* Add models/tf.py for TensorFlow and TFLite export

* Set auto=False for int8 calibration

* Update requirements.txt for TensorFlow and TFLite export

* Read anchors directly from PyTorch weights

* Add --tf-nms to append NMS in TensorFlow SavedModel and GraphDef export

* Remove check_anchor_order, check_file, set_logging from import

* Reformat code and optimize imports

* Autodownload model and check cfg

* update --source path, img-size to 320, single output

* Adjust representative_dataset

* Put representative dataset in tfl_int8 block

* detect.py TF inference

* weights to string

* weights to string

* cleanup tf.py

* Add --dynamic-batch-size

* Add xywh normalization to reduce calibration error

* Update requirements.txt

TensorFlow 2.3.1 -> 2.4.0 to avoid int8 quantization error

* Fix imports

Move C3 from models.experimental to models.common

* Add models/tf.py for TensorFlow and TFLite export

* Set auto=False for int8 calibration

* Update requirements.txt for TensorFlow and TFLite export

* Read anchors directly from PyTorch weights

* Add --tf-nms to append NMS in TensorFlow SavedModel and GraphDef export

* Remove check_anchor_order, check_file, set_logging from import

* Reformat code and optimize imports

* Autodownload model and check cfg

* update --source path, img-size to 320, single output

* Adjust representative_dataset

* detect.py TF inference

* Put representative dataset in tfl_int8 block

* weights to string

* weights to string

* cleanup tf.py

* Add --dynamic-batch-size

* Add xywh normalization to reduce calibration error

* Update requirements.txt

TensorFlow 2.3.1 -> 2.4.0 to avoid int8 quantization error

* Fix imports

Move C3 from models.experimental to models.common

* implement C3() and SiLU()

* Fix reshape dim to support dynamic batching

* Add epsilon argument in tf_BN, which is different between TF and PT

* Set stride to None if not using PyTorch, and do not warmup without PyTorch

* Add list support in check_img_size()

* Add list input support in detect.py

* sys.path.append('./') to run from yolov5/

* Add int8 quantization support for TensorFlow 2.5

* Add get_coco128.sh

* Remove --no-tfl-detect in models/tf.py (Use tf-android-tfl-detect branch for EdgeTPU)

* Update requirements.txt

* Replace torch.load() with attempt_load()

* Update requirements.txt

* Add --tf-raw-resize to set half_pixel_centers=False

* Add --agnostic-nms for TF class-agnostic NMS

* Cleanup after merge

* Cleanup2 after merge

* Cleanup3 after merge

* Add tf.py docstring with credit and usage

* pb saved_model and tflite use only one model in detect.py

* Add use cases in docstring of tf.py

* Remove redundant `stride` definition

* Remove keras direct import

* Fix `check_requirements(('tensorflow>=2.4.1',))`
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Add `SPPF()` layer

* Cleanup

* Add credit

* Implement new headers

* Reformat 1

* Reformat 2

* Reformat 3 - math

* Reformat 4 - yaml

* Merge PIL and OpenCV box plotting functions

* Add ASCII check to plot_one_box

* Cleanup

* Cleanup2

* Remove `encoding='ascii'`

* Reinstate `encoding='ascii'` in emojis()

* Add yolov5s-ghost.yaml

* Finish C3Ghost

* Add C3Ghost to list

* Add C3Ghost to number of repeats if statement

* Fixes

* Cleanup

* no cache option

* no cache option

* bit change

* changed to 0,1 instead of True False

* Update train.py

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

* 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

* Remove redundant try catch

* More refactoring and bug fixes

* retry

* Reformat using pycharm

* respect LOGGERS include list

* Fix

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

* 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

* Remove redundant try catch

* More refactoring and bug fixes

* retry

* Reformat using pycharm

* respect LOGGERS include list

* Initial readme update

* Update README.md

* Update README.md

* Update README.md

* Update README.md

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

Co-authored-by: yangyuantao <yangyuantao@transai.cn>

* more simpler code for DWConvClass

more simpler code for DWConvClass

* remove DWConv function

* Replace DWConvClass with DWConv

remove unnecessary "`"

* Update evolution to CSV format

* Update

* Update

* Update

* Update

* Update

* reset args

* reset args

* reset args

* plot_results() fix

* Cleanup

* Cleanup2

Co-authored-by: fkwong <huangfuqiang@transai.cn>

* 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>

* 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

* Remove redundant try catch

* More refactoring and bug fixes

* retry

* Reformat using pycharm

* respect LOGGERS include list

* call wandblogger.log instead of wandb.log

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

* Add `DWConvClass()`

* Cleanup

* Cleanup2

* Update AP calculation

* Cleanup

* Remove original

* 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

* Remove redundant try catch

* More refactoring and bug fixes

* retry

* Reformat using pycharm

* respect LOGGERS include list

* call wandblogger.log instead of wandb.log
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>

* Update profile()

* Update profile()

* Update profile()

* Update profile()

* Update profile()

* Update profile()

* Update profile()

* Update profile()

* Update profile()

* Update profile()

* Update profile()

* Update profile()

* Cleanup

* 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>