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[CVPR 2022] Joint hand motion and interaction hotspots prediction from egocentric videos

License: MIT License

Python 100.00%

egocentric-videos transformers video-forecasting

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EOFError: Ran out of input

Hi,

Thanks for sharing your source code.

I am getting "EOFError: Ran out of input" error while evaluating future hand trajectory or future interaction hotspots. I have followed the steps on the README. All of the error trace is following:

Using 1 GPUs !
=> loading checkpoint 'model.pth.tar'
Loaded checkpoint from epoch 35, starting from there
Loading validation samples: 100%|██████████████████████████████████████████████████████████████████████████████████| 3513/3513 [00:00<00:00, 8801.58it/s]
Loading eval samples: 100%|██████████████████████████████████████████████████████████████████████████████████████████| 401/401 [00:00<00:00, 5768.16it/s]
C:\Users\mesad\miniconda3\lib\site-packages\torch\utils\data\dataloader.py:563: UserWarning: This DataLoader will create 16 worker processes in total. Our suggested max number of worker in current system is 12 (`cpuset` is not taken into account), which is smaller than what this DataLoader is going to create. Please be aware that excessive worker creation might get DataLoader running slow or even freeze, lower the worker number to avoid potential slowness/freeze if necessary.
  warnings.warn(_create_warning_msg(
evaluation dataset size: 401
evaluate epoch 35
Traceback (most recent call last):
  File "C:\Users\mesad\projects\bitirme\hoi-forecast\traineval.py", line 125, in <module>
    main(args)
  File "C:\Users\mesad\projects\bitirme\hoi-forecast\traineval.py", line 76, in main
    epoch_pass(Exception ignored in: <function lmdbdict.__del__ at 0x000002084936B0D0>

  File "C:\Users\mesad\projects\bitirme\hoi-forecast\netscripts\epoch_feat.py", line 31, in epoch_pass
Traceback (most recent call last):
  File "C:\Users\mesad\miniconda3\lib\site-packages\lmdbdict\lmdbdict.py", line 184, in __del__
    for batch_idx, sample in enumerate(loader):
  File "C:\Users\mesad\miniconda3\lib\site-packages\torch\utils\data\dataloader.py", line 444, in __iter__
    if self.mode == 'w':
AttributeError    return self._get_iterator():
  File "C:\Users\mesad\miniconda3\lib\site-packages\torch\utils\data\dataloader.py", line 390, in _get_iterator
'lmdbdict' object has no attribute 'mode'
Traceback (most recent call last):
  File "<string>", line 1, in <module>
    return _MultiProcessingDataLoaderIter(self)
  File "C:\Users\mesad\miniconda3\lib\multiprocessing\spawn.py", line 116, in spawn_main
  File "C:\Users\mesad\miniconda3\lib\site-packages\torch\utils\data\dataloader.py", line 1077, in __init__
    exitcode = _main(fd, parent_sentinel)
  File "C:\Users\mesad\miniconda3\lib\multiprocessing\spawn.py", line 126, in _main
    w.start()
  File "C:\Users\mesad\miniconda3\lib\multiprocessing\process.py", line 121, in start
    self = reduction.pickle.load(from_parent)
EOFError: Ran out of input
    self._popen = self._Popen(self)
  File "C:\Users\mesad\miniconda3\lib\multiprocessing\context.py", line 224, in _Popen
    return _default_context.get_context().Process._Popen(process_obj)
  File "C:\Users\mesad\miniconda3\lib\multiprocessing\context.py", line 327, in _Popen
    return Popen(process_obj)
  File "C:\Users\mesad\miniconda3\lib\multiprocessing\popen_spawn_win32.py", line 93, in __init__
    reduction.dump(process_obj, to_child)
  File "C:\Users\mesad\miniconda3\lib\multiprocessing\reduction.py", line 60, in dump
    ForkingPickler(file, protocol).dump(obj)
AttributeError: Can't pickle local object 'get_features_loader.<locals>.<lambda>'```

Hi,Steven. I meet the problem when trying the train mode. I extract the features like the RULSTM, but I only get the data.mdb and lock.mdb. I found the data.lmdb in the eval mode, and the value include global features, hand features ,hand bbox. It seems that the method in LSTM cannot provide us the correct lmdb for training. Could you please tell me how can I get the whole LMDB including hand&object features? Also, I wonder how can I make .lmdb type document(not .mdb).
Thanks!

Correction for trajectory and heatmap not showing

I believe there is a small bug in the code at this line

The function should return outside the inner if conditions.

file for EGTEA Gaze+ dataset similar to ek100_eval_labels.pkl

Hi @stevenlsw ,

Thanks for your fantastic work again! Could you tell me where is the ground-truth annotation file (containing such as 'norm_contacts') in EGTEA Gaze+ dataset similar to the ek100_eval_labels.pkl in EK-100 dataset?

Looking forward to your reply~

Inquiry `.lmdb` File for EGTEA Gaze+ Dataset

Hi Steven,

Thank you so much for sharing the implementation of this interesting paper.

If it's not too much trouble and if you still have the lmdb file of EGTEA Gaze+ Dataset on your local system, could you consider sharing it? This will immensely aid my progress and save me a big amount of time.

Thank you in advance.

Sharing hand and object bounding boxes for EGTEA

Hi Steven

Thanks for sharing this interesting work. In the paper, you have extracted hand and object bounding boxes for the datasets.

Is it possible to share it for EGTEA dataset as it is not publicly available?

Thanks and Regards
Debaditya

Inquire about the license for copyright issue

Hi Shaowei,

Many thanks for sharing this great work! I noticed there is no LICENSE under this repo. I would like to use some pieces of your code, primarily the basic Transformer components from networks/embedding.py, networks/layer.py, networks/net_utils.py, and networks/transformer.py.

To respect and protect your copyright, I'm wondering if these codes are developed by yourself or referred to some licensed open-source softwares (e.g., PyTorch, huggingface, etc). If developed by yourself, would you mind providing a license (MIT, BSD 3.0, or Apache 2.0)? If modified from other sources, could you tell where are they originally from?

Thank you!

Thanks.

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