-
Notifications
You must be signed in to change notification settings - Fork 64
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
UNET + YOLOv6 #11
Comments
The error is raised in your x = self.detect(x)
...
return self.act(self.bn(self.conv(x))) which gets an input activation with |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
I am trying to add Unet as a preprocessing layer before the YOLOv6 architecture and when I am trying to do this, I am facing the following error. And how do I combine a Unet architecture with YOLO architecture. Any help from you here will be appreciated.
Looking forward to your support as soon as possible. Thank you
ERROR in training steps.
ERROR in training loop or eval/save model.
Training completed in 0.000 hours.
Traceback (most recent call last):
File "tools/train.py", line 112, in
main(args)
File "tools/train.py", line 102, in main
trainer.train()
File "/workspace/YOLOv61/yolov6/core/engine.py", line 75, in train
self.train_in_loop()
File "/workspace/YOLOv61/yolov6/core/engine.py", line 88, in train_in_loop
self.train_in_steps()
File "/workspace/YOLOv61/yolov6/core/engine.py", line 104, in train_in_steps
preds = self.model(images)
File "/home/ubuntu/anaconda3/envs/pytorch_p38/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "/workspace/YOLOv61/yolov6/models/yolo.py", line 39, in forward
x = self.detect(x)
File "/home/ubuntu/anaconda3/envs/pytorch_p38/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "/workspace/YOLOv61/yolov6/models/effidehead.py", line 60, in forward
x[i] = self.stemsi
File "/home/ubuntu/anaconda3/envs/pytorch_p38/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "/workspace/YOLOv61/yolov6/layers/common.py", line 102, in forward
return self.act(self.bn(self.conv(x)))
File "/home/ubuntu/anaconda3/envs/pytorch_p38/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "/home/ubuntu/anaconda3/envs/pytorch_p38/lib/python3.8/site-packages/torch/nn/modules/conv.py", line 446, in forward
return self._conv_forward(input, self.weight, self.bias)
File "/home/ubuntu/anaconda3/envs/pytorch_p38/lib/python3.8/site-packages/torch/nn/modules/conv.py", line 442, in _conv_forward
return F.conv2d(input, weight, bias, self.stride,
RuntimeError: Given groups=1, weight of size [256, 256, 1, 1], expected input[8, 128, 20, 20] to have 256 channels, but got 128 channels instead
The text was updated successfully, but these errors were encountered: