Segmentation with known-working code[Bug]

[biotom]

Prerequisite

• I have searched Issues and Discussions but cannot get the expected help.
• The bug has not been fixed in the latest version(https://github.com/open-mmlab/mmpose).

Environment

Hello,
I recently pulled the latest version of MMPose and tried to run some code using the Inferencer interface, and I get a segmentation fault error.

Following the FAQ, 'python3 -c 'import torch; print(torch.cuda.is_available())'' returns True, and 'python3 -c 'import mmcv; import mmcv.ops'' doesn't return any errors, so I'm assuming the problem is my GCC version, which is 11.4.
The output of python -c "from mmpose.utils import collect_env; print(collect_env())" is:

" OrderedDict([('sys.platform', 'linux'), ('Python', '3.8.18 | packaged by conda-forge | (default, Dec 23 2023, 17:21:28) [GCC 12.3.0]'), ('CUDA available', True), ('MUSA available', False), ('numpy_random_seed', 2147483648), ('GPU 0', 'NVIDIA RTX A2000 12GB'), ('CUDA_HOME', '/home/luigi/anaconda3/envs/mmpose'), ('NVCC', 'Cuda compilation tools, release 11.8, V11.8.89'), ('GCC', 'gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0'), ('PyTorch', '2.3.0'), ('PyTorch compiling details', 'PyTorch built with:\n - GCC 9.3\n - C++ Version: 201703\n - Intel(R) oneAPI Math Kernel Library Version 2023.1-Product Build 20230303 for Intel(R) 64 architecture applications\n - Intel(R) MKL-DNN v3.3.6 (Git Hash 86e6af5974177e513fd3fee58425e1063e7f1361)\n - OpenMP 201511 (a.k.a. OpenMP 4.5)\n - LAPACK is enabled (usually provided by MKL)\n - NNPACK is enabled\n - CPU capability usage: AVX512\n - CUDA Runtime 11.8\n - NVCC architecture flags: -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=sm_37;-gencode;arch=compute_90,code=sm_90;-gencode;arch=compute_37,code=compute_37\n - CuDNN 8.7\n - Magma 2.6.1\n - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.8, CUDNN_VERSION=8.7.0, CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -D_GLIBCXX_USE_CXX11_ABI=0 -fabi-version=11 -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOROCTRACER -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-strict-overflow -Wno-strict-aliasing -Wno-stringop-overflow -Wsuggest-override -Wno-psabi -Wno-error=pedantic -Wno-error=old-style-cast -Wno-missing-braces -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=2.3.0, USE_CUDA=ON, USE_CUDNN=ON, USE_CUSPARSELT=1, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_GLOO=ON, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, USE_ROCM_KERNEL_ASSERT=OFF, \n'), ('TorchVision', '0.18.0'), ('OpenCV', '4.9.0'), ('MMEngine', '0.10.3'), ('MMPose', '1.3.1+')])

and pip list | grep mm is:
mmcv 2.1.0 mmdet 3.2.0 mmengine 0.10.3 mmpose 1.3.1 /home/luigi/mmpose

Is there anything obvious I'm doing wrong?

Reproduces the problem - code sample

from mmpose.apis import MMPoseInferencer
from pathlib import Path
import os

data_folder = Path(os.getcwd())
print(data_folder)

for filename in os.listdir(data_folder):
if not filename.endswith('.mp4'):
continue
img_path = os.path.join(data_folder, filename)

print(img_path)
inferencer = MMPoseInferencer('human')


result_generator = inferencer(img_path, out_dir='ouput_all')
results = [result for result in result_generator]
print(results)

Reproduces the problem - command or script

python3 posedetection.py

Reproduces the problem - error message

Loads checkpoint by http backend from path: https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/rtmpose-m_simcc-body7_pt-body7_420e-256x192-e48f03d0_20230504.pth 05/08 15:19:35 - mmengine - WARNING - Failed to search registry with scope "mmpose" in the "function" registry tree. As a workaround, the current "function" registry in "mmengine" is used to build instance. This may cause unexpected failure when running the built modules. Please check whether "mmpose" is a correct scope, or whether the registry is initialized. Loads checkpoint by http backend from path: https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/rtmdet_m_8xb32-100e_coco-obj365-person-235e8209.pth 05/08 15:19:35 - mmengine - WARNING - Failed to search registry with scope "mmdet" in the "function" registry tree. As a workaround, the current "function" registry in "mmengine" is used to build instance. This may cause unexpected failure when running the built modules. Please check whether "mmdet" is a correct scope, or whether the registry is initialized. /home/luigi/anaconda3/envs/mmpose/lib/python3.8/site-packages/torch/functional.py:512: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at /opt/conda/conda-bld/pytorch_1712608843393/work/aten/src/ATen/native/TensorShape.cpp:3587.) return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] Segmentation fault (core dumped)

Additional information

No response