VAD脚本处理nuscenes数据

参考下面链接配置环境:

VAD/docs/install.md at main · hustvl/VAD (github.com)icon-default.png?t=N7T8https://github.com/hustvl/VAD/blob/main/docs/install.md中间遇到的问题:

Couldn't find a setup script in /tmp/easy_install-wdsk8wzm/scikit_image-0.23.2.tar.gz

参考:error: Couldn't find a setup script in /tmp/easy_install-ian85kkj/scikit_image-0.23.2.tar.gz · Issue #251 · fundamentalvision/BEVFormer (github.com)

解决方案是

pip install scikit-image==0.21.0

然后开始运行,还是会遇到一系列问题:

第一个 缺少llvmlite库

  File "/home/dwc_42526/anaconda3/envs/vad/lib/python3.8/site-packages/numpy/__init__.py", line 320, in __getattr__
    raise AttributeError("module {!r} has no attribute "
AttributeError: module 'numpy' has no attribute 'long'

原因是numpy的版本太高了,指定低版本安装一下:

pip install numpy==1.21.1

 

No module named 'llvmlite.llvmpy'

2025-06-26 16:12:03,164 - mmdet - INFO - Saving checkpoint at 12 epochs [ ] 0/81, elapsed: 0s, ETA:/home/wangbaihui/anaconda3/envs/vad/lib/python3.8/site-packages/torch/_tensor.py:575: UserWarning: floor_divide is deprecated, and will be removed in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor'). (Triggered internally at ../aten/src/ATen/native/BinaryOps.cpp:467.) return torch.floor_divide(self, other) [ ] 1/81, 0.3 task/s, elapsed: 3s, ETA: 273s/media/wangbaihui/1ecf654b-afad-4dab-af7b-e34b00dda87a/mmdetection3d/VAD/projects/mmdet3d_plugin/core/bbox/coders/fut_nms_free_coder.py:78: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor). self.post_center_range = torch.tensor( /media/wangbaihui/1ecf654b-afad-4dab-af7b-e34b00dda87a/mmdetection3d/VAD/projects/mmdet3d_plugin/core/bbox/coders/map_nms_free_coder.py:82: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor). self.post_center_range = torch.tensor( [>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>] 81/81, 4.5 task/s, elapsed: 18s, ETA: 0s Traceback (most recent call last): File "tools/train.py", line 266, in <module> main() File "tools/train.py", line 255, in main custom_train_model( File "/media/wangbaihui/1ecf654b-afad-4dab-af7b-e34b00dda87a/mmdetection3d/VAD/projects/mmdet3d_plugin/VAD/apis/train.py", line 21, in custom_train_model custom_train_detector( File "/media/wangbaihui/1ecf654b-afad-4dab-af7b-e34b00dda87a/mmdetection3d/VAD/projects/mmdet3d_plugin/VAD/apis/mmdet_train.py", line 194, in custom_train_detector runner.run(data_loaders, cfg.workflow) File "/home/wangbaihui/anaconda3/envs/vad/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 127, in run epoch_runner(data_loaders[i], **kwargs) File "/home/wangbaihui/anaconda3/envs/vad/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 54, in train self.call_hook('after_train_epoch') File "/home/wangbaihui/anaconda3/envs/vad/lib/python3.8/site-packages/mmcv/runner/base_runner.py", line 307, in call_hook getattr(hook, fn_name)(self) File "/home/wangbaihui/anaconda3/envs/vad/lib/python3.8/site-packages/mmcv/runner/hooks/evaluation.py", line 267, in after_train_epoch self._do_evaluate(runner) File "/media/wangbaihui/1ecf654b-afad-4dab-af7b-e34b00dda87a/mmdetection3d/VAD/projects/mmdet3d_plugin/core/evaluation/eval_hooks.py", line 88, in _do_evaluate key_score = self.evaluate(runner, results) File "/home/wangbaihui/anaconda3/envs/vad/lib/python3.8/site-packages/mmcv/runner/hooks/evaluation.py", line 361, in evaluate eval_res = self.dataloader.dataset.evaluate( File "/media/wangbaihui/1ecf654b-afad-4dab-af7b-e34b00dda87a/mmdetection3d/VAD/projects/mmdet3d_plugin/datasets/nuscenes_vad_dataset.py", line 1781, in evaluate all_metric_dict[key] += results[i]['metric_results'][key] KeyError: 0 ERROR:torch.distributed.elastic.multiprocessing.api:failed (exitcode: 1) local_rank: 0 (pid: 2522198) of binary: /home/wangbaihui/anaconda3/envs/vad/bin/python /home/wangbaihui/anaconda3/envs/vad/lib/python3.8/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py:367: UserWarning: ********************************************************************** CHILD PROCESS