INDEXERROR

[rookie0414]

022-05-15 19:59:08,729 - mmdet - INFO - workflow: [('train', 1)], max: 25 epochs
Traceback (most recent call last):
File "tools/train.py", line 189, in
main()
File "tools/train.py", line 178, in main
train_detector(
File "/media/dmedia/df97e94d-c388-4fab-aa15-6192cdbdef17/xmx/ccc/ViTDet-main/mmdet/apis/train.py", line 180, in train_detector
runner.run(data_loaders, cfg.workflow)
File "/media/dmedia/df97e94d-c388-4fab-aa15-6192cdbdef17/xmx/ccc/ViTDet-main/mmcv/mmcv/runner/epoch_based_runner.py", line 127, in run
epoch_runner(data_loaders[i], **kwargs)
File "/media/dmedia/df97e94d-c388-4fab-aa15-6192cdbdef17/xmx/ccc/ViTDet-main/mmcv/mmcv/runner/epoch_based_runner.py", line 47, in train
for i, data_batch in enumerate(self.data_loader):
File "/home/dmedia/anaconda3/envs/captionC/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 521, in next
data = self._next_data()
File "/home/dmedia/anaconda3/envs/captionC/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 561, in _next_data
data = self._dataset_fetcher.fetch(index) # may raise StopIteration
File "/home/dmedia/anaconda3/envs/captionC/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 49, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/dmedia/anaconda3/envs/captionC/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 49, in
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/media/dmedia/df97e94d-c388-4fab-aa15-6192cdbdef17/xmx/ccc/ViTDet-main/mmdet/datasets/dataset_wrappers.py", line 154, in getitem
return self.dataset[idx % self._ori_len]
File "/media/dmedia/df97e94d-c388-4fab-aa15-6192cdbdef17/xmx/ccc/ViTDet-main/mmdet/datasets/custom.py", line 195, in getitem
data = self.prepare_train_img(idx)
File "/media/dmedia/df97e94d-c388-4fab-aa15-6192cdbdef17/xmx/ccc/ViTDet-main/mmdet/datasets/custom.py", line 218, in prepare_train_img
return self.pipeline(results)
File "/media/dmedia/df97e94d-c388-4fab-aa15-6192cdbdef17/xmx/ccc/ViTDet-main/mmdet/datasets/pipelines/compose.py", line 41, in call
data = t(data)
File "/media/dmedia/df97e94d-c388-4fab-aa15-6192cdbdef17/xmx/ccc/ViTDet-main/mmdet/datasets/pipelines/loading.py", line 377, in call
results = self._load_masks(results)
File "/media/dmedia/df97e94d-c388-4fab-aa15-6192cdbdef17/xmx/ccc/ViTDet-main/mmdet/datasets/pipelines/loading.py", line 329, in _load_masks
[self._poly2mask(mask, h, w) for mask in gt_masks], h, w)
File "/media/dmedia/df97e94d-c388-4fab-aa15-6192cdbdef17/xmx/ccc/ViTDet-main/mmdet/datasets/pipelines/loading.py", line 329, in
[self._poly2mask(mask, h, w) for mask in gt_masks], h, w)
File "/media/dmedia/df97e94d-c388-4fab-aa15-6192cdbdef17/xmx/ccc/ViTDet-main/mmdet/datasets/pipelines/loading.py", line 285, in _poly2mask
rles = maskUtils.frPyObjects(mask_ann, img_h, img_w)
File "pycocotools/_mask.pyx", line 292, in pycocotools._mask.frPyObjects
IndexError: list index out of range
Traceback (most recent call last):
File "tools/train.py", line 189, in
main()
File "tools/train.py", line 178, in main
train_detector(
File "/media/dmedia/df97e94d-c388-4fab-aa15-6192cdbdef17/xmx/ccc/ViTDet-main/mmdet/apis/train.py", line 180, in train_detector
runner.run(data_loaders, cfg.workflow)
File "/media/dmedia/df97e94d-c388-4fab-aa15-6192cdbdef17/xmx/ccc/ViTDet-main/mmcv/mmcv/runner/epoch_based_runner.py", line 127, in run
epoch_runner(data_loaders[i], **kwargs)
File "/media/dmedia/df97e94d-c388-4fab-aa15-6192cdbdef17/xmx/ccc/ViTDet-main/mmcv/mmcv/runner/epoch_based_runner.py", line 47, in train
for i, data_batch in enumerate(self.data_loader):
File "/home/dmedia/anaconda3/envs/captionC/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 521, in next
data = self._next_data()
File "/home/dmedia/anaconda3/envs/captionC/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 561, in _next_data
data = self._dataset_fetcher.fetch(index) # may raise StopIteration
File "/home/dmedia/anaconda3/envs/captionC/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 49, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/dmedia/anaconda3/envs/captionC/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 49, in
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/media/dmedia/df97e94d-c388-4fab-aa15-6192cdbdef17/xmx/ccc/ViTDet-main/mmdet/datasets/dataset_wrappers.py", line 154, in getitem
return self.dataset[idx % self._ori_len]
File "/media/dmedia/df97e94d-c388-4fab-aa15-6192cdbdef17/xmx/ccc/ViTDet-main/mmdet/datasets/custom.py", line 195, in getitem
data = self.prepare_train_img(idx)
File "/media/dmedia/df97e94d-c388-4fab-aa15-6192cdbdef17/xmx/ccc/ViTDet-main/mmdet/datasets/custom.py", line 218, in prepare_train_img
return self.pipeline(results)
File "/media/dmedia/df97e94d-c388-4fab-aa15-6192cdbdef17/xmx/ccc/ViTDet-main/mmdet/datasets/pipelines/compose.py", line 41, in call
data = t(data)
File "/media/dmedia/df97e94d-c388-4fab-aa15-6192cdbdef17/xmx/ccc/ViTDet-main/mmdet/datasets/pipelines/loading.py", line 377, in call
results = self._load_masks(results)
File "/media/dmedia/df97e94d-c388-4fab-aa15-6192cdbdef17/xmx/ccc/ViTDet-main/mmdet/datasets/pipelines/loading.py", line 329, in _load_masks
[self._poly2mask(mask, h, w) for mask in gt_masks], h, w)
File "/media/dmedia/df97e94d-c388-4fab-aa15-6192cdbdef17/xmx/ccc/ViTDet-main/mmdet/datasets/pipelines/loading.py", line 329, in
[self._poly2mask(mask, h, w) for mask in gt_masks], h, w)
File "/media/dmedia/df97e94d-c388-4fab-aa15-6192cdbdef17/xmx/ccc/ViTDet-main/mmdet/datasets/pipelines/loading.py", line 285, in _poly2mask
rles = maskUtils.frPyObjects(mask_ann, img_h, img_w)
File "pycocotools/_mask.pyx", line 292, in pycocotools._mask.frPyObjects
IndexError: list index out of range
ERROR:torch.distributed.elastic.multiprocessing.api:failed (exitcode: 1) local_rank: 0 (pid: 743363) of binary: /home/dmedia/anaconda3/envs/captionC/bin/python
Traceback (most recent call last):
File "/home/dmedia/anaconda3/envs/captionC/lib/python3.8/runpy.py", line 194, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/home/dmedia/anaconda3/envs/captionC/lib/python3.8/runpy.py", line 87, in _run_code
exec(code, run_globals)
File "/home/dmedia/anaconda3/envs/captionC/lib/python3.8/site-packages/torch/distributed/launch.py", line 193, in
main()
File "/home/dmedia/anaconda3/envs/captionC/lib/python3.8/site-packages/torch/distributed/launch.py", line 189, in main
launch(args)
File "/home/dmedia/anaconda3/envs/captionC/lib/python3.8/site-packages/torch/distributed/launch.py", line 174, in launch
run(args)
File "/home/dmedia/anaconda3/envs/captionC/lib/python3.8/site-packages/torch/distributed/run.py", line 710, in run
elastic_launch(
File "/home/dmedia/anaconda3/envs/captionC/lib/python3.8/site-packages/torch/distributed/launcher/api.py", line 131, in call
return launch_agent(self._config, self._entrypoint, list(args))
File "/home/dmedia/anaconda3/envs/captionC/lib/python3.8/site-packages/torch/distributed/launcher/api.py", line 259, in launch_agent
raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError:

