Open vadeli opened 8 months ago
Yes, I also meet this problem. I think it is an error.
it might be due to the fact that the original humanml dataset (and I guess the csv) was in 20fps but this dataset is in 30fps—thats where the 1.5 factor comes in.
The mocap_framerate in SMPL_HG is 60, while the mocap_frame_rate in SMPL_XG is 120.
I meant I think they are using the original csv file (in the original humanml dataset) which had start and end durations according to 20fps.
I ran into an issue with humanml.py when processing samples like CMU/80/80_63_poses.npy. It seems that the start and end indices in humanml_index.csv don't match the length of the sequence. For instance, CMU/80/80_63_poses.npy has 569 frames, but in humanml.py, there's a line:
pose = pose[int(start_frame*1.5):int(end_frame*1.5)]
And in humanml_index.csv, there's an entry like this:./pose_data/CMU/80/80_63_poses.npy,516,716,000004.npy
This results in an empty pose. I'm wondering why the start and end indices in the CSV file aren't consistent with the length of the AMASS sequences. Thanks
@vadeli @sohananisetty @luomingshuang The issue comes from the inconsistency of SMPL-H and SMPL-X annotation in AMASS. The AMASS author team seems not to have replied to it yet. Plz refer to the issue and another issue.
thanks for your reply. Another question is about the frame-level annotations in humanml. The released frame-level annotations
texts/body_texts/humanml
and texts/hand_texts/humanml
have some issues. For example, the number of frames in motion-x/texts/body_texts/humanml/000000.json
is 97 (0-96). But the number of frames in motion_data/smplx_322/humanml/000000.npy
is 146 (based on frame rate=120 and ex_fps=30). So I want to know how to match these two files. Or it still should be modified due to the inconsistent frame rate?
Hope your reply. Thanks.
So can the generated humanml
based on humanml_index.csv
and amass/smpl-xg
still be used normally? (even humanml_index.csv
doesn't match well)
I ran into an issue with humanml.py when processing samples like CMU/80/80_63_poses.npy. It seems that the start and end indices in humanml_index.csv don't match the length of the sequence. For instance, CMU/80/80_63_poses.npy has 569 frames, but in humanml.py, there's a line:
pose = pose[int(start_frame*1.5):int(end_frame*1.5)]
And in humanml_index.csv, there's an entry like this:./pose_data/CMU/80/80_63_poses.npy,516,716,000004.npy
This results in an empty pose. I'm wondering why the start and end indices in the CSV file aren't consistent with the length of the AMASS sequences. Thanks