FAILED WITH NO ERROR_FILE ********************************************************************** CHILD PROCESS FAILED WITH NO ERROR_FILE Child process 2522198 (local_rank 0) FAILED (exitcode 1) Error msg: Process failed with exitcode 1 Without writing an error file to <N/A>. While this DOES NOT affect the correctness of your application, no trace information about the error will be available for inspection. Consider decorating your top level entrypoint function with torch.distributed.elastic.multiprocessing.errors.record. Example: from torch.distributed.elastic.multiprocessing.errors import record @record def trainer_main(args): # do train ********************************************************************** warnings.warn(_no_error_file_warning_msg(rank, failure)) Traceback (most recent call last): File "/home/wangbaihui/anaconda3/envs/vad/lib/python3.8/runpy.py", line 194, in _run_module_as_main return _run_code(code, main_globals, None, File "/home/wangbaihui/anaconda3/envs/vad/lib/python3.8/runpy.py", line 87, in _run_code exec(code, run_globals) File "/home/wangbaihui/anaconda3/envs/vad/lib/python3.8/site-packages/torch/distributed/run.py", line 702, in <module> main() File "/home/wangbaihui/anaconda3/envs/vad/lib/python3.8/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 361, in wrapper return f(*args, **kwargs) File "/home/wangbaihui/anaconda3/envs/vad/lib/python3.8/site-packages/torch/distributed/run.py", line 698, in main run(args) File "/home/wangbaihui/anaconda3/envs/vad/lib/python3.8/site-packages/torch/distributed/run.py", line 689, in run elastic_launch( File "/home/wangbaihui/anaconda3/envs/vad/lib/python3.8/site-packages/torch/distributed/launcher/api.py", line 116, in __call__ return launch_agent(self._config, self._entrypoint, list(args)) File "/home/wangbaihui/anaconda3/envs/vad/lib/python3.8/site-packages/torch/distributed/launcher/api.py", line 244, in launch_agent raise ChildFailedError( torch.distributed.elastic.multiprocessing.errors.ChildFailedError: *************************************** tools/train.py FAILED ======================================= Root Cause: [0]: time: 2025-06-26_16:12:28 rank: 0 (local_rank: 0) exitcode: 1 (pid: 2522198) error_file: <N/A> msg: "Process failed with exitcode 1" ======================================= Other Failures: <NO_OTHER_FAILURES> ***********2025-06-26 16:12:03,164 - mmdet - INFO - Saving checkpoint at 12 epochs [ ] 0/81, elapsed: 0s, ETA:/home/wangbaihui/anaconda3/envs/vad/lib/python3.8/site-packages/torch/_tensor.py:575: UserWarning: floor_divide is deprecated, and will be removed in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor'). (Triggered internally at ../aten/src/ATen/native/BinaryOps.cpp:467.) return torch.floor_divide(self, other) [ ] 1/81, 0.3 task/s, elapsed: 3s, ETA: 273s/media/wangbaihui/1ecf654b-afad-4dab-af7b-e34b00dda87a/mmdetection3d/VAD/projects/mmdet3d_plugin/core/bbox/coders/fut_nms_free_coder.py:78: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor). self.post_center_range = torch.tensor( /media/wangbaihui/1ecf654b-afad-4dab-af7b-e34b00dda87a/mmdetection3d/VAD/projects/mmdet3d_plugin/core/bbox/coders/map_nms_free_coder.py:82: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor). self.post_center_range = torch.tensor( [>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>] 81/81, 4.5 task/s, elapsed: 18s, ETA: 0s Traceback (most recent call last): File "tools/train.py", line 266, in <module> main() File "tools/train.py", line 255, in main custom_train_model( File "/media/wangbaihui/1ecf654b-afad-4dab-af7b-e34b00dda87a/mmdetection3d/VAD/projects/mmdet3d_plugin/VAD/apis/train.py", line 21, in custom_train_model custom_train_detector( File "/media/wangbaihui/1ecf654b-afad-4dab-af7b-e34b00dda87a/mmdetection3d/VAD/projects/mmdet3d_plugin/VAD/apis/mmdet_train.py", line 194, in custom_train_detector runner.run(data_loaders, cfg.workflow) File "/home/wangbaihui/anaconda3/envs/vad/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 127, in run epoch_runner(data_loaders[i], **kwargs) File "/home/wangbaihui/anaconda3/envs/vad/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 54, in train self.call_hook('after_train_epoch') File "/home/wangbaihui/anaconda3/envs/vad/lib/python3.8/site-packages/mmcv/runner/base_runner.py", line 307, in call_hook getattr(hook, fn_name)(self) File "/home/wangbaihui/anaconda3/envs/vad/lib/python3.8/site-packages/mmcv/runner/hooks/evaluation.py", line 267, in after_train_epoch self._do_evaluate(runner) File "/media/wangbaihui/1ecf654b-afad-4dab-af7b-e34b00dda87a/mmdetection3d/VAD/projects/mmdet3d_plugin/core/evaluation/eval_hooks.py", line 88, in _do_evaluate key_score = self.evaluate(runner, results) File "/home/wangbaihui/anaconda3/envs/vad/lib/python3.8/site-packages/mmcv/runner/hooks/evaluation.py", line 361, in evaluate eval_res = self.dataloader.dataset.evaluate( File "/media/wangbaihui/1ecf654b-afad-4dab-af7b-e34b00dda87a/mmdetection3d/VAD/projects/mmdet3d_plugin/datasets/nuscenes_vad_dataset.py", line 1781, in evaluate all_metric_dict[key] += results[i]['metric_results'][key] KeyError: 0 ERROR:torch.distributed.elastic.multiprocessing.api:failed (exitcode: 1) local_rank: 0 (pid: 2522198) of binary: /home/wangbaihui/anaconda3/envs/vad/bin/python /home/wangbaihui/anaconda3/envs/vad/lib/python3.8/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py:367: UserWarning: ********************************************************************** CHILD PROCESS FAILED WITH NO ERROR_FILE ********************************************************************** CHILD PROCESS FAILED WITH NO ERROR_FILE Child process 2522198 (local_rank 0) FAILED (exitcode 1) Error msg: Process failed with exitcode 1 Without writing an error file to <N/A>. While this DOES NOT affect the correctness of your application, no trace information about the error will be available for inspection. Consider decorating your top level entrypoint function with torch.distributed.elastic.multiprocessing.errors.record. Example: from torch.distributed.elastic.multiprocessing.errors import record @record def trainer_main(args): # do train ********************************************************************** warnings.warn(_no_error_file_warning_msg(rank, failure)) Traceback (most recent call last): File "/home/wangbaihui/anaconda3/envs/vad/lib/python3.8/runpy.py", line 194, in _run_module_as_main return _run_code(code, main_globals, None, File "/home/wangbaihui/anaconda3/envs/vad/lib/python3.8/runpy.py", line 87, in _run_code exec(code, run_globals) File "/home/wangbaihui/anaconda3/envs/vad/lib/python3.8/site-packages/torch/distributed/run.py", line 702, in <module> main() File "/home/wangbaihui/anaconda3/envs/vad/lib/python3.8/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 361, in wrapper return f(*args, **kwargs) File "/home/wangbaihui/anaconda3/envs/vad/lib/python3.8/site-packages/torch/distributed/run.py", line 698, in main run(args) File "/home/wangbaihui/anaconda3/envs/vad/lib/python3.8/site-packages/torch/distributed/run.py", line 689, in run elastic_launch( File "/home/wangbaihui/anaconda3/envs/vad/lib/python3.8/site-packages/torch/distributed/launcher/api.py", line 116, in __call__ return launch_agent(self._config, self._entrypoint, list(args)) File "/home/wangbaihui/anaconda3/envs/vad/lib/python3.8/site-packages/torch/distributed/launcher/api.py", line 244, in launch_agent raise ChildFailedError( torch.distributed.elastic.multiprocessing.errors.ChildFailedError: *************************************** tools/train.py FAILED ======================================= Root Cause: [0]: time: 2025-06-26_16:12:28 rank: 0 (local_rank: 0) exitcode: 1 (pid: 2522198) error_file: <N/A> msg: "Process failed with exitcode 1" ======================================= Other Failures: <NO_OTHER_FAILURES> ***********
06-27
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