[Bug] Error occurs during converting scanNet

[Mintinson]

Prerequisite

• I have searched Issues and Discussions but cannot get the expected help.
• I have read the FAQ documentation but cannot get the expected help.
• The bug has not been fixed in the latest version (dev-1.x) or latest version (dev-1.0).

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:

• GCC 7.3

• C++ Version: 201402

• Intel(R) oneAPI Math Kernel Library Version 2023.1-Product Build 20230303 for Intel(R) 64 architecture applications

• Intel(R) MKL-DNN v2.5.2 (Git Hash a9302535553c73243c632ad3c4c80beec3d19a1e)

• OpenMP 201511 (a.k.a. OpenMP 4.5)

• LAPACK is enabled (usually provided by MKL)

• NNPACK is enabled

• CPU capability usage: AVX2

• CUDA Runtime 11.3

• NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_37,code=compute_37

• CuDNN 8.2

• Magma 2.5.2

• Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.3, CUDNN_VERSION=8.2.0, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF,

  TorchVision: 0.12.0
  OpenCV: 4.10.0
  MMEngine: 0.10.5

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]

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]

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]

Thanks! It works!

[mxh1999]

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