opendm import system
from opendm import context
class ODMGeoreferencingCell(ecto.Cell):
def declare_params(self, params):
params.declare("gcp_file", 'path to the file containing the ground control '
@ -23,12 +25,15 @@ class ODMGeoreferencingCell(ecto.Cell):
outputs.declare("reconstruction", "list of ODMReconstructions", [])
def process(self, inputs, outputs):
# Benchmarking
start_time = system.now_raw()
log.ODM_INFO('Running OMD Georeferencing Cell')
log.ODM_INFO('Running ODM Georeferencing Cell')
# get inputs
args = self.inputs.args
tree = self.inputs.tree
gcpfile = io.join_paths(tree.root_path, self.params.gcp_file)
# define paths and create working directories
system.mkdir_p(tree.odm_georeferencing)
@ -38,229 +43,107 @@ class ODMGeoreferencingCell(ecto.Cell):
if not self.params.use_gcp and \
not io.file_exists(tree.odm_georeferencing_coords):
log.ODM_WARNING('Warning: No coordinates file. ' \
'Generating coordinates file in: %s' % tree.odm_georeferencing_coords)
log.ODM_WARNING('Warning: No coordinates file. '
'Generating coordinates file in: %s'
% tree.odm_georeferencing_coords)
try:
# odm_georeference definitions
kwargs = {
'bin': context.odm_modules_path,
'imgs': tree.dataset_resize,
'imgs': tree.dataset_raw,
'imgs_list': tree.opensfm_bundle_list,
'coords': tree.odm_georeferencing_coords,
'log': tree.odm_georeferencing_utm_log
}
# run UTM extraction binary
system.run('{bin}/odm_extract_utm -imagesPath {imgs}/ ' \
'-imageListFile {imgs_list} -outputCoordFile {coords} ' \
'-logFile {log}'.format(**kwargs))
system.run('{bin}/odm_extract_utm -imagesPath {imgs}/ '
'-imageListFile {imgs_list} -outputCoordFile {coords} '
'-logFile {log}'.format(**kwargs))
except Exception, e:
log.ODM_ERROR('Could not generate GCP file from images metadata.' \
'Consider rerunning with argument --odm_georeferencing-useGcp' \
' and provide a proper GCP file')
log.ODM_ERROR('Could not generate GCP file from images metadata.'
'Consider rerunning with argument --odm_georeferencing-useGcp'
' and provide a proper GCP file')
log.ODM_ERROR(e)
return ecto.QUIT
# check if we rerun cell or not
rerun_cell = args['rerun'] is not None \
and args['rerun'] == 'odm_georeferencing'
rerun_cell = (args.rerun is not None and
args.rerun == 'odm_georeferencing') or \
(args.rerun_all) or \
(args.rerun_from is not None and
'odm_georeferencing' in args.rerun_from)
if not io.file_exists(tree.odm_textured_model_obj_geo) or \
not io.file_exists(tree.odm_textured_model_ply_geo) or rerun_cell:
if not io.file_exists(tree.odm_georeferencing_model_obj_geo) or \
not io.file_exists(tree.odm_georeferencing_model_ply_geo) or rerun_cell:
# odm_georeference definitions
kwargs = {
'bin': context.odm_modules_path,
'bundle': tree.opensfm_bundle,
'imgs': tree.dataset_resize,
'imgs': tree.dataset_raw,
'imgs_list': tree.opensfm_bundle_list,
'model': tree.odm_textured_model_obj,
'pc': tree.pmvs_model,
'log': tree.odm_georeferencing_log,
'coords': tree.odm_georeferencing_coords,
'pc_geo': tree.odm_textured_model_ply_geo,
'geo_sys': tree.odm_textured_model_txt_geo,
'model_geo': tree.odm_textured_model_obj_geo,
'pc_geo': tree.odm_georeferencing_model_ply_geo,
'geo_sys': tree.odm_georeferencing_model_txt_geo,
'model_geo': tree.odm_georeferencing_model_obj_geo,
'size': self.params.img_size,
'gcp': io.join_paths(tree.root_path, self.params.gcp_file),
'gcp': gcpfile,
}
if self.params.use_gcp and \
io.file_exists(tree.odm_georeferencing_coords):
io.file_exists(gcpfile):
system.run('{bin}/odm_georef -bundleFile {bundle} -inputCoordFile {coords} ' \
'-bundleResizedTo {size} -inputFile {model} -outputFile {model_geo} ' \
'-inputPointCloudFile {pc} -outputPointCloudFile {pc_geo} ' \
'-logFile {log} -georefFileOutputPath {geo_sys} -gcpFile {gcp} ' \
'-outputCoordFile {coords}'.format(**kwargs))
system.run('{bin}/odm_georef -bundleFile {bundle} -imagesPath {imgs} -imagesListPath {imgs_list} '
'-bundleResizedTo {size} -inputFile {model} -outputFile {model_geo} '
'-inputPointCloudFile {pc} -outputPointCloudFile {pc_geo} '
'-logFile {log} -georefFileOutputPath {geo_sys} -gcpFile {gcp} '
'-outputCoordFile {coords}'.format(**kwargs))
else:
system.run('{bin}/odm_georef -bundleFile {bundle} -inputCoordFile {coords} ' \
'-inputFile {model} -outputFile {model_geo} ' \
'-inputPointCloudFile {pc} -outputPointCloudFile {pc_geo} ' \
'-logFile {log} -georefFileOutputPath {geo_sys}'.format(**kwargs))
system.run('{bin}/odm_georef -bundleFile {bundle} -inputCoordFile {coords} '
'-inputFile {model} -outputFile {model_geo} '
'-inputPointCloudFile {pc} -outputPointCloudFile {pc_geo} '
'-logFile {log} -georefFileOutputPath {geo_sys}'.format(**kwargs))
# update images metadata
geo_ref = types.ODM_GeoRef()
geo_ref.parse_coordinate_system(tree.odm_georeferencing_coords)
for idx, photo in enumerate(self.inputs.photos):
geo_ref.utm_to_latlon(tree.odm_georeferencing_latlon, photo, idx)
# convert ply model to LAS reference system
geo_ref.convert_to_las(tree.odm_georeferencing_model_ply_geo,
tree.odm_georeferencing_pdal)
# XYZ point cloud output
log.ODM_INFO("Creating geo-referenced CSV file (XYZ format, can be used with GRASS to create DEM)")
with open(tree.odm_georeferencing_xyz_file, "wb") as csvfile:
csvfile_writer = csv.writer(csvfile, delimiter=",")
reachedpoints = False
with open(tree.odm_georeferencing_model_ply_geo) as f:
for lineNumber, line in enumerate(f):
if reachedpoints:
tokens = line.split(" ")
csv_line = [float(tokens[0])+geo_ref.utm_east_offset,
float(tokens[1])+geo_ref.utm_north_offset,
tokens[2]]
csvfile_writer.writerow(csv_line)
if line.startswith("end_header"):
reachedpoints = True
csvfile.close()
else:
log.ODM_WARNING('Found a valid georeferenced model in: %s' \
% tree.odm_textured_model_ply_geo)
log.ODM_WARNING('Found a valid georeferenced model in: %s'
% tree.odm_georeferencing_model_ply_geo)
if args.time:
system.benchmark(start_time, tree.benchmarking, 'Georeferencing')
# update images metadata
geo_ref = types.ODM_GeoRef()
geo_ref.parse_coordinate_system(tree.odm_georeferencing_coords)
for idx, photo in enumerate(self.inputs.photos):
geo_ref.utm_to_latlon(tree.odm_georeferencing_latlon, photo, idx)
# convert ply model to LAS reference system
geo_ref.convert_to_las(tree.odm_textured_model_ply_geo)
log.ODM_INFO('Running OMD Georeferencing Cell - Finished')
return ecto.OK if args['end_with'] != 'odm_georeferencing' else ecto.QUIT
def odm_georeferencing():
"""Run odm_georeferencing"""
print "\n - running georeferencing - " + now()
os.chdir(jobOptions["jobDir"])
try:
os.mkdir(jobOptions["jobDir"] + "/odm_georeferencing")
except:
pass
if not args.odm_georeferencing_useGcp:
run("\"" + BIN_PATH + "/odm_extract_utm\" -imagesPath " + jobOptions["srcDir"] + "/ -imageListFile " \
+ jobOptions["jobDir"] + "/pmvs/list.rd.txt -outputCoordFile " + jobOptions["jobDir"] \
+ "/odm_georeferencing/coordFile.txt")
run("\"" + BIN_PATH + "/odm_georef\" -bundleFile " + jobOptions["jobDir"] \
+ "/pmvs/bundle.rd.out -inputCoordFile " + jobOptions["jobDir"] \
+ "/odm_georeferencing/coordFile.txt -inputFile " + jobOptions["jobDir"] \
+ "-results/odm_texturing/odm_textured_model.obj -outputFile " + jobOptions["jobDir"] \
+ "-results/odm_texturing/odm_textured_model_geo.obj -inputPointCloudFile " \
+ jobOptions["jobDir"] + "-results/option-0000.ply -outputPointCloudFile " + jobOptions["jobDir"] \
+ "-results/option-0000_georef.ply -logFile " + jobOptions["jobDir"] \
+ "/odm_georeferencing/odm_georeferencing_log.txt -georefFileOutputPath " + jobOptions["jobDir"] \
+ "-results/odm_texturing/odm_textured_model_geo_georef_system.txt")
elif os.path.isfile(jobOptions["srcDir"] + "/" + args.odm_georeferencing_gcpFile):
run("\"" + BIN_PATH + "/odm_georef\" -bundleFile " + jobOptions["jobDir"] \
+ "/pmvs/bundle.rd.out -gcpFile " + jobOptions["srcDir"] + "/" + args.odm_georeferencing_gcpFile \
+ " -imagesPath " + jobOptions["srcDir"] + "/ -imagesListPath " + jobOptions["jobDir"] \
+ "/pmvs/list.rd.txt -bundleResizedTo " + str(jobOptions["resizeTo"]) + " -inputFile " \
+ jobOptions["jobDir"] + "-results/odm_texturing/odm_textured_model.obj -outputFile " \
+ jobOptions["jobDir"] + "-results/odm_texturing/odm_textured_model_geo.obj -outputCoordFile " \
+ jobOptions["jobDir"] + "/odm_georeferencing/coordFile.txt -inputPointCloudFile " \
+ jobOptions["jobDir"] + "-results/option-0000.ply -outputPointCloudFile " + jobOptions["jobDir"] \
+ "-results/option-0000_georef.ply -logFile " + jobOptions["jobDir"] \
+ "/odm_georeferencing/odm_georeferencing_log.txt -georefFileOutputPath " + jobOptions["jobDir"] \
+ "-results/odm_texturing/odm_textured_model_geo_georef_system.txt")
else:
print "Warning: No GCP file. Consider rerunning with argument --odm_georeferencing-useGcp false --start-with odm_georeferencing"
print "Skipping orthophoto"
args.end_with = "odm_georeferencing"
if "csString" not in jobOptions:
parse_coordinate_system()
if "csString" in jobOptions and "utmEastOffset" in jobOptions and "utmNorthOffset" in jobOptions:
images = []
with open(jobOptions["jobDir"] + "/pmvs/list.rd.txt") as f:
images = f.readlines()
if len(images) > 0:
with open(jobOptions["jobDir"] + "/odm_georeferencing/coordFile.txt") as f:
for lineNumber, line in enumerate(f):
if lineNumber >= 2 and lineNumber - 2 < len(images):
tokens = line.split(' ')
if len(tokens) >= 3:
x = float(tokens[0])
y = float(tokens[1])
z = float(tokens[2])
filename = images[lineNumber - 2]
run("echo " + str(x + jobOptions["utmEastOffset"]) + " " \
+ str(y + jobOptions["utmNorthOffset"]) + " " + str(z) \
+ " | cs2cs " + jobOptions["csString"] + " +to +datum=WGS84 +proj=latlong > " \
+ jobOptions["jobDir"] + "/odm_georeferencing/latlong.txt")
with open(jobOptions["jobDir"] + "/odm_georeferencing/latlong.txt") as latlongFile:
latlongLine = latlongFile.readline()
tokens = latlongLine.split()
if len(tokens) >= 2:
exifGpsInfoWritten = False
lonString = tokens[0] # Example: 83d18'16.285"W
latString = tokens[1] # Example: 41d2'11.789"N
altString = ""
if len(tokens) > 2:
altString = tokens[2] # Example: 0.998
tokens = re.split("[d '\"]+", lonString)
if len(tokens) >= 4:
lonDeg = tokens[0]
lonMin = tokens[1]
lonSec = tokens[2]
lonSecFrac = fractions.Fraction(lonSec)
lonSecNumerator = str(lonSecFrac._numerator)
lonSecDenominator = str(lonSecFrac._denominator)
lonRef = tokens[3]
tokens = re.split("[d '\"]+", latString)
if len(tokens) >= 4:
latDeg = tokens[0]
latMin = tokens[1]
latSec = tokens[2]
latSecFrac = fractions.Fraction(latSec)
latSecNumerator = str(latSecFrac._numerator)
latSecDenominator = str(latSecFrac._denominator)
latRef = tokens[3]
exivCmd = "exiv2 -q"
exivCmd += " -M\"set Exif.GPSInfo.GPSLatitude " + latDeg + "/1 " \
+ latMin + "/1 " + latSecNumerator + "/" + latSecDenominator + "\""
exivCmd += " -M\"set Exif.GPSInfo.GPSLatitudeRef " + latRef + "\""
exivCmd += " -M\"set Exif.GPSInfo.GPSLongitude " + lonDeg + "/1 " \
+ lonMin + "/1 " + lonSecNumerator + "/" + lonSecDenominator + "\""
exivCmd += " -M\"set Exif.GPSInfo.GPSLongitudeRef " + lonRef + "\""
altNumerator = arcDenominator = 0 # BUG: arcDenominator is never used
if altString:
altFrac = fractions.Fraction(altString)
altNumerator = str(altFrac._numerator)
altDenominator = str(altFrac._denominator)
exivCmd += " -M\"set Exif.GPSInfo.GPSAltitude " + altNumerator + "/" + altDenominator + "\""
exivCmd += " -M\"set Exif.GPSInfo.GPSAltitudeRef 0\""
exivCmd += " " + filename
run(exivCmd)
exifGpsInfoWritten = True
if not exifGpsInfoWritten:
print(" Warning: Failed setting EXIF GPS info for " \
+ filename + " based on " + latlongLine)
if "epsg" in jobOptions and "utmEastOffset" in jobOptions and "utmNorthOffset" in jobOptions:
lasCmd = "\"" + BIN_PATH + "/txt2las\" -i " + jobOptions["jobDir"] + \
"-results/option-0000_georef.ply -o " + jobOptions["jobDir"] \
+ "-results/pointcloud_georef.laz -skip 30 -parse xyzRGBssss -set_scale 0.01 0.01 0.01 -set_offset " \
+ str(jobOptions["utmEastOffset"]) + " " + str(jobOptions["utmNorthOffset"]) + " 0 -translate_xyz " \
+ str(jobOptions["utmEastOffset"]) + " " + str(jobOptions["utmNorthOffset"]) \
+ " 0 -epsg " + str(jobOptions["epsg"])
print(" Creating geo-referenced LAS file (expecting warning)...")
run(lasCmd)
if args['--end-with'] != "odm_georeferencing":
odm_orthophoto()
log.ODM_INFO('Running ODM Georeferencing Cell - Finished')
return ecto.OK if args.end_with != 'odm_georeferencing' else ecto.QUIT

55
scripts/odm_meshing.py
Wyświetl plik

@ -5,20 +5,20 @@ from opendm import io
from opendm import system
from opendm import context
class ODMeshingCell(ecto.Cell):
class ODMeshingCell(ecto.Cell):
def declare_params(self, params):
params.declare("max_vertex", 'The maximum vertex count of the output '
'mesh', 100000)
'mesh', 100000)
params.declare("oct_tree", 'Oct-tree depth used in the mesh reconstruction, '
'increase to get more vertices, recommended '
'values are 8-12', 9)
'increase to get more vertices, recommended '
'values are 8-12', 9)
params.declare("samples", 'Number of points per octree node, recommended '
'value: 1.0', 1)
'value: 1.0', 1)
params.declare("solver", 'Oct-tree depth at which the Laplacian equation '
'is solved in the surface reconstruction step. '
'Increasing this value increases computation '
'times slightly but helps reduce memory usage.', 9)
'is solved in the surface reconstruction step. '
'Increasing this value increases computation '
'times slightly but helps reduce memory usage.', 9)
def declare_io(self, params, inputs, outputs):
inputs.declare("tree", "Struct with paths", [])
@ -27,8 +27,11 @@ class ODMeshingCell(ecto.Cell):
outputs.declare("reconstruction", "Clusters output. list of ODMReconstructions", [])
def process(self, inputs, outputs):
log.ODM_INFO('Running OMD Meshing Cell')
# Benchmarking
start_time = system.now_raw()
log.ODM_INFO('Running ODM Meshing Cell')
# get inputs
args = self.inputs.args
@ -38,11 +41,14 @@ class ODMeshingCell(ecto.Cell):
system.mkdir_p(tree.odm_meshing)
# check if we rerun cell or not
rerun_cell = args['rerun'] is not None \
and args['rerun'] == 'odm_meshing'
rerun_cell = (args.rerun is not None and
args.rerun == 'odm_meshing') or \
(args.rerun_all) or \
(args.rerun_from is not None and
'odm_meshing' in args.rerun_from)
if not io.file_exists(tree.odm_mesh) or rerun_cell:
log.ODM_DEBUG('Writting ODM Mesh file in: %s' % tree.odm_mesh)
log.ODM_DEBUG('Writing ODM Mesh file in: %s' % tree.odm_mesh)
kwargs = {
'bin': context.odm_modules_path,
@ -52,17 +58,20 @@ class ODMeshingCell(ecto.Cell):
'max_vertex': self.params.max_vertex,
'oct_tree': self.params.oct_tree,
'samples': self.params.samples,
'solver':self.params.solver
'solver': self.params.solver
}
# run meshing binary
system.run('{bin}/odm_meshing -inputFile {infile} ' \
'-outputFile {outfile} -logFile {log} ' \
'-maxVertexCount {max_vertex} -octreeDepth {oct_tree} ' \
'-samplesPerNode {samples} -solverDivide {solver}'.format(**kwargs))
system.run('{bin}/odm_meshing -inputFile {infile} '
'-outputFile {outfile} -logFile {log} '
'-maxVertexCount {max_vertex} -octreeDepth {oct_tree} '
'-samplesPerNode {samples} -solverDivide {solver}'.format(**kwargs))
else:
log.ODM_WARNING('Found a valid ODM Mesh file in: %s' %
(tree.odm_mesh))
log.ODM_INFO('Running OMD Meshing Cell - Finished')
return ecto.OK if args['end_with'] != 'odm_meshing' else ecto.QUIT
log.ODM_WARNING('Found a valid ODM Mesh file in: %s' %
tree.odm_mesh)
if args.time:
system.benchmark(start_time, tree.benchmarking, 'Meshing')
log.ODM_INFO('Running ODM Meshing Cell - Finished')
return ecto.OK if args.end_with != 'odm_meshing' else ecto.QUIT

122
scripts/odm_orthophoto.py
Wyświetl plik

@ -4,6 +4,8 @@ from opendm import io
from opendm import log
from opendm import system
from opendm import context
from opendm import types
class ODMOrthoPhotoCell(ecto.Cell):
def declare_params(self, params):
@ -16,6 +18,9 @@ class ODMOrthoPhotoCell(ecto.Cell):
def process(self, inputs, outputs):
# Benchmarking
start_time = system.now_raw()
log.ODM_INFO('Running OMD OrthoPhoto Cell')
# get inputs
@ -26,78 +31,75 @@ class ODMOrthoPhotoCell(ecto.Cell):
system.mkdir_p(tree.odm_orthophoto)
# check if we rerun cell or not
rerun_cell = args['rerun'] is not None \
and args['rerun'] == 'odm_orthophoto'
rerun_cell = (args.rerun is not None and
args.rerun == 'odm_orthophoto') or \
(args.rerun_all) or \
(args.rerun_from is not None and
'odm_orthophoto' in args.rerun_from)
if not io.file_exists(tree.odm_orthophoto_file) or rerun_cell:
# odm_georeference definitions
# odm_orthophoto definitions
kwargs = {
'bin': context.odm_modules_path,
'model_geo': tree.odm_textured_model_obj_geo,
'model_geo': tree.odm_georeferencing_model_obj_geo,
'log': tree.odm_orthophoto_log,
'ortho': tree.odm_orthophoto_file,
'corners': tree.odm_orthophoto_corners,
'res': self.params.resolution
}
# run odm_georeference
system.run('{bin}/odm_orthophoto -inputFile {model_geo} ' \
'-logFile {log} -outputFile {ortho} -resolution {res} ' \
'-outputCornerFile {corners}'.format(**kwargs))
# run odm_orthophoto
system.run('{bin}/odm_orthophoto -inputFile {model_geo} '
'-logFile {log} -outputFile {ortho} -resolution {res} '
'-outputCornerFile {corners}'.format(**kwargs))
# Create georeferenced GeoTiff
geotiffcreated = False
georef = types.ODM_GeoRef()
# creates the coord refs # TODO I don't want to have to do this twice- after odm_georef
georef.parse_coordinate_system(tree.odm_georeferencing_coords)
if georef.epsg and georef.utm_east_offset and georef.utm_north_offset:
ulx = uly = lrx = lry = 0.0
with open(tree.odm_orthophoto_corners) as f:
for lineNumber, line in enumerate(f):
if lineNumber == 0:
tokens = line.split(' ')
if len(tokens) == 4:
ulx = float(tokens[0]) + \
float(georef.utm_east_offset)
lry = float(tokens[1]) + \
float(georef.utm_north_offset)
lrx = float(tokens[2]) + \
float(georef.utm_east_offset)
uly = float(tokens[3]) + \
float(georef.utm_north_offset)
log.ODM_INFO('Creating GeoTIFF')
kwargs = {
'ulx': ulx,
'uly': uly,
'lrx': lrx,
'lry': lry,
'epsg': georef.epsg,
'png': tree.odm_orthophoto_file,
'tiff': tree.odm_orthophoto_tif,
'log': tree.odm_orthophoto_tif_log
}
system.run('gdal_translate -a_ullr {ulx} {uly} {lrx} {lry} '
'-a_srs \"EPSG:{epsg}\" {png} {tiff} > {log}'.format(**kwargs))
geotiffcreated = True
if not geotiffcreated:
log.ODM_WARNING('No geo-referenced orthophoto created due '
'to missing geo-referencing or corner coordinates.')
else:
log.ODM_WARNING('Found a valid orthophoto in: %s' % tree.odm_orthophoto_file)
log.ODM_INFO('Running OMD OrthoPhoto Cell - Finished')
return ecto.OK if args['end_with'] != 'odm_orthophoto' else ecto.QUIT
if args.time:
system.benchmark(start_time, tree.benchmarking, 'Orthophoto')
def odm_orthophoto():
"""Run odm_orthophoto"""
print "\n - running orthophoto generation - " + system.now()
os.chdir(jobOptions["jobDir"])
try:
os.mkdir(jobOptions["jobDir"] + "/odm_orthophoto")
except:
pass
run("\"" + BIN_PATH + "/odm_orthophoto\" -inputFile " + jobOptions["jobDir"] + \
"-results/odm_texturing/odm_textured_model_geo.obj -logFile " + jobOptions["jobDir"] \
+ "/odm_orthophoto/odm_orthophoto_log.txt -outputFile " + jobOptions["jobDir"] \
+ "-results/odm_orthphoto.png -resolution 20.0 -outputCornerFile " + jobOptions["jobDir"] \
+ "/odm_orthphoto_corners.txt")
if "csString" not in jobOptions:
parse_coordinate_system()
geoTiffCreated = False
if ("csString" in jobOptions and
"utmEastOffset" in jobOptions and "utmNorthOffset" in jobOptions):
ulx = uly = lrx = lry = 0.0
with open(jobOptions["jobDir"] +
"/odm_orthphoto_corners.txt") as f:
for lineNumber, line in enumerate(f):
if lineNumber == 0:
tokens = line.split(' ')
if len(tokens) == 4:
ulx = float(tokens[0]) + \
float(jobOptions["utmEastOffset"])
lry = float(tokens[1]) + \
float(jobOptions["utmNorthOffset"])
lrx = float(tokens[2]) + \
float(jobOptions["utmEastOffset"])
uly = float(tokens[3]) + \
float(jobOptions["utmNorthOffset"])
print(" Creating GeoTIFF...")
sys.stdout.write(" ")
run("gdal_translate -a_ullr " + str(ulx) + " " + str(uly) + " " +
str(lrx) + " " + str(lry) + " -a_srs \"" + jobOptions["csString"] +
"\" " + jobOptions["jobDir"] + "-results/odm_orthphoto.png " +
jobOptions["jobDir"] + "-results/odm_orthphoto.tif")
geoTiffCreated = True
if not geoTiffCreated:
print " Warning: No geo-referenced orthophoto created due to missing geo-referencing or corner coordinates."
log.ODM_INFO('Running ODM OrthoPhoto Cell - Finished')
return ecto.OK if args.end_with != 'odm_orthophoto' else ecto.QUIT

47
scripts/odm_texturing.py
Wyświetl plik

@ -7,14 +7,14 @@ from opendm import io
from opendm import system
from opendm import context
class ODMTexturingCell(ecto.Cell):
class ODMTexturingCell(ecto.Cell):
def declare_params(self, params):
params.declare("resize", 'resizes images by the largest side', 2400)
params.declare("resolution", 'The resolution of the output textures. Must be '
'greater than textureWithSize.', 4096)
'greater than textureWithSize.', 4096)
params.declare("size", 'The resolution to rescale the images performing '
'the texturing.', 3600)
'the texturing.', 3600)
def declare_io(self, params, inputs, outputs):
inputs.declare("tree", "Struct with paths", [])
@ -23,8 +23,11 @@ class ODMTexturingCell(ecto.Cell):
outputs.declare("reconstruction", "Clusters output. list of ODMReconstructions", [])
def process(self, inputs, outputs):
log.ODM_INFO('Running OMD Texturing Cell')
# Benchmarking
start_time = system.now_raw()
log.ODM_INFO('Running ODM Texturing Cell')
# get inputs
args = self.inputs.args
@ -34,8 +37,11 @@ class ODMTexturingCell(ecto.Cell):
system.mkdir_p(tree.odm_texturing)
# check if we rerun cell or not
rerun_cell = args['rerun'] is not None \
and args['rerun'] == 'odm_texturing'
rerun_cell = (args.rerun is not None and
args.rerun == 'odm_texturing') or \
(args.rerun_all) or \
(args.rerun_from is not None and
'odm_texturing' in args.rerun_from)
# Undistort radial distortion
if not os.path.isdir(tree.odm_texturing_undistorted_image_path) or rerun_cell:
@ -60,8 +66,8 @@ class ODMTexturingCell(ecto.Cell):
(tree.opensfm_reconstruction))
if not io.file_exists(tree.odm_textured_model_obj) or rerun_cell:
log.ODM_DEBUG('Writting ODM Textured file in: %s' \
% tree.odm_textured_model_obj)
log.ODM_DEBUG('Writing ODM Textured file in: %s'
% tree.odm_textured_model_obj)
# odm_texturing definitions
kwargs = {
@ -78,14 +84,17 @@ class ODMTexturingCell(ecto.Cell):
}
# run texturing binary
system.run('{bin}/odm_texturing -bundleFile {bundle} ' \
'-imagesPath {imgs_path} -imagesListPath {imgs_list} ' \
'-inputModelPath {model} -outputFolder {out_dir}/ ' \
'-textureResolution {resolution} -bundleResizedTo {resize} ' \
'-textureWithSize {size} -logFile {log}'.format(**kwargs))
system.run('{bin}/odm_texturing -bundleFile {bundle} '
'-imagesPath {imgs_path} -imagesListPath {imgs_list} '
'-inputModelPath {model} -outputFolder {out_dir}/ '
'-textureResolution {resolution} -bundleResizedTo {resize} '
'-textureWithSize {size} -logFile {log}'.format(**kwargs))
else:
log.ODM_WARNING('Found a valid ODM Texture file in: %s' \
% tree.odm_textured_model_obj)
log.ODM_INFO('Running OMD Texturing Cell - Finished')
return ecto.OK if args['end_with'] != 'odm_texturing' else ecto.QUIT
log.ODM_WARNING('Found a valid ODM Texture file in: %s'
% tree.odm_textured_model_obj)
if args.time:
system.benchmark(start_time, tree.benchmarking, 'Texturing')
log.ODM_INFO('Running ODM Texturing Cell - Finished')
return ecto.OK if args.end_with != 'odm_texturing' else ecto.QUIT

51
scripts/opensfm.py
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@ -5,6 +5,7 @@ from opendm import io
from opendm import system
from opendm import context
class ODMOpenSfMCell(ecto.Cell):
def declare_params(self, params):
params.declare("use_exif_size", "The application arguments.", False)
@ -22,7 +23,10 @@ class ODMOpenSfMCell(ecto.Cell):
def process(self, inputs, outputs):
log.ODM_INFO('Running OMD OpenSfm Cell')
# Benchmarking
start_time = system.now_raw()
log.ODM_INFO('Running ODM OpenSfM Cell')
# get inputs
tree = self.inputs.tree
@ -30,7 +34,7 @@ class ODMOpenSfMCell(ecto.Cell):
photos = self.inputs.photos
if not photos:
log.ODM_ERROR('Not enough photos in photos array to start OpenSfm')
log.ODM_ERROR('Not enough photos in photos array to start OpenSfM')
return ecto.QUIT
# create working directories
@ -38,11 +42,13 @@ class ODMOpenSfMCell(ecto.Cell):
system.mkdir_p(tree.pmvs)
# check if we rerun cell or not
rerun_cell = args['rerun'] is not None \
and args['rerun'] == 'opensfm'
rerun_cell = (args.rerun is not None and
args.rerun == 'opensfm') or \
(args.rerun_all) or \
(args.rerun_from is not None and
'opensfm' in args.rerun_from)
### check if reconstruction was done before
# check if reconstruction was done before
if not io.file_exists(tree.opensfm_reconstruction) or rerun_cell:
# create file list
@ -60,7 +66,7 @@ class ODMOpenSfMCell(ecto.Cell):
"matching_gps_neighbors: %s" % self.params.matching_gps_neighbors
]
if args['matcher_distance']>0:
if args.matcher_distance > 0:
config.append("matching_gps_distance: %s" % self.params.matching_gps_distance)
# write config file
@ -69,32 +75,33 @@ class ODMOpenSfMCell(ecto.Cell):
fout.write("\n".join(config))
# run OpenSfM reconstruction
system.run('PYTHONPATH=%s %s/bin/run_all %s' %
(context.pyopencv_path, context.opensfm_path, tree.opensfm))
system.run('PYTHONPATH=%s %s/bin/run_all %s' %
(context.pyopencv_path, context.opensfm_path, tree.opensfm))
else:
log.ODM_WARNING('Found a valid OpenSfm file in: %s' %
(tree.opensfm_reconstruction))
log.ODM_WARNING('Found a valid OpenSfM file in: %s' %
tree.opensfm_reconstruction)
### check if reconstruction was exported to bundler before
# check if reconstruction was exported to bundler before
if not io.file_exists(tree.opensfm_bundle_list) or rerun_cell:
# convert back to bundler's format
system.run('PYTHONPATH=%s %s/bin/export_bundler %s' %
(context.pyopencv_path, context.opensfm_path, tree.opensfm))
(context.pyopencv_path, context.opensfm_path, tree.opensfm))
else:
log.ODM_WARNING('Found a valid Bundler file in: %s' %
(tree.opensfm_reconstruction))
log.ODM_WARNING('Found a valid Bundler file in: %s' %
tree.opensfm_reconstruction)
### check if reconstruction was exported to pmvs before
# check if reconstruction was exported to pmvs before
if not io.file_exists(tree.pmvs_visdat) or rerun_cell:
# run PMVS converter
system.run('PYTHONPATH=%s %s/bin/export_pmvs %s --output %s' %
(context.pyopencv_path, context.opensfm_path, tree.opensfm, tree.pmvs))
system.run('PYTHONPATH=%s %s/bin/export_pmvs %s --output %s' %
(context.pyopencv_path, context.opensfm_path, tree.opensfm, tree.pmvs))
else:
log.ODM_WARNING('Found a valid CMVS file in: %s' % tree.pmvs_visdat)
log.ODM_INFO('Running OMD OpenSfm Cell - Finished')
return ecto.OK if args['end_with'] != 'opensfm' else ecto.QUIT
if args.time:
system.benchmark(start_time, tree.benchmarking, 'OpenSfM')
log.ODM_INFO('Running ODM OpenSfM Cell - Finished')
return ecto.OK if args.end_with != 'opensfm' else ecto.QUIT

