Follows https://github.com/ultralytics/yolov5/pull/7488. Correct bug where fonts were downloading to current working directory rather than global CONFIG_DIR

* Improved non-latin labels Annotator plotting

May resolve https://github.com/ultralytics/yolov5/issues/7460

* Update train.py

* Update train.py

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* add progress arg

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* Update val.py

is_coco doesn't work!! '/' -> os.sep!!

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* Cleanup

* fix

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Bumps [cirrus-actions/rebase](https://github.com/cirrus-actions/rebase) from 1.5 to 1.6.
- [Release notes](https://github.com/cirrus-actions/rebase/releases)
- [Commits](https://github.com/cirrus-actions/rebase/compare/1.5...1.6)

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* add fp16 for coreml using --half

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* fix

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* Update export.py

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* add version warning

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* Cleanup

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* Update __init__.py

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* Dynamic normalization layer selection

Based on actual available layers. Torch 1.7 compatible, resolves https://github.com/ultralytics/yolov5/issues/7381

* Update train.py

* Add support for different normalization layers.

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* Cleanup

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* Update optimizer param group strategy

Avoid empty lists on missing BathNorm2d models as in https://github.com/ultralytics/yolov5/issues/7375

* fix init

Bumps [actions/stale](https://github.com/actions/stale) from 4 to 5.
- [Release notes](https://github.com/actions/stale/releases)
- [Changelog](https://github.com/actions/stale/blob/main/CHANGELOG.md)
- [Commits](https://github.com/actions/stale/compare/v4...v5)

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Deleting as redundant with FUNDING.yml present in organization repo at https://github.com/ultralytics/.github

* set common default stride as 32

* restore default stride, and set it on argument optional

* fix wrong use of opt

* fix missing parameter of stride

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* fix format of parameters

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* Update common.py

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* 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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* 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.

Example:
    If yolov5 is used as part of another project with some sophisticated
    logging, the internal `logging.basicConfig` call overwrites all the
    external configuration.

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* Update general.py

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* Comment kaggle

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Improved error messages for understanding of user error with val.py. May help https://github.com/ultralytics/yolov5/issues/7291

* enable TensorFlow ops if flag --nms or --agnostic-nms is used

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