* Allow specifying multi_label option for NMS when using torch hub

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

* adding get cropped functionality

* Add target logic in existing functions

* Crops cleanup

* Add dictionary keys: conf, cls, box

* Bug fixes - avoid return after first image
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Add `user_config_dir`

* Linux to .config

* Update `check_yaml()` comment

* Cleanup

Fix a bug when `file=''`

* 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

Fix 3 for Arial.ttf redownloads with hub inference, follow-on to #4628.

* Remove assert

* debug0

* trace=not opt.sync

* sync to sync_bn fix

* Cleanup

* Close plots

* Replace fig.close() for plt.close()

Layer 21 includes the information of xsmall objects

* Auto-download Arial.ttf on init

* Fix ROOT

* 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

* Add `Profile()` profiler

* CamelCase Timeout

* 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

This PR brings alignment in AP computation practices with Detectron2 and MMDetection. 

Problem first noted by @yusiyoh in https://github.com/ultralytics/yolov5/issues/4546

Auto-fix corrupt JPEGs PR introduced a bug whereby the f.seek() operation read all of the bytes in the image, resulting in the PIL image having nothing to read upon the .save() operation. 

Fix was to re-open the image using PIL before saving.

* Autofix corrupt JPEGs

This PR automatically re-saves corrupt JPEGs and trains with the resaved images. WARNING: this will overwrite the existing corrupt JPEGs in a dataset and replace them with correct JPEGs, though the filesize may increase and the image contents may not be exactly the same due to lossy JPEG compression schemes. Results may vary by JPEG decoder and hardware.

Current behavior is to exclude corrupt JPEGs from training with a warning to the user, but many users have been complaining about large parts of their dataset being excluded from training.

* Clarify re-save reason

Profiling fix copies input to Detect layer to circumvent inplace changes to the feature maps.

* Auto TFLite uint8 detection

This PR automatically determines if TFLite models are uint8 quantized rather than accepting a manual argument.

The quantization determination is based on @zldrobit comment https://github.com/ultralytics/yolov5/pull/1127#issuecomment-901713847

* Cleanup

* Add `install=True` argument to `check_requirements`

* Update general.py