Comments (6)
For the first issue, try to change the name of self.down to self.conv_res in
Line 72 in d4880e1
For the second issue, try to change the name of self.l1 to self.l1a in
Line 145 in d4880e1
Or just re-train the model.
Sorry for this mistake, but it has been a long day and I forgot some details.
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Hi. Thank you for replying. There were other issues similar to these, so now i am retraining. But it will be great if you could release a working set of weights if you get time. Thanks again!
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thank your source code, but when I run this code, The following error occurs:
ValueError: num_samples should be a positive integer value, but got num_samples=0
I've run the program 'python data_gen/ntu_gendata.py 'before, and some documents were generated :
train_data_joint.npy
train_label.pkl
val_data_joint.npy
val_label.pkl
but their size are all 1K
How should I deal with, trouble you give directions.
thanks
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For the first issue, try to change the name of self.down to self.conv_res in
Line 72 in d4880e1
For the second issue, try to change the name of self.l1 to self.l1a in
Line 145 in d4880e1
Or just re-train the model.
Sorry for this mistake, but it has been a long day and I forgot some details.
I have the same problem, it seems only test joints on ntu-crossview, it will work. otherwise there will be the same problem of the model mismatch even if I try the above modifications.
Could you please help me with this? If you get any time, Thanks
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[ Sun Oct 25 02:03:25 2020 ] Load weights from ./runs/ntu_cv_agcn_joint-49-29400.pt. [ Sun Oct 25 02:03:25 2020 ] using warm up, epoch: 0 [ Sun Oct 25 02:03:25 2020 ] Model: model.agcn.Model. [ Sun Oct 25 02:03:25 2020 ] Weights: ./runs/ntu_cv_agcn_joint-49-29400.pt. [ Sun Oct 25 02:03:25 2020 ] Eval epoch: 1 main.py:460: UserWarning: volatile was removed and now has no effect. Use
with torch.no_grad():instead. volatile=True) main.py:464: UserWarning: volatile was removed and now has no effect. Use
with torch.no_grad():instead. volatile=True) 100%|███████████████████████████████████████████| 74/74 [03:43<00:00, 3.03s/it] Accuracy: 0.012465666596239171 model: ./runs/ntu_cv_agcn_test_joint [ Sun Oct 25 02:07:09 2020 ] Mean test loss of 74 batches: 16.15059603871526. [ Sun Oct 25 02:07:09 2020 ] Top1: 1.25% [ Sun Oct 25 02:07:09 2020 ] Top5: 8.16% [ Sun Oct 25 02:07:10 2020 ] Done.
there might be some problem with the provided model.
I try it with ntu-cross-view on joints data with provided model, the result is too poor.
Is there anything wrong with the model or Did I do something wrong? Thanks
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[ Sun Oct 25 02:03:25 2020 ] Load weights from ./runs/ntu_cv_agcn_joint-49-29400.pt. [ Sun Oct 25 02:03:25 2020 ] using warm up, epoch: 0 [ Sun Oct 25 02:03:25 2020 ] Model: model.agcn.Model. [ Sun Oct 25 02:03:25 2020 ] Weights: ./runs/ntu_cv_agcn_joint-49-29400.pt. [ Sun Oct 25 02:03:25 2020 ] Eval epoch: 1 main.py:460: UserWarning: volatile was removed and now has no effect. Use
with torch.no_grad():instead. volatile=True) main.py:464: UserWarning: volatile was removed and now has no effect. Use
with torch.no_grad():instead. volatile=True) 100%|███████████████████████████████████████████| 74/74 [03:43<00:00, 3.03s/it] Accuracy: 0.012465666596239171 model: ./runs/ntu_cv_agcn_test_joint [ Sun Oct 25 02:07:09 2020 ] Mean test loss of 74 batches: 16.15059603871526. [ Sun Oct 25 02:07:09 2020 ] Top1: 1.25% [ Sun Oct 25 02:07:09 2020 ] Top5: 8.16% [ Sun Oct 25 02:07:10 2020 ] Done.
there might be some problem with the provided model.
I try it with ntu-cross-view on joints data with provided model, the result is too poor.
Is there anything wrong with the model or Did I do something wrong? Thanks
I changed the layers name of the mismatched ones and reload the model, however, it seems all of the provided model isn't working well with a poor performance.
Start training from scratch.
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Related Issues (20)
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