* Add arguments to TensorFlow NMS call

* Add regex substitution to reorder Identity_*

* Delete reorder in docstring

* Cleanup

* Cleanup2

* Removed `+ \` on string ends (not needed)
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Avoid out-of-image class labels

* Update plots.py

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

* evolve fix

* Enable login timeout

* fix pkg

* check rank

* don't relogin

* fix

* reformat

* evolve fix

* Enable login timeout

* fix pkg

* check rank

* don't relogin

* Annotator `check_font()` RANK -1 remove progress

* Cleanup

* Simplify `check_requirements()` usage

* remove assert, print()

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

* Cleanup

* Refactor argparser printing to `print_args()`

* Cleanup

* evolve fix

* Enable login timeout

* fix pkg

Defines dataset labels *.cache version in a single place, fixing a bug introduced in #4845.

PR should produce datasets sorted alphabetically by filename. Cache version incremented to 0.5. 

Note: will force a one-time re-caching of existing datasets on first-use.

* Unpin Pillow

* Update requirements.txt

* Update plots.py

* Fix val.py study plot

* call plot_val_study

* Rename plot_study_txt to plot_val_study

* Add fused conv support

* Set all saved_model values to non trainable

* Fix TFLite fp16 model export

* Fix int8 TFLite conversion

Follows #4823

* added callbacks

* added back callback to main

* added save_dir to callback output

* merged in upstream

* removed ghost code

* added url check

* Add url2file()

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

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

* Add `--int8` argument

* parents[0] bug fix

* Fix order

Thank you for sharing nice open-source codes 👍

I applied to shuffle the order of all 4(or 9) images in mosaic augmentation

Currently, the order of images in mosaic augmentation is not completely random.
The remaining images except the first are randomly arranged. Apply shuffle all to increase the diversity of data composition.

* Initial commit

* Remove unused export_torchscript return

* ROOT variable

* Add prefix to fcn arg

* fix ROOT

* check_yaml into run()

* interim fixes

* imgsz=(320, 320)

* Hardcode tf_raw_resize False

* Finish opt elimination

* Update representative_dataset_gen()

* Update export.py with TF methods

* SiLU and GraphDef fixes

* file_size() directory handling feature

* export fixes

* add lambda: to representative_dataset

* Detect training False default

* Fuse false for TF models

* Embed agnostic NMS arguments

* Remove lambda

* TensorFlow.js export success

* Add pb to Usage

* Add *_tfjs_model/ to ignore files

* prepend YOLOv5 to function headers

* Remove end --- comments

* parameterize tfjs export pb file

* update run() data default /ROOT

* update --include help

* update imports

* return ct_model

* Consolidate TFLite export

* pb prerequisite to tfjs

* TF modules CamelCase

* Remove exports from tf.py and cleanup

* pass agnostic NMS arguments

* CI

* CI

* ignore *_web_model/

* Add tensorflow to CI dependencies

* CI tensorflow-cpu

* Update requirements.txt

* Remove tensorflow check_requirement

* CI coreml tfjs

* export only onnx torchscript

* reorder exports torchscript first

* Writeable test

* Fix

* Cleanup

* Fix `is_writeable()` for 3 OS support

* Update general.py

* add callbacks to train function in wandb sweep

Fix following https://github.com/ultralytics/yolov5/pull/4688 which modified the function signature to `train`

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

* Improved detect.py timing

* Eliminate 1 time_sync() call

* Inference-only time

* dash

* #Save section

* Cleanup

@KalenMike