Blockquote
–texturing-skip-global-seam-leveling
Skip normalization of colors across all images. Useful
when processing radiometric data. Default: False
–texturing-skip-local-seam-leveling
Skip the blending of colors near seams. Default: False
–texturing-keep-unseen-faces
Keep faces in the mesh that are not seen in any
camera. Default: False
–texturing-tone-mapping
Turn on gamma tone mapping or none for no tone
mapping. Can be one of none, gamma. Default: none
–gcp Path to the file containing the ground control points
used for georeferencing. The file needs to use the
following format: EPSG:or <+proj definition>
geo_x geo_y geo_z im_x im_y image_name [gcp_name]
[extra1] [extra2] Default: None
–geo Path to the image geolocation file containing the
camera center coordinates used for georeferencing.
Note that omega/phi/kappa are currently not supported
(you can set them to 0). The file needs to use the
following format: EPSG:or <+proj definition>
image_name geo_x geo_y geo_z [omega (degrees)] [phi
(degrees)] [kappa (degrees)] [horz accuracy (meters)]
[vert accuracy (meters)] Default: None
–use-exif Use this tag if you have a GCP File but want to use
the EXIF information for georeferencing instead.
Default: False
–dtm Use this tag to build a DTM (Digital Terrain Model,
ground only) using a simple morphological filter.
Check the --dem* and --smrf* parameters for finer
tuning. Default: False
–dsm Use this tag to build a DSM (Digital Surface Model,
ground + objects) using a progressive morphological
filter. Check the --dem* parameters for finer tuning.
Default: False
–dem-gapfill-steps
Number of steps used to fill areas with gaps. Set to 0
to disable gap filling. Starting with a radius equal
to the output resolution, N different DEMs are
generated with progressively bigger radius using the
inverse distance weighted (IDW) algorithm and merged
together. Remaining gaps are then merged using nearest
neighbor interpolation. Default: 3
–dem-resolution
DSM/DTM resolution in cm / pixel. Note that this value
is capped by a ground sampling distance (GSD)
estimate. To remove the cap, check --ignore-gsd also.
Default: 5
–dem-decimation
Decimate the points before generating the DEM. 1 is no
decimation (full quality). 100 decimates ~99% of the
points. Useful for speeding up generation of DEM
results in very large datasets. Default: 1
–dem-euclidean-map Computes an euclidean raster map for each DEM. The map
reports the distance from each cell to the nearest
NODATA value (before any hole filling takes place).
This can be useful to isolate the areas that have been
filled. Default: False
–orthophoto-resolution 0.0>
Orthophoto resolution in cm / pixel. Note that this
value is capped by a ground sampling distance (GSD)
estimate. To remove the cap, check --ignore-gsd also.
Default: 5
–orthophoto-no-tiled
Set this parameter if you want a striped GeoTIFF.
Default: False
–orthophoto-png Set this parameter if you want to generate a PNG
rendering of the orthophoto. Default: False
–orthophoto-kmz Set this parameter if you want to generate a Google
Earth (KMZ) rendering of the orthophoto. Default:
False
–orthophoto-compression
Set the compression to use for orthophotos. Can be one
of: JPEG, LZW, PACKBITS, DEFLATE, LZMA, NONE. Default:
DEFLATE
–orthophoto-cutline Generates a polygon around the cropping area that cuts
the orthophoto around the edges of features. This
polygon can be useful for stitching seamless mosaics
with multiple overlapping orthophotos. Default: False
–tiles Generate static tiles for orthophotos and DEMs that
are suitable for viewers like Leaflet or OpenLayers.
Default: False
–build-overviews Build orthophoto overviews for faster display in
programs such as QGIS. Default: False
–cog Create Cloud-Optimized GeoTIFFs instead of normal
GeoTIFFs. Default: False
–verbose, -v Print additional messages to the console. Default:
False
–copy-to Copy output results to this folder after processing.
–time Generates a benchmark file with runtime info. Default:
False
–debug Print debug messages. Default: False
–version Displays version number and exits.
–split
Average number of images per submodel. When splitting
a large dataset into smaller submodels, images are
grouped into clusters. This value regulates the number
of images that each cluster should have on average.
Default: 999999
–split-overlap
Radius of the overlap between submodels. After
grouping images into clusters, images that are closer
than this radius to a cluster are added to the
cluster. This is done to ensure that neighboring
submodels overlap. Default: 150
–split-image-groups
Path to the image groups file that controls how images
should be split into groups. The file needs to use the
following format: image_name group_name Default: None
–sm-cluster
URL to a ClusterODM instance for distributing a split-
merge workflow on multiple nodes in parallel. Default:
None
–merge Choose what to merge in the merge step in a split
dataset. By default all available outputs are merged.
