Merge remote-tracking branch 'origin/master' into odm_output_improvements

Dockerfile

@@ -21,7 +21,7 @@ libexiv2-dev liblas-bin python-matplotlib libatlas-base-dev swig2.0 python-wheel
 RUN apt-get remove libdc1394-22-dev
 RUN pip install --upgrade pip
 RUN pip install setuptools
-RUN pip install -U PyYAML exifread gpxpy xmltodict catkin-pkg appsettings gippy loky shapely numpy pyproj psutil && pip install -U scipy --ignore-installed
+RUN pip install -U PyYAML exifread gpxpy xmltodict catkin-pkg appsettings https://github.com/gipit/gippy/archive/v1.0.0.zip loky shapely numpy pyproj psutil && pip install -U scipy --ignore-installed
 
 ENV PYTHONPATH="$PYTHONPATH:/code/SuperBuild/install/lib/python2.7/dist-packages"
 ENV PYTHONPATH="$PYTHONPATH:/code/SuperBuild/src/opensfm"

README.md

@@ -30,7 +30,11 @@ instructions through "Create a Docker group". The Docker image workflow
 has equivalent procedures for Mac OS X and Windows found at [docs.docker.com](docs.docker.com). Then run the following command which will build a pre-built image and run on images found in `$(pwd)/images` (you can change this if you need to, see the [wiki](https://github.com/OpenDroneMap/OpenDroneMap/wiki/Docker) for more detailed instructions.
 
 ```
-docker run -it --rm -v $(pwd)/images:/code/images -v $(pwd)/odm_orthophoto:/code/odm_orthophoto -v $(pwd)/odm_texturing:/code/odm_texturing opendronemap/opendronemap
+docker run -it --rm \
+    -v "$(pwd)/images:/code/images" \
+    -v "$(pwd)/odm_orthophoto:/code/odm_orthophoto" \
+    -v "$(pwd)/odm_texturing:/code/odm_texturing" \
+    opendronemap/opendronemap
 ```
 
 ### Native Install (Ubuntu 16.04)
@@ -126,7 +130,7 @@ When the process finishes, the results will be organized as follows:
         |-- 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.laz     # LAZ format point cloud
         |-- odm_georeferenced_model.csv     # XYZ format point cloud
         |-- odm_georeferencing_log.txt      # Georeferencing log
         |-- odm_georeferencing_transform.txt# Transform used for georeferencing
@@ -155,12 +159,20 @@ installed on your machine. Docker software is free to install and use in this co
 see the [Docker Ubuntu installation tutorial](https://docs.docker.com/engine/installation/linux/ubuntulinux/) and follow the
 instructions through "Create a Docker group". Once Docker is installed, the fastest way to use OpenDroneMap is to run a pre-built image by typing:
 
-    docker run -it --rm -v $(pwd)/images:/code/images -v $(pwd)/odm_orthophoto:/code/odm_orthophoto -v $(pwd)/odm_texturing:/code/odm_texturing opendronemap/opendronemap
+    docker run -it --rm \
+        -v "$(pwd)/images:/code/images" \
+        -v "$(pwd)/odm_orthophoto:/code/odm_orthophoto" \
+        -v "$(pwd)/odm_texturing:/code/odm_texturing" \
+        opendronemap/opendronemap
 
 If you want to build your own Docker image from sources, type:
 
     docker build -t my_odm_image .
-    docker run -it --rm -v $(pwd)/images:/code/images -v $(pwd)/odm_orthophoto:/code/odm_orthophoto -v $(pwd)/odm_texturing:/code/odm_texturing my_odm_image
+    docker run -it --rm \
+        -v "$(pwd)/images:/code/images" \
+        -v "$(pwd)/odm_orthophoto:/code/odm_orthophoto" \
+        -v "$(pwd)/odm_texturing:/code/odm_texturing" \
+        my_odm_image
 
 Using this method, the containerized ODM will process the images in the OpenDroneMap/images directory and output results
 to the OpenDroneMap/odm_orthophoto and OpenDroneMap/odm_texturing directories as described in the [Viewing Results](https://github.com/OpenDroneMap/OpenDroneMap/wiki/Output-and-Results) section.
@@ -168,19 +180,40 @@ If you want to view other results outside the Docker image simply add which dire
 established above. For example, if you're interested in the dense cloud results generated by PMVS and in the orthophoto,
 simply use the following `docker run` command after building the image:
 
-    docker run -it --rm -v $(pwd)/images:/code/images -v $(pwd)/odm_georeferencing:/code/odm_georeferencing -v $(pwd)/odm_orthophoto:/code/odm_orthophoto my_odm_image
+    docker run -it --rm \
+        -v "$(pwd)/images:/code/images" \
+        -v "$(pwd)/odm_georeferencing:/code/odm_georeferencing" \
+        -v "$(pwd)/odm_orthophoto:/code/odm_orthophoto" \
+        my_odm_image
 
 If you want to get all intermediate outputs, run the following command:
 
-    docker run -it --rm -v $(pwd)/images:/code/images -v $(pwd)/odm_georeferencing:/code/odm_georeferencing -v $(pwd)/odm_meshing:/code/odm_meshing -v $(pwd)/odm_orthophoto:/code/odm_orthophoto -v $(pwd)/odm_texturing:/code/odm_texturing -v $(pwd)/opensfm:/code/opensfm -v $(pwd)/pmvs:/code/pmvs opendronemap/opendronemap
+    docker run -it --rm \
+        -v "$(pwd)/images:/code/images" \
+        -v "$(pwd)/odm_georeferencing:/code/odm_georeferencing" \
+        -v "$(pwd)/odm_meshing:/code/odm_meshing" \
+        -v "$(pwd)/odm_orthophoto:/code/odm_orthophoto" \
+        -v "$(pwd)/odm_texturing:/code/odm_texturing" \
+        -v "$(pwd)/opensfm:/code/opensfm" \
+        -v "$(pwd)/pmvs:/code/pmvs" \
+        opendronemap/opendronemap
 
 To pass in custom parameters to the run.py script, simply pass it as arguments to the `docker run` command. For example:
 
-    docker run -it --rm -v $(pwd)/images:/code/images v $(pwd)/odm_orthophoto:/code/odm_orthophoto -v $(pwd)/odm_texturing:/code/odm_texturing opendronemap/opendronemap --resize-to 1800 --force-ccd 6.16
+    docker run -it --rm \
+        -v "$(pwd)/images:/code/images" \
+        -v "$(pwd)/odm_orthophoto:/code/odm_orthophoto" \
+        -v "$(pwd)/odm_texturing:/code/odm_texturing" \
+        opendronemap/opendronemap --resize-to 1800 --force-ccd 6.16
 
 If you want to pass in custom parameters using the settings.yaml file, you can pass it as a -v volume binding:
 
-    docker run -it --rm -v $(pwd)/images:/code/images v $(pwd)/odm_orthophoto:/code/odm_orthophoto -v $(pwd)/odm_texturing:/code/odm_texturing -v $(pwd)/settings.yaml:/code/settings.yaml opendronemap/opendronemap
+    docker run -it --rm \
+        -v "$(pwd)/images:/code/images" \
+        -v "$(pwd)/odm_orthophoto:/code/odm_orthophoto" \
+        -v "$(pwd)/odm_texturing:/code/odm_texturing" \
+        -v "$(pwd)/settings.yaml:/code/settings.yaml" \
+        opendronemap/opendronemap
 
 When building your own Docker image, if image size is of importance to you, you should use the ```--squash``` flag, like so:
 
@@ -203,7 +236,7 @@ A web interface and API to OpenDroneMap is currently under active development in
 
 ## Video Support
 
-Currently we have an experimental feature that uses ORB_SLAM to render a textured mesh from video. It is only supported on Ubuntu 14.04 on machines with X11 support. See the [wiki](https://github.com/OpenDroneMap/OpenDroneMap/wiki/Reconstruction-from-Video)for details on installation and use.
+Currently we have an experimental feature that uses ORB_SLAM to render a textured mesh from video. It is only supported on Ubuntu 14.04 on machines with X11 support. See the [wiki](https://github.com/OpenDroneMap/OpenDroneMap/wiki/Reconstruction-from-Video) for details on installation and use.
 
 ## Examples
 

SuperBuild/CMakeLists.txt

@@ -124,6 +124,7 @@ set(custom_libs OpenGV
 				CMVS
 				Catkin
 				Ecto
+				LASzip
 				PDAL
 				MvsTexturing
 )

SuperBuild/cmake/External-LASzip.cmake

@@ -0,0 +1,29 @@
+set(_proj_name laszip)
+set(_SB_BINARY_DIR "${SB_BINARY_DIR}/${_proj_name}")
+
+ExternalProject_Add(${_proj_name}
+  DEPENDS
+  PREFIX            ${_SB_BINARY_DIR}
+  TMP_DIR           ${_SB_BINARY_DIR}/tmp
+  STAMP_DIR         ${_SB_BINARY_DIR}/stamp
+  #--Download step--------------
+  DOWNLOAD_DIR      ${SB_DOWNLOAD_DIR}/${_proj_name}
+  URL               https://github.com/LASzip/LASzip/archive/0069c42307183c49744f1eb170f7032a8cf6a9db.zip
+  #--Update/Patch step----------
+  UPDATE_COMMAND    ""
+  #--Configure step-------------
+  SOURCE_DIR        ${SB_SOURCE_DIR}/${_proj_name}
+  CMAKE_ARGS
+    -DBUILD_SHARED_LIBS=ON
+    -DBUILD_STATIC_LIBS=OFF
+    -DCMAKE_INSTALL_PREFIX=${SB_INSTALL_DIR}
+    -DCMAKE_INSTALL_LIBDIR=lib
+  #--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
+)

SuperBuild/cmake/External-MvsTexturing.cmake

@@ -7,7 +7,7 @@ ExternalProject_Add(${_proj_name}
   TMP_DIR           ${_SB_BINARY_DIR}/tmp
   STAMP_DIR         ${_SB_BINARY_DIR}/stamp
   #--Download step--------------
-  DOWNLOAD_DIR      ${SB_DOWNLOAD_DIR}
+  DOWNLOAD_DIR      ${SB_DOWNLOAD_DIR}/${_proj_name}
   URL               https://github.com/OpenDroneMap/mvs-texturing/archive/master.zip
   #--Update/Patch step----------
   UPDATE_COMMAND    ""

SuperBuild/cmake/External-PDAL.cmake

@@ -2,14 +2,13 @@ set(_proj_name pdal)
 set(_SB_BINARY_DIR "${SB_BINARY_DIR}/${_proj_name}")
 
 ExternalProject_Add(${_proj_name}
-  DEPENDS           hexer
+  DEPENDS           hexer laszip
   PREFIX            ${_SB_BINARY_DIR}
   TMP_DIR           ${_SB_BINARY_DIR}/tmp
   STAMP_DIR         ${_SB_BINARY_DIR}/stamp
   #--Download step--------------
   DOWNLOAD_DIR      ${SB_DOWNLOAD_DIR}
-  URL               https://github.com/PDAL/PDAL/archive/e881b581e3b91a928105d67db44c567f3b6d1afe.tar.gz
+  URL               https://github.com/PDAL/PDAL/archive/1.6.zip
-  URL_MD5           cadbadf1c83d69d6525cfffd41473323
   #--Update/Patch step----------
   UPDATE_COMMAND    ""
   #--Configure step-------------
@@ -34,6 +33,11 @@ ExternalProject_Add(${_proj_name}
 	-DWITH_LAZPERF=OFF
 	-DWITH_GEOTIFF=ON
 	-DWITH_LASZIP=ON
+	-DLASZIP_FOUND=TRUE
+	-DLASZIP_LIBRARIES=${SB_INSTALL_DIR}/lib/liblaszip.so
+	-DLASZIP_VERSION=3.1.1
+	-DLASZIP_INCLUDE_DIR=${SB_INSTALL_DIR}/include
+	-DLASZIP_LIBRARY=${SB_INSTALL_DIR}/lib/liblaszip.so
 	-DWITH_TESTS=OFF
 	-DCMAKE_BUILD_TYPE=Release
     -DCMAKE_INSTALL_PREFIX:PATH=${SB_INSTALL_DIR}

