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Issues training with CMU_Panoptic

See original GitHub issue


  1. I am trying to train the model starting from pretrained resent on the cmu_panoptic dataset. However, I get the following error:
Traceback (most recent call last):
  File "HumanObj_videos_ResNet/", line 277, in <module>
  File "HumanObj_videos_ResNet/", line 273, in main
  File "HumanObj_videos_ResNet/", line 77, in train
  File "HumanObj_videos_ResNet/", line 192, in train_epoch
    for iter_index, meta_data in enumerate(self.loader):
  File "/z/home/mkhoshle/env/romp2/lib/python3.8/site-packages/torch/utils/data/", line 521, in __next__
    data = self._next_data()
  File "/z/home/mkhoshle/env/romp2/lib/python3.8/site-packages/torch/utils/data/", line 1203, in _next_data
    return self._process_data(data)
  File "/z/home/mkhoshle/env/romp2/lib/python3.8/site-packages/torch/utils/data/", line 1229, in _process_data
  File "/z/home/mkhoshle/env/romp2/lib/python3.8/site-packages/torch/", line 434, in reraise
    raise exception
ValueError: Caught ValueError in DataLoader worker process 0.
Original Traceback (most recent call last):
  File "/z/home/mkhoshle/env/romp2/lib/python3.8/site-packages/torch/utils/data/_utils/", line 287, in _worker_loop
    data = fetcher.fetch(index)
  File "/z/home/mkhoshle/env/romp2/lib/python3.8/site-packages/torch/utils/data/_utils/", line 49, in fetch
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File "/z/home/mkhoshle/env/romp2/lib/python3.8/site-packages/torch/utils/data/_utils/", line 49, in <listcomp>
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File "/z/home/mkhoshle/Human_object_transform/HumanObj_videos_ResNet/lib/dataset/", line 79, in __getitem__
    annots = self.datasets[dataset_id][index_sample]
  File "/z/home/mkhoshle/Human_object_transform/HumanObj_videos_ResNet/lib/dataset/", line 375, in __getitem__
    return self.get_item_single_frame(index)
  File "/z/home/mkhoshle/Human_object_transform/HumanObj_videos_ResNet/lib/dataset/", line 123, in get_item_single_frame
    kp3d, valid_masks[:,1] = self.process_kp3ds(info['kp3ds'], used_person_inds, \
  File "/z/home/mkhoshle/Human_object_transform/HumanObj_videos_ResNet/lib/dataset/", line 284, in process_kp3ds
    kp3d_processed[inds] = kp3d
ValueError: could not broadcast input array from shape (17,3) into shape (54,3)

Do you know what I need to do to avoid this error?

  1. Also, does the cmu_panoptic have the 2d pose annotation for all the people appearing in every image?

I would appreciate it if you could help me with this, Thanks,

Issue Analytics

  • State:open
  • Created 10 months ago
  • Comments:5 (3 by maintainers)

github_iconTop GitHub Comments

Arthur151commented, Nov 23, 2022

Hi,@mkhoshle, To prepare a dataloader for a dataset, please refer to Please note that, via function self.map_kps, we tranfer the different skeleton defination of each dataset (e.g. 17 joints in CMU P) to a unified format (our 54 joints). The mapping is achieved via:

The skeleton of each dataset is defined in

You can define the skeleton of CMU P as CMUP_17, for example,

CMUP_17 = {'R_Ankle':0 ....}

Our 54 joints are defined as SMPL_ALL_54,

Then the mapping would be self.kp3d_mapper = constants.joint_mapping(constants.CMUP_17, constants.SMPL_ALL_54)

Arthur151commented, Nov 27, 2022

I am not sure. Maybe this function setting label_kp_order=True, would be helpful. Using to set up the dataset loader, you can use debug function at to check the keypoints.

Yes, all multi-person datasets have this problem, more or less, including cmu_panoptic.

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