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Issue with AssertionError during Runtime #1
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Hi Xiaohuahuaw, Thank you for taking an interest in our work and informing us of errors you encountered. I run the code again and it works for me. You should download libra_retinanet_r50_fpn_1x_coco.py (save it to ./perception/) and libra_retinanet_r50_fpn_1x_coco_20200205-804d94ce.pth (save it to ./perception/configs). I guess you can find both files in https://github.com/open-mmlab/mmdetection/tree/master/configs/libra_rcnn. You may also try other backbones as mmdetection provides various pre-trained models. Here are the versions of some important packages we use, can you try again and let me know if you still have the same error? |
Thank you for your detailed response! I have followed the steps you mentioned to download and configure the libra_retinanet_r50_fpn_1x_coco.py and libra_retinanet_r50_fpn_1x_coco_20200205-804d94ce.pth files. (actually, I had downloaded them earlier). Additionally, I have updated mmcv and mmdet to the versions you provided. However, I still encounter the same error. Specifically, when running the "python train-det.py ./configs/perception-types.py" command, I still receive the following error message: AssertionError: train_cfg specified in both the outer field and model field. Is there any other possible solution or advice you could provide? Thank you for your assistance! |
Hello,
I encountered an error when running the command "python train-det.py ./configs/perception-types.py." The error message is as follows: AssertionError: train_cfg specified in both the outer field and model field.
After reviewing the code, I initially attempted to address the issue by commenting out the assert code. However, this led to a new error: TypeError: RetinaNet: init() got an unexpected keyword argument 'data_preprocessor.'
My runtime environment includes Python 3.8, PyTorch version 1.9.1, mmcv-full version 1.7.2, and mmdet version 2.28.0.
Despite thorough code inspection, I have been unable to resolve the problem. Could you provide assistance in finding a solution? Your help is greatly appreciated!
Thanks in advance.
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