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| Description: |
Perform point cloud and camera calibration :
$ RunBundler.py --photos="./examples/MyPhotos"
You could test various option... $ RunBundler.py
In a second step you could compute the dense 3D point cloud in one step if the dataset have a reasonable size.
$ RunPMVS.py --bundlerOutputPath="C:/temp/PreviousLineTempDirectoryPath"
If you have a lot of images, it better to use CMVS cluster computation.
It performs dense 3D point could computation by using Cluster 3D representation of the scene :
$ RunCMVS.py --bundlerOutputPath="C:/temp/PreviousLineTempDirectoryPath" --ClusterToCompute ="Number of Desired Cluster".
Example :
$ RunCMVS.py --bundlerOutputPath="C:/temp/osm-Result" --ClusterToCompute ="10". |
| SHA1 Checksum: |
302326005d61a0498e40c8245c429cc68b182a32
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