configure.sh

@@ -100,7 +100,7 @@ install() {
     echo "Installing split-merge Dependencies"
     pip install -U scipy shapely numpy pyproj
 
-    pip install -U gippy psutil
+    pip install -U https://github.com/gipit/gippy/archive/v1.0.0.zip psutil
 
     echo "Compiling SuperBuild"
     cd ${RUNPATH}/SuperBuild

core2.Dockerfile

@@ -19,7 +19,7 @@ libexiv2-dev liblas-bin python-matplotlib libatlas-base-dev swig2.0 python-wheel
 RUN apt-get remove libdc1394-22-dev
 RUN pip install --upgrade pip
 RUN pip install setuptools
-RUN pip install -U PyYAML exifread gpxpy xmltodict catkin-pkg appsettings gippy loky shapely numpy pyproj psutil && pip install -U scipy --ignore-installed
+RUN pip install -U PyYAML exifread gpxpy xmltodict catkin-pkg appsettings https://github.com/gipit/gippy/archive/v1.0.0.zip loky shapely numpy pyproj psutil && pip install -U scipy --ignore-installed
 
 ENV PYTHONPATH="$PYTHONPATH:/code/SuperBuild/install/lib/python2.7/dist-packages"
 ENV PYTHONPATH="$PYTHONPATH:/code/SuperBuild/src/opensfm"

opendm/types.py

@@ -255,16 +255,18 @@ class ODM_GeoRef(object):
                   'srs': self.projection.srs,
                   'json': json_file}
 
-        # create pipeline file transform.xml to enable transformation
+        # create pipeline file las.json to write odm_georeferenced_model.laz point cloud
         pipeline = '{{' \
                    '  "pipeline":[' \
                    '    "untransformed.ply",' \
                    '    {{' \
+                   '      "type":"writers.las",' \
                    '      "a_srs":"{srs}",' \
                    '      "offset_x":"{east}",' \
                    '      "offset_y":"{north}",' \
                    '      "offset_z":"0",' \
-                   '      "filename":"transformed.las"' \
+                   '      "compression":"laszip",' \
+                   '      "filename":"{f_out}"' \
                    '    }}' \
                    '  ]' \
                    '}}'.format(**kwargs)
@@ -273,8 +275,7 @@ class ODM_GeoRef(object):
             f.write(pipeline)
 
         # call pdal 
-        system.run('{bin}/pdal pipeline -i {json} --readers.ply.filename={f_in} '
+        system.run('{bin}/pdal pipeline -i {json} --readers.ply.filename={f_in}'.format(**kwargs))
-                   '--writers.las.filename={f_out}'.format(**kwargs))
 
     def utm_to_latlon(self, _file, _photo, idx):
 
@@ -477,8 +478,8 @@ class ODM_Tree(object):
             self.odm_georeferencing, 'odm_georeferenced_model.csv')
         self.odm_georeferencing_las_json = io.join_paths(
             self.odm_georeferencing, 'las.json')
-        self.odm_georeferencing_model_las = io.join_paths(
+        self.odm_georeferencing_model_laz = io.join_paths(
-            self.odm_georeferencing, 'odm_georeferenced_model.las')
+            self.odm_georeferencing, 'odm_georeferenced_model.laz')
         self.odm_georeferencing_dem = io.join_paths(
             self.odm_georeferencing, 'odm_georeferencing_model_dem.tif')
 

scripts/odm_dem.py

@@ -28,7 +28,7 @@ class ODMDEMCell(ecto.Cell):
         # get inputs
         args = self.inputs.args
         tree = self.inputs.tree
-        las_model_found = io.file_exists(tree.odm_georeferencing_model_las)
+        las_model_found = io.file_exists(tree.odm_georeferencing_model_laz)
 
         # check if we rerun cell or not
         rerun_cell = (args.rerun is not None and
@@ -40,7 +40,7 @@ class ODMDEMCell(ecto.Cell):
         log.ODM_INFO('Classify: ' + str(args.pc_classify != "none"))
         log.ODM_INFO('Create DSM: ' + str(args.dsm))
         log.ODM_INFO('Create DTM: ' + str(args.dtm))
-        log.ODM_INFO('DEM input file {0} found: {1}'.format(tree.odm_georeferencing_model_las, str(las_model_found)))
+        log.ODM_INFO('DEM input file {0} found: {1}'.format(tree.odm_georeferencing_model_laz, str(las_model_found)))
 
         # Setup terrain parameters
         terrain_params_map = {
@@ -61,8 +61,8 @@ class ODMDEMCell(ecto.Cell):
             pc_classify_marker = os.path.join(odm_dem_root, 'pc_classify_done.txt')
 
             if not io.file_exists(pc_classify_marker) or rerun_cell:
-                log.ODM_INFO("Classifying {} using {}".format(tree.odm_georeferencing_model_las, args.pc_classify))
+                log.ODM_INFO("Classifying {} using {}".format(tree.odm_georeferencing_model_laz, args.pc_classify))
-                commands.classify(tree.odm_georeferencing_model_las, 
+                commands.classify(tree.odm_georeferencing_model_laz, 
                                   args.pc_classify == "smrf",
                                   slope,
                                   cellsize,
@@ -96,7 +96,7 @@ class ODMDEMCell(ecto.Cell):
 
                 for product in products:
                     commands.create_dems(
-                            [tree.odm_georeferencing_model_las], 
+                            [tree.odm_georeferencing_model_laz], 
                             product,
                             radius=map(str, radius_steps),
                             gapfill=True,

scripts/odm_georeferencing.py

@@ -138,7 +138,7 @@ class ODMGeoreferencingCell(ecto.Cell):
 
                     # convert ply model to LAS reference system
                     geo_ref.convert_to_las(odm_georeferencing_model_ply_geo,
-                                           tree.odm_georeferencing_model_las,
+                                           tree.odm_georeferencing_model_laz,
                                            tree.odm_georeferencing_las_json)
 
                     reconstruction.georef = geo_ref
@@ -171,7 +171,7 @@ class ODMGeoreferencingCell(ecto.Cell):
                     if args.crop > 0:
                         log.ODM_INFO("Calculating cropping area and generating bounds shapefile from point cloud")
                         cropper = Cropper(tree.odm_georeferencing, 'odm_georeferenced_model')
-                        cropper.create_bounds_shapefile(tree.odm_georeferencing_model_las, args.crop)
+                        cropper.create_bounds_shapefile(tree.odm_georeferencing_model_laz, args.crop)
 
                     # Do not execute a second time, since
                     # We might be doing georeferencing for

tests/test_odm.py

@@ -136,7 +136,7 @@ class TestGeoreferencing(unittest.TestCase):
 
     def test_las_out(self):
         self.assertTrue(os.path.isfile(os.path.join(self.app.georeferencing.inputs.tree.odm_georeferencing,
-                                                    "odm_georeferenced_model.ply.las")))
+                                                    "odm_georeferenced_model.laz")))
 
 
 class TestOrthophoto(unittest.TestCase):