-
Notifications
You must be signed in to change notification settings - Fork 27
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
Many errors a noob can't solve ^^ #66
Comments
your graphics card does not have enough video memory for what the program is trying to use. I think you can lower the inference size and that should help, or maybe the batch size is too large Which settings are you using? |
hm, yeah maybe try lowering the batch size, it inherently multiplies the needed vram amount, since it does 16 times as much at the same time |
No change, i even lowered it to 1, same error. Here you can find the error i get when i change it to 360p: |
Sorry, I can't really make sense of this to be honest. @joshinils is correct, a large batch size very quickly depletes your RAM and VRAM, but at 1 this really shouldn't be an issue. |
Hey, da ich nun mitbekommen habe dass ihr deutsche seid, so weiter :-D Besteht keine Möglichkeit irgendwie eine Anleitung zu bekommen für Otto-Normal-Verbraucher? :-D Die Arbeit die ihr macht Danke trotzdem! |
Mit der neusten Version sollte es gehen, zumindest bei mir funktioniert es wieder. |
Hey, first, i have no clue in programming. I just found a video with a tutorial how to install DCC.
The GUI is loading now and my first try ended in the "TypeError: unsupported operand type(s) for /: 'tuple' and 'int'" error.
As you mentioned in the other issue, i deleted the ".cache/torch" folder. But now i receive the following error:
Blurrer started!
Traceback (most recent call last):
File "D:\Dashcam Shit\DashcamCleaner\dashcamcleaner\src\qt_wrapper.py", line 74, in run
new_detections = self.detect_identifiable_information(frame_buffer)
File "D:\Dashcam Shit\DashcamCleaner\dashcamcleaner\src\blurrer.py", line 39, in detect_identifiable_information
results_list = self.detector(images, size=(scale,)).xyxy
File "D:\Dashcam Shit\Anaconda\envs\py38\lib\site-packages\torch\nn\modules\module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "D:\Dashcam Shit\Anaconda\envs\py38\lib\site-packages\torch\autograd\grad_mode.py", line 27, in decorate_context
return func(*args, **kwargs)
File "C:\Users\spams/.cache\torch\hub\ultralytics_yolov5_master\models\common.py", line 704, in forward
y = self.model(x, augment=augment) # forward
File "D:\Dashcam Shit\Anaconda\envs\py38\lib\site-packages\torch\nn\modules\module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "C:\Users\spams/.cache\torch\hub\ultralytics_yolov5_master\models\common.py", line 514, in forward
y = self.model(im, augment=augment, visualize=visualize) if augment or visualize else self.model(im)
File "D:\Dashcam Shit\Anaconda\envs\py38\lib\site-packages\torch\nn\modules\module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "C:\Users\spams/.cache\torch\hub\ultralytics_yolov5_master\models\yolo.py", line 209, in forward
return self._forward_once(x, profile, visualize) # single-scale inference, train
File "C:\Users\spams/.cache\torch\hub\ultralytics_yolov5_master\models\yolo.py", line 121, in _forward_once
x = m(x) # run
File "D:\Dashcam Shit\Anaconda\envs\py38\lib\site-packages\torch\nn\modules\module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "C:\Users\spams/.cache\torch\hub\ultralytics_yolov5_master\models\common.py", line 167, in forward
return self.cv3(torch.cat((self.m(self.cv1(x)), self.cv2(x)), 1))
File "D:\Dashcam Shit\Anaconda\envs\py38\lib\site-packages\torch\nn\modules\module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "C:\Users\spams/.cache\torch\hub\ultralytics_yolov5_master\models\common.py", line 59, in forward_fuse
return self.act(self.conv(x))
File "D:\Dashcam Shit\Anaconda\envs\py38\lib\site-packages\torch\nn\modules\module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "D:\Dashcam Shit\Anaconda\envs\py38\lib\site-packages\torch\nn\modules\conv.py", line 399, in forward
return self._conv_forward(input, self.weight, self.bias)
File "D:\Dashcam Shit\Anaconda\envs\py38\lib\site-packages\torch\nn\modules\conv.py", line 395, in _conv_forward
return F.conv2d(input, weight, bias, self.stride,
RuntimeError: CUDA out of memory. Tried to allocate 10.58 GiB (GPU 0; 24.00 GiB total capacity; 1.76 GiB already allocated; 19.60 GiB free; 1.96 GiB reserved in total by PyTorch)
And i have really no idea XD
Hope you can help. Thank you!
The text was updated successfully, but these errors were encountered: