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Shapenet Multi-view data training does not work
See original GitHub issueHi,
I use the following command to train shapenet multiview data (the single-view training works fine)
python3 train.py --model=sdf_srn --yaml=options/shapenet/sdf_srn.yaml --name=chair --data.shapenet.cat=chair --max_epoch=28
but the result seems not good, I trained several times, all experiments on multi-view data give me similar results. Chamfer distance does not change during the whole process, reconstructed image is similar to the ground truth, depth-map is also ok, but predicted normal-map is bad, .ply is empty,
Issue Analytics
- State:
- Created 3 years ago
- Comments:9 (4 by maintainers)
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Thanks for the quick reply! I double checked my dataset and found I had changed the folders’s name running another code. The training and evaluating went well in both muti-view data and single-view data after fixing this problem. Thanks again for this great work!
Hi @ZijinWu-AIA, it looks like the rendered images you have were from another source. Can you try evaluating on the ShapeNet rendering as described in the README (and making sure you followed all the steps in the README as well)?