GongDianCheng
commented
2 years ago Hi bro,have you solved this problem? I meet the same problem.
Open batuhanbeytekin opened 2 years ago
GongDianCheng
commented
2 years ago Hi bro,have you solved this problem? I meet the same problem.
I have tried to test my image with tusimple_small.pth. I ran this command line
python3 demo/image_demo.py ../linesDetected.jpg configs/condlanenet/tusimple/tusimple_small_test.py ../Downloads/tusimple_small.pth.When I run the command I get this error:
/home/batuhanbeytekin/conditional-lane-detection/mmdet/models/necks/trans_fpn.py:44: UserWarning: floordiv is deprecated, and its behavior will change 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'). dim_t = self.temperature*(2 (dim_t // 2) / self.num_pos_feats) /home/batuhanbeytekin/anaconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/functional.py:445: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at /opt/conda/conda-bld/pytorch_1640811797118/work/aten/src/ATen/native/TensorShape.cpp:2157.) return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] The model and loaded state dict do not match exactly
unexpected key in source state_dict: bbox_head.reg_branch.0.conv.weight, bbox_head.reg_branch.0.bn.weight, bbox_head.reg_branch.0.bn.bias, bbox_head.reg_branch.0.bn.running_mean, bbox_head.reg_branch.0.bn.running_var, bbox_head.reg_branch.0.bn.num_batches_tracked, bbox_head.reg_branch.1.conv.weight, bbox_head.reg_branch.1.bn.weight, bbox_head.reg_branch.1.bn.bias, bbox_head.reg_branch.1.bn.running_mean, bbox_head.reg_branch.1.bn.running_var, bbox_head.reg_branch.1.bn.num_batches_tracked, bbox_head.reg_branch.2.conv.weight, bbox_head.reg_branch.2.bn.weight, bbox_head.reg_branch.2.bn.bias, bbox_head.reg_branch.2.bn.running_mean, bbox_head.reg_branch.2.bn.running_var, bbox_head.reg_branch.2.bn.num_batches_tracked
Traceback (most recent call last): File "demo/image_demo.py", line 26, in
main()
File "demo/image_demo.py", line 20, in main
result = inference_detector(model, args.img)
File "/home/batuhanbeytekin/conditional-lane-detection/mmdet/apis/inference.py", line 82, in inference_detector
data = test_pipeline(data)
File "/home/batuhanbeytekin/conditional-lane-detection/mmdet/datasets/pipelines/compose.py", line 29, in call
data = t(data)
File "/home/batuhanbeytekin/conditional-lane-detection/mmdet/datasets/pipelines/lane_formating.py", line 420, in call
valid = self.target(results)
File "/home/batuhanbeytekin/conditional-lane-detection/mmdet/datasets/pipelines/lane_formating.py", line 332, in target
gt_points = results['gt_points']
KeyError: 'gt_points'
Does anyone know how to solve this problem?