* log best.pt metrics at train end

* update

* Update __init__.py

* flush callbacks when using evolve

* remember batch size on resuming

* Update train.py

* improve stability of resume

Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Fix missing data folder when running log_dataset

* Use ROOT/'data'

* PEP8 whitespace

* Fix `hyp_evolve.yaml` indexing bug

Bug caused hyp_evolve.yaml to display latest generation result rather than best generation result.

* Update plots.py

* Update general.py

* Update general.py

* Update general.py

* Fix `plot_labels()` colored histogram bug

* Cleanup

* Move trainloader functions to class methods

* results = ThreadPool(NUM_THREADS).imap(self.load_image, range(n))

* Cleanup

* F541

* F821

* F841

* E741

* E302

* E722

* Apply suggestions from code review

* Update general.py

* Update datasets.py

* Update export.py

* Update plots.py

* Update plots.py

Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Fix2 select_device() for Multi-GPU

* Cleanup

* Cleanup

* Simplify error message

* Improve assert

* Update torch_utils.py

* Verbose updates

* Verbose updates

* Gave a more explicit name to the logger

* Cleanup

Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Add detect.py GIF video inference

* Cleanup

* New flag 'stop_training' in util.callbacks.Callbacks class to prematurely stop training from callback handler

* Removed most of the new  checks, leaving only the one after calling 'on_train_batch_end'

* Cleanup

Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* log best.pt metrics at train end

* update

* Update __init__.py

* flush callbacks when using evolve

Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

New environment variable `VERBOSE`

* Console corrupted -> corrupt 

Minor style changes.

* Update export.py

* `select_device()` cleanup

* Update torch_utils.py

* Update torch_utils.py

* Update torch_utils.py

* Update torch_utils.py

* Update torch_utils.py

* Fix device count check()

* Update torch_utils.py

* Update torch_utils.py

* Update hubconf.py

* Add `is_kaggle()` function

Return True if environment is Kaggle Notebook.

* Remove root loggers only if is_kaggle() == True

* Update general.py

* Refactor the code to reduece else

* Update metrics.py

* Cleanup

Co-authored-by: Cmos <gen.chen@ubisoft.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* log best result in summary

* comment added

* add space for `flake8`

* log `best/epoch`

* fix `dimension` for epoch

ValueError: all the input arrays must have same number of dimensions

* log `best/` in `utils.logger.__init__`

* fix pre-commit

1. missing whitespace around operator
2.  over-indented

* log best.pt metrics at train end

* update

* Update __init__.py

Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* track batch size after autobatch

* remove redundant import

* Update __init__.py

* Update __init__.py

Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

Consider that the default value is CIOU，adjust the order of judgment could reduce the number of judgments.
And “elif CIoU:” didn't need 'if'.

Co-authored-by: 李杰 <360751194@qq.comqq.com>

* Making `ar_thr` available as a hyperparameter

* Disabling ar_thr as hyperparameter and computing from the dataset instead

* Fixing bug in ar_thr computation

* Fix `ar_thr` to 100

Add __init__() function.

Replace 'training_result' with 'best_fitness' in strip_optimizer() to match key with ckpt from train.py