47
scripts/pmvs.py
Wyświetl plik

@ -5,26 +5,26 @@ from opendm import log
from opendm import system
from opendm import context
class ODMPmvsCell(ecto.Cell):
class ODMPmvsCell(ecto.Cell):
def declare_params(self, params):
params.declare("level", 'The level in the image pyramid that is used '
'for the computation', 1)
params.declare("csize", 'Cell size controls the density of reconstructions', 2)
params.declare("thresh", 'A patch reconstruction is accepted as a success '
'and kept, if its associcated photometric consistency '
'measure is above this threshold.', 0.7)
'and kept, if its associcated photometric consistency '
'measure is above this threshold.', 0.7)
params.declare("wsize", 'pmvs samples wsize x wsize pixel colors from '
'each image to compute photometric consistency '
'score. For example, when wsize=7, 7x7=49 pixel '
'colors are sampled in each image. Increasing the '
'value leads to more stable reconstructions, but '
'the program becomes slower.', 7)
'each image to compute photometric consistency '
'score. For example, when wsize=7, 7x7=49 pixel '
'colors are sampled in each image. Increasing the '
'value leads to more stable reconstructions, but '
'the program becomes slower.', 7)
params.declare("min_imgs", 'Each 3D point must be visible in at least '
'minImageNum images for being reconstructed. 3 is '
'suggested in general.', 3)
'minImageNum images for being reconstructed. 3 is '
'suggested in general.', 3)
params.declare("cores", 'The maximum number of cores to use in dense '
' reconstruction.', context.num_cores)
' reconstruction.', context.num_cores)
def declare_io(self, params, inputs, outputs):
inputs.declare("tree", "Struct with paths", [])
@ -33,7 +33,10 @@ class ODMPmvsCell(ecto.Cell):
outputs.declare("reconstruction", "list of ODMReconstructions", [])
def process(self, inputs, outputs):
# Benchmarking
start_time = system.now_raw()
log.ODM_INFO('Running OMD PMVS Cell')
# get inputs
@ -41,8 +44,11 @@ class ODMPmvsCell(ecto.Cell):
tree = self.inputs.tree
# check if we rerun cell or not
rerun_cell = args['rerun'] is not None \
and args['rerun'] == 'pmvs'
rerun_cell = (args.rerun is not None and
args.rerun == 'pmvs') or \
(args.rerun_all) or \
(args.rerun_from is not None and
'pmvs' in args.rerun_from)
if not io.file_exists(tree.pmvs_model) or rerun_cell:
log.ODM_DEBUG('Creating dense pointcloud in: %s' % tree.pmvs_model)
@ -59,15 +65,18 @@ class ODMPmvsCell(ecto.Cell):
}
# generate pmvs2 options
system.run('{bin} {prefix}/ {level} {csize} {thresh} {wsize} ' \
system.run('{bin} {prefix}/ {level} {csize} {thresh} {wsize} '
'{min_imgs} {cores}'.format(**kwargs))
# run pmvs2
system.run('%s %s/ option-0000' % \
(context.pmvs2_path, tree.pmvs_rec_path))
system.run('%s %s/ option-0000' %
(context.pmvs2_path, tree.pmvs_rec_path))
else:
log.ODM_WARNING('Found a valid PMVS file in %s' % tree.pmvs_model)
log.ODM_INFO('Running OMD PMVS Cell - Finished')
return ecto.OK if args['end_with'] != 'pmvs' else ecto.QUIT
if args.time:
system.benchmark(start_time, tree.benchmarking, 'PMVS')
log.ODM_INFO('Running ODM PMVS Cell - Finished')
return ecto.OK if args.end_with != 'pmvs' else ecto.QUIT

41
scripts/resize.py
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@ -7,7 +7,8 @@ from opendm import system
from opendm import io
from opendm import types
class ODMResizeCell(ecto.Cell):
class ODMResizeCell(ecto.Cell):
def declare_params(self, params):
params.declare("resize_to", "resizes images by the largest side", 2400)
@ -19,6 +20,9 @@ class ODMResizeCell(ecto.Cell):
def process(self, inputs, outputs):
# Benchmarking
start_time = system.now_raw()
log.ODM_INFO('Running ODM Resize Cell')
# get inputs
@ -29,15 +33,22 @@ class ODMResizeCell(ecto.Cell):
if not photos:
log.ODM_ERROR('Not enough photos in photos to resize')
return ecto.QUIT
if self.params.resize_to <= 0:
log.ODM_ERROR('Resize parameter must be greater than 0')
return ecto.QUIT
# create working directory
system.mkdir_p(tree.dataset_resize)
log.ODM_DEBUG('Resizing dataset to: %s' % tree.dataset_resize)
# check if we rerun cell or not
rerun_cell = args['rerun'] is not None \
and args['rerun'] == 'resize'
rerun_cell = (args.rerun is not None and
args.rerun == 'resize') or \
(args.rerun_all) or \
(args.rerun_from is not None and
'resize' in args.rerun_from)
# loop over photos
for photo in photos:
@ -53,6 +64,8 @@ class ODMResizeCell(ecto.Cell):
img = cv2.imread(path_file)
# compute new size
max_side = max(img.shape[0], img.shape[1])
if max_side <= self.params.resize_to:
log.ODM_WARNING('Resize Parameter is greater than the largest side of the image')
ratio = float(self.params.resize_to) / float(max_side)
img_r = cv2.resize(img, None, fx=ratio, fy=ratio)
# write image with opencv
@ -65,8 +78,8 @@ class ODMResizeCell(ecto.Cell):
# copy metadata
old_meta.copy(new_meta)
# update metadata size
new_meta['Exif.Photo.PixelXDimension'].value = img_r.shape[0]
new_meta['Exif.Photo.PixelYDimension'].value = img_r.shape[1]
new_meta['Exif.Photo.PixelXDimension'] = img_r.shape[0]
new_meta['Exif.Photo.PixelYDimension'] = img_r.shape[1]
new_meta.write()
# update photos array with new values
photo.path_file = new_path_file
@ -75,17 +88,21 @@ class ODMResizeCell(ecto.Cell):
photo.update_focal()
# log message
log.ODM_DEBUG('Resized %s | dimensions: %s' % \
(photo.filename, img_r.shape))
log.ODM_DEBUG('Resized %s | dimensions: %s' %
(photo.filename, img_r.shape))
else:
# log message
log.ODM_WARNING('Already resized %s | dimensions: %s x %s' % \
(photo.filename, photo.width, photo.height))
log.ODM_WARNING('Already resized %s | dimensions: %s x %s' %
(photo.filename, photo.width, photo.height))
log.ODM_INFO('Resized %s images' % len(photos))
# append photos to cell output
self.outputs.photos = photos
if args.time:
system.benchmark(start_time, tree.benchmarking, 'Resizing')
log.ODM_INFO('Running ODM Resize Cell - Finished')
return ecto.OK if args['end_with'] != 'resize' else ecto.QUIT
return ecto.OK if args.end_with != 'resize' else ecto.QUIT

