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hello, Thanks for your work. I've trained HigherHRNet on CrowdPose dataset, but when I evaluate my model on the test set by using the command python tools/valid.py --cfg xxx.xml TEST.MODEL_FILE xx.pth.tar, The program seems to be stuck.
Number of Layers
Conv2d : 302 layers BatchNorm2d : 301 layers ReLU : 270 layers Bottleneck : 4 layers BasicBlock : 108 layers Upsample : 28 layers HighResolutionModule : 8 layers ConvTranspose2d : 1 layers
=> loading model from models/model_best.pth.tar
loading annotations into memory...
Done (t=0.55s)
creating index...
index created!
=> classes: ['__background__', 'person']
The text was updated successfully, but these errors were encountered:
hello, Thanks for your work. I've trained HigherHRNet on CrowdPose dataset, but when I evaluate my model on the test set by using the command python tools/valid.py --cfg xxx.xml TEST.MODEL_FILE xx.pth.tar, The program seems to be stuck.
Number of Layers
Conv2d : 302 layers BatchNorm2d : 301 layers ReLU : 270 layers Bottleneck : 4 layers BasicBlock : 108 layers Upsample : 28 layers HighResolutionModule : 8 layers ConvTranspose2d : 1 layers
=> loading model from models/model_best.pth.tar
loading annotations into memory...
Done (t=0.55s)
creating index...
index created!
=> classes: ['__background__', 'person']
make the cfg.TEST.LOG_PROGRESS to be ture, and you can see the progress bar.
hello, Thanks for your work. I've trained HigherHRNet on CrowdPose dataset, but when I evaluate my model on the test set by using the command
python tools/valid.py --cfg xxx.xml TEST.MODEL_FILE xx.pth.tar
, The program seems to be stuck.The text was updated successfully, but these errors were encountered: