Comments (2)
hello,I haven't changed your code,but there is a problem:
" File "E:/python_console/pose_2/Poseur-main1/tools/train.py", line 202, in
main()
File "E:/python_console/pose_2/Poseur-main1/tools/train.py", line 198, in main
meta=meta)
File "E:\python_console\pose_2\Poseur-main\mmpose\apis\train.py", line 212, in train_model
runner.run(data_loaders, cfg.workflow, cfg.total_epochs)
File "E:\ana\envs\ptorch\lib\site-packages\mmcv\runner\epoch_based_runner.py", line 136, in run
epoch_runner(data_loaders[i], **kwargs)
File "E:\ana\envs\ptorch\lib\site-packages\mmcv\runner\epoch_based_runner.py", line 53, in train
self.run_iter(data_batch, train_mode=True, **kwargs)
File "E:\ana\envs\ptorch\lib\site-packages\mmcv\runner\epoch_based_runner.py", line 32, in run_iter
**kwargs)
File "E:\ana\envs\ptorch\lib\site-packages\mmcv\parallel\data_parallel.py", line 77, in train_step
return self.module.train_step(*inputs[0], **kwargs[0])
File "E:\python_console\pose_2\Poseur-main\mmpose\models\detectors\base.py", line 95, in train_step
losses = self.forward(**data_batch)
File "E:\ana\envs\ptorch\lib\site-packages\mmcv\runner\fp16_utils.py", line 146, in new_func
output = old_func(*new_args, **new_kwargs)
File "E:\python_console\pose_2\Poseur-main\mmpose\models\detectors\poseur.py", line 92, in forward
**kwargs)
File "E:\python_console\pose_2\Poseur-main\mmpose\models\detectors\poseur.py", line 115, in forward_train
output = self.keypoint_head(output, img_metas)
File "E:\ana\envs\ptorch\lib\site-packages\torch\nn\modules\module.py", line 1130, in _call_impl
return forward_call(*input, **kwargs)
TypeError: forward() takes 2 positional arguments but 3 were given"
what is the keypoint_head's input?
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Hi, @flomok, the input of keypoint head is the multi-level features from the neck. You can pull the code from the main branch and try it again. We have fixed the problem.
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Related Issues (17)
- About the reproducibility HOT 1
- Prediction uncertainty estimation. HOT 3
- The URL for downloading the poseur_mobilenetv2_coco_256x192 model is linked to the poseur_res50_coco_256x192 model HOT 3
- when will the full model release? HOT 4
- About RLELoss_poseur HOT 1
- the input of keypoint head
- How to train on MPII HOT 1
- How to train on my own dataset? HOT 3
- convert to onnx failed
- Did RLELoss use with hm Loss? HOT 1
- Welcome update to OpenMMLab 2.0
- How many GPUs dose the training process consume HOT 1
- KeyError: 'Poseur is not in the models registry' HOT 4
- mmpose and mmcv version HOT 3
- About the MPII dataset
- Multi-person case
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