OpenRobotLab / EmbodiedScan

[CVPR 2024 & NeurIPS 2024] EmbodiedScan: A Holistic Multi-Modal 3D Perception Suite Towards Embodied AI
https://tai-wang.github.io/embodiedscan/
Apache License 2.0
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[Bug] Error occurs during converting scanNet #82

Open Mintinson opened 2 months ago

Mintinson commented 2 months ago

Prerequisite

Task

I'm using the official example scripts/configs for the officially supported tasks/models/datasets.

Branch

main branch https://github.com/open-mmlab/mmdetection3d

Environment

System environment: sys.platform: linux Python: 3.8.19 (default, Mar 20 2024, 19:58:24) [GCC 11.2.0] CUDA available: True MUSA available: False numpy_random_seed: 287746113 GPU 0: NVIDIA A100-PCIE-40GB CUDA_HOME: /usr/local/cuda-11.3 NVCC: Cuda compilation tools, release 11.3, V11.3.58 GCC: gcc (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0 PyTorch: 1.11.0 PyTorch compiling details: PyTorch built with:

Runtime environment: cudnn_benchmark: False mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} dist_cfg: {'backend': 'nccl'} seed: 287746113 Distributed launcher: none Distributed training: False GPU number: 1

Reproduces the problem - code sample

python embodiedscan/converter/generate_image_scannet.py --dataset_folder data/scannet/ --fast  

Reproduces the problem - command or script

python embodiedscan/converter/generate_image_scannet.py --dataset_folder data/scannet/ --fast  

Reproduces the problem - error message

Traceback (most recent call last):
  File "/root/miniconda3/envs/embodiedscan/lib/python3.8/multiprocessing/pool.py", line 125, in worker
    result = (True, func(*args, **kwds))
  File "embodiedscan/converter/generate_image_scannet.py", line 176, in process_scene
    data = SensorData(os.path.join(path, idx, f'{idx}.sens'), fast)
  File "embodiedscan/converter/generate_image_scannet.py", line 62, in __init__
    self.load(filename, fast)
  File "embodiedscan/converter/generate_image_scannet.py", line 104, in load
    frame.load(f)
  File "embodiedscan/converter/generate_image_scannet.py", line 37, in load
    struct.unpack('c' * self.color_size_bytes,
struct.error: unpack requires a buffer of 265617 bytes
"""

Additional information

I can train fine, but when I run the script for test.py, it reports the error FileNotFoundError: [Errno 2] No such file or directory: 'data/scannet/posed_images/scene0568_00/00000.jpg. . After checking, I found that there was no such image in that path (it seems that not all of them were converted during my first convert), so I re-ran the generate_image_scannet.py script. But it fails, with the error as described above. (Oddly enough, it works at my first run) I added the following two lines to the source code:

                try.
                    frame.load(f)
                except Exception as e.
                  print(f)

which prints the following.

<_io.BufferedReader name='scans/scene0548_00/scene0548_00.sens'>
unpack requires a buffer of 64 bytes

It seems to be a buffer shortage? I would like to know how to solve this problem. Also, since I have already converted most of the scannet data, is there any way to just specify the converted files to save time.

Thnak you for your intime help.

Mintinson commented 2 months ago

I have found the solution. It seems to be because there is corruption in the specified data, I re-downloaded the specified scene and this time it works. But when I execute test.py, it still doesn't go through and reports the following error:

Traceback (most recent call last):
  File "tools/test.py", line 157, in <module>
    main()
  File "tools/test.py", line 153, in main
    runner.test()
  File "/root/miniconda3/envs/embodiedscan/lib/python3.8/site-packages/mmengine/runner/runner.py", line 1823, in test
    metrics = self.test_loop.run()  # type: ignore
  File "/root/miniconda3/envs/embodiedscan/lib/python3.8/site-packages/mmengine/runner/loops.py", line 463, in run
    self.run_iter(idx, data_batch)
  File "/root/miniconda3/envs/embodiedscan/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "/root/miniconda3/envs/embodiedscan/lib/python3.8/site-packages/mmengine/runner/loops.py", line 487, in run_iter
    outputs = self.runner.model.test_step(data_batch)
  File "/root/miniconda3/envs/embodiedscan/lib/python3.8/site-packages/mmengine/model/base_model/base_model.py", line 145, in test_step
    return self._run_forward(data, mode='predict')  # type: ignore
  File "/root/miniconda3/envs/embodiedscan/lib/python3.8/site-packages/mmengine/model/base_model/base_model.py", line 361, in _run_forward
    results = self(**data, mode=mode)
  File "/root/miniconda3/envs/embodiedscan/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
    return forward_call(*input, **kwargs)
  File "/root/EmbodiedScan/embodiedscan/models/detectors/sparse_featfusion_grounder.py", line 681, in forward
    return self.predict(inputs, data_samples, **kwargs)
  File "/root/EmbodiedScan/embodiedscan/models/detectors/sparse_featfusion_grounder.py", line 538, in predict
    positive_maps = self.get_positive_map(tokenized, tokens_positive)
  File "/root/EmbodiedScan/embodiedscan/models/detectors/sparse_featfusion_grounder.py", line 632, in get_positive_map
    positive_map = self.create_positive_map(tokenized, tp, idx)
  File "/root/EmbodiedScan/embodiedscan/models/detectors/sparse_featfusion_grounder.py", line 595, in create_positive_map
    for (beg, end) in tok_list:
TypeError: cannot unpack non-iterable int object
henryzhengr commented 2 months ago

In the grounder decoder file, change the following lines in predict function in sparse_featfusion_grounder L532-L533

to the following code

  tokens_positive = [[[[0, 1]]]
                     for _ in range(len(batch_data_samples))]
Mintinson commented 2 months ago

Thanks! It works!

mxh1999 commented 2 months ago

Thank you a lot for pointing out this bug, we'll fix it in the next update!