object_segmentation_guide.md

Object Part Segmentation on ShapeNetPart

Data

ShapeNetPart dataset can be downloaded here (635 MB). Uncompress the folder and move it to Data/ShapeNetPart/shapenetcore_partanno_segmentation_benchmark_v0.

Training

Simply run the following script to start the training:

    python3 training_ShapeNetPart.py

Similarly to ModelNet40 training, the parameters can be modified in a configuration subclass called ShapeNetPartConfig, and the first run of this script might take some time to precompute dataset structures.

Plot a logged training

When you start a new training, it is saved in a results folder. A dated log folder will be created, containing many information including loss values, validation metrics, model snapshots, etc.

In plot_convergence.py, you will find detailed comments explaining how to choose which training log you want to plot. Follow them and then run the script :

    python3 plot_convergence.py

Test the trained model

The test script is the same for all models (segmentation or classification). In test_any_model.py, you will find detailed comments explaining how to choose which logged trained model you want to test. Follow them and then run the script :

    python3 test_any_model.py