* WORLD_SIZE-safe workers

* Update with DDP comment

* Fix float zeros format

* 255 to integer

* Update `set_logging()`

* Update export.py

* pre-commit fixes

* Update LoadImages

* Update LoadStreams

* Update print_args

* Single LOGGER definition

* yolo.py fix

Co-authored-by: pre-commit <pre-commit@example.com>

* Autobatch

* fix mem

* fix mem2

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update train.py

* print result

* Cleanup print result

* swap fix in call

* to 64

* use total

* fix

* fix

* fix

* fix

* fix

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Cleanup printing

* Update final printout

* Update autobatch.py

* Update autobatch.py

* Update autobatch.py

* Add `on_fit_epoch_end` callback

* Add results to train

* Update __init__.py

* use os.path.relpath instead of relative_to

* use os.path.relpath instead of relative_to

* Remove os.path from val.py

* Remove os.path from train.py

* Update detect.py import to os

* Update export.py import to os

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

Co-authored-by: qiningonline <qiningonline@gmail.com>

This PR adds a new training argument `--save-period` to save training checkpoints every `x` epochs. To save training every 50 epochs for example:
```
python train.py --save-period 50  # saves epoch50.pt, epoch100.pt, epoch150.pt, ... etc.
```

This saved checkpoints in addition to existing last.pt and best.pt checkpoints and does not affect their behavior. Default value is -1, i.e. disabled.

* Fix E722, do not use bare 'except'

* Remove used codes

* Add FileNotFoundError in LoadImagesAndLabels

* Remove AssertionError

* Ignore LoadImagesAndLabels

* Ignore downloads.py

* Ignore torch_utils.py

* Ignore train.py

* Ignore datasets.py

* Enable utils/download.py

* Fixing exception in thop

* Remove unused code

* Fixing exception in LoadImagesAndLabels

* Fixing exception in exif_size

* Fixing exception in parse_model

* Ignore exceptions in requests

* Revert the exception as suggested

* Revert the exception as suggested

* Allow YOLOv5 execution from arbitrary `cwd`

* Fix str bugs

* Validate best.pt on train end

* 0.7 iou for COCO only

* pass callbacks

* active model.float() if not half

* print Validating best.pt...

* add newline

* Simplify `check_requirements()` usage

* remove assert, print()

* Update `sys.path.append(str(ROOT))`

* Cleanup

* Refactor argparser printing to `print_args()`

* Cleanup

Also disable `/weights` dir creation when evolving as no weights are saved and empty folder causes user expectations of weights.

* Add suffix checks

* Cleanup

* Cleanup2

* Cleanup3

* added callbacks

* added back callback to main

* added save_dir to callback output

* reduced code count

* updated callbacks

* added default callback class to main, added missing parameters to on_model_save

* Glenn updates

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

* Fixed 'meta' and 'hyp' may out of order when using evolve

* Update gitignore

* Remove assert

* debug0

* trace=not opt.sync

* sync to sync_bn fix

* Cleanup

* Add Annotator() class

* Download Arial

* 2x for loop

* Cleanup

* tuple 2 list

* max_size=1920

* bold logging results to

* tolist()

* im = annotator.im

* PIL save in detect.py

* Smart asarray in detect.py

* revert to cv2.imwrite

* Cleanup

* Return result asarray

* Add `Profile()` profiler

* CamelCase Timeout

* Resize after mosaic

* pillow>=8.0.0

* daemon imwrite

* Add cv2 support

* Remove plot_wh_methods and plot_one_box

* pil=False for hubconf.py annotations

* im.shape bug fix

* colorstr common.py

* join daemons

* Update t.daemon

* Removed daemon saving

* Initial commit

* Update

* Add EarlyStopping feature

* Add comment

* Cleanup

* Cleanup2

* debug

* debug2

* debug3

* debug3

* debug4

* debug5

* debug6

* debug7

* debug8

* debug9

* debug10

* debug11

* debug12

* Cleanup

* Add TODO for known DDP issue

* Implement new headers

* Reformat 1

* Reformat 2

* Reformat 3 - math

* Reformat 4 - yaml

* Update evolution to CSV format

* Update

* Update

* Update

* Update

* Update

* reset args

* reset args

* reset args

* plot_results() fix

* Cleanup

* Cleanup2

* Add cache-on-disk and cache-directory to cache images on disk

* Fix load_image with cache_on_disk

* Add no_cache flag for load_image

* Revert the parts('logging' and a new line) that do not need to be modified

* Add the assertion for shapes of cached images

* Add a suffix string for cached images

* Fix boundary-error of letterbox for load_mosaic

* Add prefix as cache-key of cache-on-disk

* Update cache-function on disk

* Add psutil in requirements.txt

* Update train.py

* Cleanup1

* Cleanup2

* Skip existing npy

* Include re-space

* Export return character fix

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

* added callbacks

* Update callbacks.py

* Update train.py

* Update val.py

* Fix CamlCase add staticmethod

* Refactor logger into callbacks

* Cleanup

* New callback on_val_image_end()

* Add curves and results images to TensorBoard

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

* Add freeze as an argument

I train on different platforms and sometimes I want to freeze some layers. I have to go into the code and change it and also keep track of how many layers I froze on what platform. Please add the number of layers to freeze as an argument in future versions thanks.

* Update train.py

* Update train.py

* Cleanup

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

* PyCharm reformat

* YAML reformat

* Markdown reformat

* Improve docstrings and run names

* default wandb login prompt with timeout

* return key

* Update api_key check logic

* Properly support zipped dataset feature

* update docstring

* Revert tuorial change

* extend changes to log_dataset

* add run name

* bug fix

* bug fix

* Update comment

* fix import check

* remove unused import

* Hardcore .yaml file extension

* reduce code

* Reformat using pycharm

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