BIN
tests/test_data/gcp_List_GCPposition.jpg 100644
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Po

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20
tests/test_data/gcp_list.txt 100644
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@ -0,0 +1,20 @@
WGS84 UTM 32N
274914.738,4603349.014,400,2121.02804,-405.91779,DJI_0068.JPG
274914.738,4603349.014,400,2113.45101,-52.37843,DJI_0104.JPG
274914.738,4603349.014,400,2251.05140,-2510.08324,1JI_0076.JPG
274915.887,4603307.715,400,2189.08075,-1266.93925,DJI_0068.JPG
274915.887,4603307.715,400,1249.52906,-136.41574,DJI_0104.JPG
274915.887,4603307.715,400561.05432,-1057.69568,DJI_0083.JPG
274915.887,4603307.715,400,2239.44947,-1593.32652,1JI_0076.JPG
274985.284,4603319.756,400,3619.20999,-978.85879,DJI_0068.JPG
274985.284,4603319.756,400,1506.89252,-1535.16355,DJI_0104.JPG
274985.284,4603319.756,400,783.53534,-1793.26811,1JI_0076.JPG
274920.710,4603258.802,400,2342.84463,-2285.96671,DJI_0068.JPG
274920.710,4603258.802,400,305.37748,-303.36595,DJI_0104.JPG
274920.710,4603258.802,400,1531.52745,-896.39311,DJI_0083.JPG
274920.710,4603258.802,400,3671.08645,-2198.67114,DJI_0063.JPG
274920.710,4603258.802,400.1007.75409,-1286.05432,DJI_0074.JPG
274879.571,4603204.279,400,2693.25350,-1682.97313,DJI_0083.JPG
274879.571,4603204.279,400,2513.14252,-1413.82886,DJI_0063.JPG
274879.571,4603204.279,400,2150.56951,-2093.38493,DJI_0074.JPG

66
tests/test_data/gcp_list_README.txt 100644
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@ -0,0 +1,66 @@
Do not exspect more acurate results with these coordinates!!
These GCPs are reverse geotagged from an OpenDroneMap created Geotif
with WGS84 coordinates in the EXIF tags.
I also do not have a height value for the points!
(Set to 400m for testing purposes...)
-----------
CRS:
----
WGS 84 / UTM zone 17N
EPSG: 32617
-----------
GCP point values:
----
GCP_PointNr,X_Coordinate,Y_Coordinate
1,274914.738,4603349.014,400
2,274915.887,4603307.715,400
3,274985.284,4603319.756,400
4,274920.710,4603258.802,400
5,274879.571,4603204.279,400
-----------
-----------
Better human readable gcp_list.txt
----
WGS84 UTM 32N
## x1 y1 z1 pixelx1 pixely1 imagename1
## 0/0 of Pixel Coordinate = Upper left hand corner
# GCP 1
274914.738,4603349.014,400,2121.02804,-405.91779,DJI_0068.JPG
274914.738,4603349.014,400,2113.45101,-52.37843,DJI_0104.JPG
274914.738,4603349.014,400,2251.05140,-2510.08324,1JI_0076.JPG
# GCP 2
274915.887,4603307.715,400,2189.08075,-1266.93925,DJI_0068.JPG
274915.887,4603307.715,400,1249.52906,-136.41574,DJI_0104.JPG
274915.887,4603307.715,400561.05432,-1057.69568,DJI_0083.JPG
274915.887,4603307.715,400,2239.44947,-1593.32652,1JI_0076.JPG
# GCP 3
274985.284,4603319.756,400,3619.20999,-978.85879,DJI_0068.JPG
274985.284,4603319.756,400,1506.89252,-1535.16355,DJI_0104.JPG
274985.284,4603319.756,400,783.53534,-1793.26811,1JI_0076.JPG
# GCP 4
274920.710,4603258.802,400,2342.84463,-2285.96671,DJI_0068.JPG
274920.710,4603258.802,400,305.37748,-303.36595,DJI_0104.JPG
274920.710,4603258.802,400,1531.52745,-896.39311,DJI_0083.JPG
274920.710,4603258.802,400,3671.08645,-2198.67114,DJI_0063.JPG
274920.710,4603258.802,400.1007.75409,-1286.05432,DJI_0074.JPG
# GCP 5
274879.571,4603204.279,400,2693.25350,-1682.97313,DJI_0083.JPG
274879.571,4603204.279,400,2513.14252,-1413.82886,DJI_0063.JPG
274879.571,4603204.279,400,2150.56951,-2093.38493,DJI_0074.JPG

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c46a1e3a765b6974b8b5995d472eed6c620eeb09

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433a51fcac348bc741b98f2cb9c098b03b6ab26c

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35f630bafe453d675c773f1d8304184a4c21e468

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5af5613cfaa98bfde835e10353cfb85c1660b5dc

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93aae65839132a59f768335b8e73949ba1e2f359

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f410a8ef95e061299711be032f383820a8ad1e15

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188f3a590c8a91558b30a5b6a224bdfba9d82dd5

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4f1a66fedadd856e1dc3c1a0cde1814ea8a72894

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409e9b1d887a9e9cba52ca8ecacc33e05c0c9314

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16065e90bb3ea4008e4a27d0f49ec66f259fa913

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