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hustvl / TopFormer

TopFormer: Token Pyramid Transformer for Mobile Semantic Segmentation, CVPR2022
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Deploy test error with onnx backend #6

Closed wangyidong3 closed 2 years ago

wangyidong3 commented 2 years ago

Hello,

Thanks for sharing this great repo. I trained and test with my own dataset, the prediction results are quite good.

But when I exported the onnx file with command:

python3 tools/convert2onnx.py  local_configs/topformer/topformer_tiny_512x512_80k_2x8_drive_inviol1k.py --input-img results/0109.png --shape 512 512 --checkpoint results/tiny_20k/latest.pth --output-file results/tiny_80k/tiny_512_512.onnx --show

then try the deploy script with command: python tools/deploy_test.py local_configs/topformer/topformer_tiny_512x512_80k_2x8_drive_inviol1k.py results/tiny_80k/tiny_512_512.onnx --backend=onnxruntime --show

Then it show error:

File "tools/deploy_test.py", line 297, in main() File "tools/deploy_test.py", line 268, in main results = single_gpu_test( File "/home/yidong/anaconda3/envs/mask2former/lib/python3.8/site-packages/mmsegmentation-0.19.0-py3.8.egg/mmseg/apis/test.py", line 91, in single_gpu_test result = model(return_loss=False, data) File "/home/yidong/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl result = self.forward(*input, *kwargs) File "/home/yidong/anaconda3/envs/mask2former/lib/python3.8/site-packages/mmcv/parallel/data_parallel.py", line 42, in forward return super().forward(inputs, kwargs) File "/home/yidong/.local/lib/python3.8/site-packages/torch/nn/parallel/data_parallel.py", line 165, in forward return self.module(*inputs[0], kwargs[0]) File "/home/yidong/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl result = self.forward(*input, *kwargs) File "/home/yidong/anaconda3/envs/mask2former/lib/python3.8/site-packages/mmcv/runner/fp16_utils.py", line 98, in new_func return old_func(args, kwargs) File "/home/yidong/anaconda3/envs/mask2former/lib/python3.8/site-packages/mmsegmentation-0.19.0-py3.8.egg/mmseg/models/segmentors/base.py", line 110, in forward return self.forward_test(img, img_metas, kwargs) File "/home/yidong/anaconda3/envs/mask2former/lib/python3.8/site-packages/mmsegmentation-0.19.0-py3.8.egg/mmseg/models/segmentors/base.py", line 92, in forward_test return self.simple_test(imgs[0], img_metas[0], kwargs) File "tools/deploy_test.py", line 84, in simple_test self.sess.run_with_iobinding(self.io_binding) File "/home/yidong/anaconda3/envs/mask2former/lib/python3.8/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 276, in run_with_iobinding self._sess.run_with_iobinding(iobinding._iobinding, run_options) RuntimeError: Error in execution: Got invalid dimensions for input: input for the following indices index: 2 Got: 1080 Expected: 512 index: 3 Got: 1878 Expected: 512 Please fix either the inputs or the model.

Does it have any requirements for input images or shapes when export onnx file? the config setting as: img_scale = (1920, 1080) , crop_size = (512, 512).

I also tried some other shape size, still confused with this error and any helps would be much appreciated.

mulinmeng commented 2 years ago

Hello,

Thanks for sharing this great repo. I trained and test with my own dataset, the prediction results are quite good.

But when I exported the onnx file with command:

python3 tools/convert2onnx.py  local_configs/topformer/topformer_tiny_512x512_80k_2x8_drive_inviol1k.py --input-img results/0109.png --shape 512 512 --checkpoint results/tiny_20k/latest.pth --output-file results/tiny_80k/tiny_512_512.onnx --show

then try the deploy script with command: python tools/deploy_test.py local_configs/topformer/topformer_tiny_512x512_80k_2x8_drive_inviol1k.py results/tiny_80k/tiny_512_512.onnx --backend=onnxruntime --show

Then it show error:

File "tools/deploy_test.py", line 297, in main() File "tools/deploy_test.py", line 268, in main results = single_gpu_test( File "/home/yidong/anaconda3/envs/mask2former/lib/python3.8/site-packages/mmsegmentation-0.19.0-py3.8.egg/mmseg/apis/test.py", line 91, in single_gpu_test result = model(return_loss=False, data) File "/home/yidong/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl result = self.forward(*input, *kwargs) File "/home/yidong/anaconda3/envs/mask2former/lib/python3.8/site-packages/mmcv/parallel/data_parallel.py", line 42, in forward return super().forward(inputs, kwargs) File "/home/yidong/.local/lib/python3.8/site-packages/torch/nn/parallel/data_parallel.py", line 165, in forward return self.module(*inputs[0], kwargs[0]) File "/home/yidong/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl result = self.forward(*input, *kwargs) File "/home/yidong/anaconda3/envs/mask2former/lib/python3.8/site-packages/mmcv/runner/fp16_utils.py", line 98, in new_func return old_func(args, kwargs) File "/home/yidong/anaconda3/envs/mask2former/lib/python3.8/site-packages/mmsegmentation-0.19.0-py3.8.egg/mmseg/models/segmentors/base.py", line 110, in forward return self.forward_test(img, img_metas, kwargs) File "/home/yidong/anaconda3/envs/mask2former/lib/python3.8/site-packages/mmsegmentation-0.19.0-py3.8.egg/mmseg/models/segmentors/base.py", line 92, in forward_test return self.simple_test(imgs[0], img_metas[0], kwargs) File "tools/deploy_test.py", line 84, in simple_test self.sess.run_with_iobinding(self.io_binding) File "/home/yidong/anaconda3/envs/mask2former/lib/python3.8/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 276, in run_with_iobinding self._sess.run_with_iobinding(iobinding._iobinding, run_options) RuntimeError: Error in execution: Got invalid dimensions for input: input for the following indices index: 2 Got: 1080 Expected: 512 index: 3 Got: 1878 Expected: 512 Please fix either the inputs or the model.

Does it have any requirements for input images or shapes when export onnx file? the config setting as: img_scale = (1920, 1080) , crop_size = (512, 512).

I also tried some other shape size, still confused with this error and any helps would be much appreciated.

We didn't use the 'test_deploy.py' script, so there exists some incompatibility. We just tried to update the script and hope it can solve your problems.

just run:

python tools/deploy_test.py local_configs/topformer/topformer_tiny_512x512_80k_2x8_drive_inviol1k.py results/tiny_80k/tiny_512_512.onnx --backend=onnxruntime --show  --shape 512 512

Note that the 'data_popeline' used during deployment is different from the one used during evaluation. If you have any other questions, feel free to ask under this issue.