Sorry to bother you, but this issue has not been resolved. I want to ask your opinion. Another thing is whether the image size of the dataset should be resized to 1024*1024. I still have this problem after resize.

[Annbless]

The issue

It seems that there is no mask data in the dataset directory. If the mask data is not available or expected.to use, please disable the mask loading options from the data processing pipelines.

The image size

Temporally, the answer is yes. We resize the images following their original aspect ratio and padding them to 1024*1024. It seems that your issue is not related to the resize operation but the lack of mask data.

[rookie0414]

an you tell me to disable mask data there? A new error is reported when I set withmask to false. Looking forward to your reply。
2022-05-25 09:48:17,966 - mmdet - INFO - workflow: [('train', 1)], max: 25 epochs
/home/x3022/anaconda3/envs/vitdet/lib/python3.8/site-packages/torch/nn/functional.py:718: UserWarning: Named tensors and all their associated APIs are an experimental feature and subject to change. Please do not use them for anything important until they are released as stable. (Triggered internally at /pytorch/c10/core/TensorImpl.h:1156.)
return torch.max_pool2d(input, kernel_size, stride, padding, dilation, ceil_mode)
Traceback (most recent call last):
File "tools/train.py", line 189, in
main()
File "tools/train.py", line 178, in main
train_detector(
File "/home/x3022/anaconda3/envs/vitdet/lib/python3.8/site-packages/mmdet-2.18.0-py3.8.egg/mmdet/apis/train.py", line 180, in train_detector
runner.run(data_loaders, cfg.workflow)
File "/home/x3022/xmx/ViTDet-main/mmcv/mmcv/runner/epoch_based_runner.py", line 127, in run
epoch_runner(data_loaders[i], **kwargs)
File "/home/x3022/xmx/ViTDet-main/mmcv/mmcv/runner/epoch_based_runner.py", line 50, in train
self.run_iter(data_batch, train_mode=True, **kwargs)
File "/home/x3022/xmx/ViTDet-main/mmcv/mmcv/runner/epoch_based_runner.py", line 29, in run_iter
outputs = self.model.train_step(data_batch, self.optimizer,
File "/home/x3022/xmx/ViTDet-main/mmcv/mmcv/parallel/data_parallel.py", line 67, in train_step
return self.module.train_step(*inputs[0], **kwargs[0])
File "/home/x3022/anaconda3/envs/vitdet/lib/python3.8/site-packages/mmdet-2.18.0-py3.8.egg/mmdet/models/detectors/base.py", line 238, in train_step
losses = self(**data)
File "/home/x3022/anaconda3/envs/vitdet/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/home/x3022/xmx/ViTDet-main/mmcv/mmcv/runner/fp16_utils.py", line 98, in new_func
return old_func(*args, **kwargs)
File "/home/x3022/anaconda3/envs/vitdet/lib/python3.8/site-packages/mmdet-2.18.0-py3.8.egg/mmdet/models/detectors/base.py", line 172, in forward
return self.forward_train(img, img_metas, **kwargs)
File "/home/x3022/anaconda3/envs/vitdet/lib/python3.8/site-packages/mmdet-2.18.0-py3.8.egg/mmdet/models/detectors/two_stage.py", line 147, in forward_train
roi_losses = self.roi_head.forward_train(x, img_metas, proposal_list,
File "/home/x3022/anaconda3/envs/vitdet/lib/python3.8/site-packages/mmdet-2.18.0-py3.8.egg/mmdet/models/roi_heads/standard_roi_head.py", line 111, in forward_train
mask_results = self._mask_forward_train(x, sampling_results,
File "/home/x3022/anaconda3/envs/vitdet/lib/python3.8/site-packages/mmdet-2.18.0-py3.8.egg/mmdet/models/roi_heads/standard_roi_head.py", line 172, in _mask_forward_train
mask_targets = self.mask_head.get_targets(sampling_results, gt_masks,
File "/home/x3022/anaconda3/envs/vitdet/lib/python3.8/site-packages/mmdet-2.18.0-py3.8.egg/mmdet/models/roi_heads/mask_heads/fcn_mask_head.py", line 144, in get_targets
mask_targets = mask_target(pos_proposals, pos_assigned_gt_inds,
File "/home/x3022/anaconda3/envs/vitdet/lib/python3.8/site-packages/mmdet-2.18.0-py3.8.egg/mmdet/core/mask/mask_target.py", line 59, in mask_target
mask_targets = map(mask_target_single, pos_proposals_list,
TypeError: 'NoneType' object is not iterable

[Annbless]

Maybe you forgot to disable the mask prediction in the model definition?