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* FROM nvcr.io/nvidia/pytorch:22.04-py3
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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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* support nomedia
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* Added a way to skip dependency auto-installation.
Setting the environment variable `YOLOv5_AUTOINSTALL=False` will
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`install=False` to `check_requirements`.
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* Print dataset scan only `if RANK in (-1, 0)`
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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.
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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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external configuration.
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Glenn Jocher
Yonghye Kwon
Cristi Fati
SylvanDing
Ayush Chaurasia
Powercube7
Zengyf-CVer
Joseph Kocherhans
Nick Martin
Max Strobel
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