Options: all, pointcloud, orthophoto, dem. Default:
all
–force-gps Use images’ GPS exif data for reconstruction, even if
there are GCPs present.This flag is useful if you have
high precision GPS measurements. If there are no GCPs,
this flag does nothing. Default: False
–gps-accuracy
Set a value in meters for the GPS Dilution of
Precision (DOP) information for all images. If your
images are tagged with high precision GPS information
(RTK), this value will be automatically set
accordingly. You can use this option to manually set
it in case the reconstruction fails. Lowering this
option can sometimes help control bowling-effects over
large areas. Default: 10
–optimize-disk-space
Delete heavy intermediate files to optimize disk space
usage. This affects the ability to restart the
pipeline from an intermediate stage, but allows
datasets to be processed on machines that don’t have
sufficient disk space available. Default: False
–pc-rectify Perform ground rectification on the point cloud. This
means that wrongly classified ground points will be
re-classified and gaps will be filled. Useful for
generating DTMs. Default: False
–primary-band
When processing multispectral datasets, you can
specify the name of the primary band that will be used
for reconstruction. It’s recommended to choose a band
which has sharp details and is in focus. Default: auto
–skip-band-alignment
When processing multispectral datasets, ODM will
automatically align the images for each band. If the
images have been postprocessed and are already
aligned, use this option. Default: False
(venv) d:\ODM>run “D:/Projects/Gaudette Contracting 2020-06-06” --camera-lens perspective --dsm --dtm --pc-las --pc-quality ultra --time
[INFO] DTM is turned on, automatically turning on point cloud classification
[INFO] Initializing ODM - Sat Jun 12 21:17:17 2021
[INFO] ==============
[INFO] build_overviews: False
[INFO] camera_lens: perspective
[INFO] cameras: {}
[INFO] cog: False
[INFO] copy_to: None
[INFO] crop: 3
[INFO] debug: False
[INFO] dem_decimation: 1
[INFO] dem_euclidean_map: False
[INFO] dem_gapfill_steps: 3
[INFO] dem_resolution: 5
[INFO] depthmap_resolution: 640
[INFO] dsm: True
[INFO] dtm: True
[INFO] end_with: odm_report
[INFO] fast_orthophoto: False
[INFO] feature_quality: high
[INFO] feature_type: sift
[INFO] force_gps: False
[INFO] gcp: None
[INFO] geo: None
[INFO] gps_accuracy: 10
[INFO] ignore_gsd: False
[INFO] matcher_distance: 0
[INFO] matcher_neighbors: 8
[INFO] matcher_type: flann
[INFO] max_concurrency: 12
[INFO] merge: all
[INFO] mesh_octree_depth: 11
[INFO] mesh_size: 200000
[INFO] min_num_features: 8000
[INFO] name: D:/Projects/Gaudette Contracting 2020-06-06
[INFO] optimize_disk_space: False
[INFO] orthophoto_compression: DEFLATE
[INFO] orthophoto_cutline: False
[INFO] orthophoto_kmz: False
[INFO] orthophoto_no_tiled: False
[INFO] orthophoto_png: False
[INFO] orthophoto_resolution: 5
[INFO] pc_classify: True
[INFO] pc_csv: False
[INFO] pc_ept: False
[INFO] pc_filter: 2.5
[INFO] pc_las: True
[INFO] pc_quality: ultra
[INFO] pc_rectify: False
[INFO] pc_sample: 0
[INFO] pc_tile: False
[INFO] primary_band: auto
[INFO] project_path: /
[INFO] radiometric_calibration: none
[INFO] rerun: None
[INFO] rerun_all: False
[INFO] rerun_from: None
[INFO] resize_to: 2048
[INFO] skip_3dmodel: False
[INFO] skip_band_alignment: False
[INFO] skip_report: False
[INFO] sm_cluster: None
[INFO] smrf_scalar: 1.25
[INFO] smrf_slope: 0.15
[INFO] smrf_threshold: 0.5
[INFO] smrf_window: 18.0
[INFO] split: 999999
[INFO] split_image_groups: None
[INFO] split_overlap: 150
[INFO] texturing_data_term: gmi
[INFO] texturing_keep_unseen_faces: False
[INFO] texturing_outlier_removal_type: gauss_clamping
[INFO] texturing_skip_global_seam_leveling: False
[INFO] texturing_skip_local_seam_leveling: False
[INFO] texturing_tone_mapping: none
[INFO] tiles: False
[INFO] time: True
[INFO] use_3dmesh: False
[INFO] use_exif: False
[INFO] use_fixed_camera_params: False
[INFO] use_hybrid_bundle_adjustment: False
[INFO] verbose: False
[INFO] ==============
[INFO] Running dataset stage
[INFO] Loading dataset from: D:\Projects\Gaudette Contracting 2020-06-06\images
[INFO] Loading images database: D:\Projects\Gaudette Contracting 2020-06-06\images.json
[INFO] Found 247 usable images
[INFO] Coordinates file already exist: D:\Projects\Gaudette Contracting 2020-06-06\odm_georeferencing\coords.txt
[INFO] Model geo file already exist: D:\Projects\Gaudette Contracting 2020-06-06\odm_georeferencing\odm_georeferencing_model_geo.txt
[INFO] Parsing SRS header: WGS84 UTM 17N
[INFO] Finished dataset stage
[INFO] Running split stage
[INFO] Normal dataset, will process all at once.
[INFO] Finished split stage
[INFO] Running merge stage
[INFO] Normal dataset, nothing to merge.
[INFO] Finished merge stage
[INFO] Running opensfm stage
[WARNING] D:\Projects\Gaudette Contracting 2020-06-06\opensfm\image_list.txt already exists, not rerunning OpenSfM setup
[WARNING] Detect features already done: D:\Projects\Gaudette Contracting 2020-06-06\opensfm\features exists
[WARNING] Match features already done: D:\Projects\Gaudette Contracting 2020-06-06\opensfm\matches exists
[WARNING] Found a valid OpenSfM tracks file in: D:\Projects\Gaudette Contracting 2020-06-06\opensfm\tracks.csv
[WARNING] Found a valid OpenSfM reconstruction file in: D:\Projects\Gaudette Contracting 2020-06-06\opensfm\reconstruction.json
[INFO] Already extracted cameras
[INFO] Export reconstruction stats
[WARNING] Found existing reconstruction stats D:\Projects\Gaudette Contracting 2020-06-06\opensfm\stats\stats.json
[WARNING] Will skip exporting D:\Projects\Gaudette Contracting 2020-06-06\opensfm\reconstruction.geocoords.json
[INFO] Undistorting D:\Projects\Gaudette Contracting 2020-06-06\opensfm …
[WARNING] Already undistorted (nominal)
[WARNING] Found a valid OpenSfM NVM reconstruction file in: D:\Projects\Gaudette Contracting 2020-06-06\opensfm\undistorted/reconstruction.nvm
[INFO] Finished opensfm stage
[INFO] Running openmvs stage
[INFO] running d:\ODM\SuperBuild\install\bin\opensfm\bin\opensfm export_openmvs “D:\Projects\Gaudette Contracting 2020-06-06\opensfm”
[INFO] Running dense reconstruction. This might take a while.
[INFO] Estimating depthmaps
[INFO] running d:\ODM\SuperBuild\install\bin\OpenMVS\DensifyPointCloud “D:\Projects\Gaudette Contracting 2020-06-06\opensfm\undistorted\openmvs\scene.mvs” --resolution-level 1 --min-resolution 2028 --max-resolution 4056 --max-threads 12 --number-views-fuse 2 -w “D:\Projects\Gaudette Contracting 2020-06-06\opensfm\undistorted\openmvs\depthmaps” -v 0
21:17:23 [App ] Build date: Jun 10 2021, 15:37:41
21:17:23 [App ] CPU: Intel(R) Core™ i7-10750H CPU @ 2.60GHz (12 cores)
21:17:23 [App ] RAM: 15.77GB Physical Memory 128.00TB Virtual Memory
21:17:23 [App ] OS: Windows 8 x64
21:17:23 [App ] SSE & AVX compatible CPU & OS detected
21:17:23 [App ] Command line: D:\Projects\Gaudette Contracting 2020-06-06\opensfm\undistorted\openmvs\scene.mvs --resolution-level 1 --min-resolution 2028 --max-resolution 4056 --max-threads 12 --number-views-fuse 2 -w D:\Projects\Gaudette Contracting 2020-06-06\opensfm\undistorted\openmvs\depthmaps -v 0
21:18:11 [App ] Preparing images for dense reconstruction completed: 247 images (48s823ms)
21:18:11 [App ] Selecting images for dense reconstruction completed: 247 images (51ms)
Estimated depth-maps 247 (100%, 1h49m23s388ms)
===== Dumping Info for Geeks (developers need this to fix bugs) =====
Child returned 3221225478
Traceback (most recent call last):
File “d:\ODM\stages\odm_app.py”, line 89, in execute
File “d:\ODM\opendm\types.py”, line 340, in run
File “d:\ODM\opendm\types.py”, line 340, in run
File “d:\ODM\opendm\types.py”, line 340, in run
[Previous line repeated 1 more time]
File “d:\ODM\opendm\types.py”, line 321, in run
File “d:\ODM\stages\openmvs.py”, line 76, in process
File “d:\ODM\opendm\system.py”, line 106, in run
opendm.system.SubprocessException: Child returned 3221225478
===== Done, human-readable information to follow… =====
[ERROR] The program exited with a strange error code. Please report it at https://community.opendronemap.org
Cannot write log.json: [Errno 2] No such file or directory: 'D:/Projects/Gaudette Contracting 2020-06-06\log.json’
The system cannot find the path specified.
Double back slash at least showing in the ODM output but not here is the forum page? See the screen grab.
Appreciate any help or pointers.
Cheers,
Jeff
