* Update tutorial.ipynb
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* FROM nvcr.io/nvidia/pytorch:22.04-py3
* Update Docker
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* Update Docker
* Update TRT auto-install
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* Cleanup
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* Cleanup cpu
* Cleanup cpu
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* PyTorch Hub `_verbose=False` fix2
* Update downloads.py
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* Update hubconf.py
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* Update restapi.py
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* Update restapi.py
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* Update restapi.py
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* Add redundant weights download mirrors
This PR seeks to improve access worldwide to YOLOv5 weights. Universal access to AI for all is our core value, and we are against any censorship or restriction efforts.
I've uploaded the official YOLOv5 v6.1 weights to a primary backup bucket on GCP and to secondary backup on Google Drive at https://drive.google.com/drive/folders/1EFQTEUeXWSFww0luse2jB9M1QNZQGwNl. Autodownload with try the first two locations (GitHuB release assets and GCP bucket), and point users to the Google Drive folder if the first two fail.
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* Autoinstall TensorRT if missing
May resolve https://github.com/ultralytics/yolov5/issues/7464
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* Update export.py
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* Update `git_describe()`
Add .git path check to avoid `fatal: not a git repository (or any of the parent directories): .git` printout
* Update general.py
* Print dataset scan only `if RANK in (-1, 0)`
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* Simplify callbacks.py return
* Indent args (pytorch convention)
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* Update export.py
Simplify code.
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* Update
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Resolve `UserWarning: Usage of dash-separated 'description-file' will not be supported in future versions. Please use the underscore name 'description_file' instead`
* yolo.py profiling updates
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* Sidestep os.path.relpath() Windows bug
os.path.relpath() seems to have a major bug on Windows due to Windows horrible path handling. This fix attempts to sidestep the issue.
```
File "C:\Users\mkokg/.cache\torch\hub\ultralytics_yolov5_master\export.py", line 64, in
ROOT = Path(os.path.relpath(ROOT, Path.cwd())) # relative
File "C:\Users\mkokg\AppData\Local\Programs\Python\Python310\lib\ntpath.py", line 718, in relpath
raise ValueError("path is on mount %r, start on mount %r" % (
ValueError: path is on mount 'C:', start on mount 'D:'
```
* Update yolo.py
* Update yolo.py
* Update yolo.py
* Update export.py
Stems not working correctly for YOLOv5l with current .rstrip() implementation. After fix:
```
YOLOv5l summary: 468 layers, 46563709 parameters, 46563709 gradients, 109.3 GFLOPs
```
* Update loss.py
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* Update loss.py
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