Various scripts for (pre-)processing of data. Functionality includes rendering, identification of physically plausible object poses generation of watertight meshes from arbitrary triangle soups, identification of uncertain regions as introduced in Shape Completion with Prediction of Uncertain Regions and more.
render_kinect.py
: Render depth images from a given camera pose and intrinsics. Also simulates Kinect depth noise.render_kinect_parallel.py
: Runsrender_kinect.py
in parallel for multiple camera poses and intrinsics.render_data.py
UsesBlenderProc
for the rendering.
The script generate_physics_poses.py
generates physically plausible poses for sets of objects. It uses the Bullet Physics Engine to simulate the object falling onto a plane.
The script make_watertight.py
generates watertight meshes from triangle soups. It is based on mesh-fusion with various improvements for quality, robustness and speed.
Usage
make_watertight path/to/ShapeNetCore.v1
Use --out_dir /path/to/output/directory
to specify the output directory.
The script find_uncertain_regions.py
identifies regions with ambiguous occupancy given the current point of view.
For more details refer to Shape Completion with Prediction of Uncertain Regions.
Usage
find_uncertain_regions -cn shapenet_uncertain
Add vis.split=val
or vis.split=test
to find uncertain regions for the validation or test set, respectively.
Use log.verbose=True
to get detailed information about the process and vis.show=True
to visualize the results.