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When I ran train.py, this bug appeared. Later, I adjusted the torch version and no longer reported the error, but it appeared again when I ran evaluate_model.py. I don't know what caused it?
The text was updated successfully, but these errors were encountered:
It is because some person is not in all 16 positions (8 observed, 8 predicted) - in your case, "(2,15)" means there are 15 positions of some person in dataset instead of 16. I had the same issue so I added these lines in trajectory.py under line curr_ped_seq = np.transpose(curr_ped_seq[:, 2:]):
if curr_ped_seq.shape != (2,16): continue
(in case you are predicting 12 positions, use (2,20) )
When I ran train.py, this bug appeared. Later, I adjusted the torch version and no longer reported the error, but it appeared again when I ran evaluate_model.py. I don't know what caused it?
The text was updated successfully, but these errors were encountered: