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* Copy wandb param dict before training to avoid overwrites.
Copy the hyperparameter dict retrieved from wandb configuration before passing it to `train()`. Training overwrites parameters in the dictionary (eg scaling obj/box/cls gains), which causes the values reported in wandb to not match the input values. This is confusing as it makes it hard to reproduce a run, and also throws off wandb's Bayesian sweep algorithm.
* Cleanup
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* fix: disable usage of root logger
`logging.basicConfig` configures Python's root logger. This prohibits
fine control of logging, overwrites logging configuration done outside
the package, and is not best practice. Instead, the used logger is now
configured directly, and the root logger is untouched.
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logging, the internal `logging.basicConfig` call overwrites all the
external configuration.
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* precommit: yapf
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# Conflicts:
# utils/plots.py
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* 🎉🆕 now can read Chinese image path.
use "cv2.imdecode(np.fromfile(f, np.uint8), cv2.IMREAD_COLOR)" instead of "cv2.imread(f)" for Chinese image path.
* Update datasets.py
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Stems not working correctly for YOLOv5l with current .rstrip() implementation. After fix:
```
YOLOv5l summary: 468 layers, 46563709 parameters, 46563709 gradients, 109.3 GFLOPs
```
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* log best result in summary
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ValueError: all the input arrays must have same number of dimensions
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* fix pre-commit
1. missing whitespace around operator
2. over-indented
Glenn Jocher
Nick Martin
Max Strobel
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Zengyf-CVer
Jirka Borovec
RcINS
yeshanliu
Philip Gutjahr
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Samuel Yvon
imyhxy
Ayush Chaurasia
or-toledano
toschi23
Jonathan Samelson
Matthias
sitecao
johnk2hawaii
Henry
Chen Gen
Awsaf