New environment variable `VERBOSE`

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* `export.py` return exported files/dirs

* Path to str

* TensorRT `assert im.device.type != 'cpu'` on export

* Update export.py

* Console corrupted -> corrupt 

Minor style changes.

* Update export.py

* Remove `dataset_stats()` autodownload capability

@kalenmike security update per Slack convo

* Update datasets.py

* Fix `train.py` parameter groups desc error

* Cleanup
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* `select_device()` cleanup

* Update torch_utils.py

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* Fixing bug multi-gpu training

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* Update torch_utils.py for pep8

* Fix device count check()

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* Update hubconf.py

* Add `is_kaggle()` function

Return True if environment is Kaggle Notebook.

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

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* TFLite `--int8` 'flatbuffers==1.12' fix 2

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* TFLite `--int8` 'flatbuffers==1.12' fix

Temporary workaround for TFLite INT8 export.

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* Edge TPU compiler comment

* 7 to 8 fix

Fix for Webcam stop working suddenly (Issue #6197)

* Add Apple CoreML inference

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* fix export of TorchScript on mobile

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* Global export sort

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updates:
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- [github.com/PyCQA/isort: 5.9.3 → 5.10.1](https://github.com/PyCQA/isort/compare/5.9.3...5.10.1)
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* 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()

* Add TensorFlow and TFLite Detection

* Add --tfl-detect for TFLite Detection

* Add int8 quantized TFLite inference in detect.py

* Add --edgetpu for Edge TPU detection

* Fix --img-size to add rectangle TensorFlow and TFLite input

* Add --no-tf-nms to detect objects using models combined with TensorFlow NMS

* Fix --img-size list type input

* Update README.md

* Add Android project for TFLite inference

* Upgrade TensorFlow v2.3.1 -> v2.4.0

* Disable normalization of xywh

* Rewrite names init in detect.py

* Change input resolution 640 -> 320 on Android

* Disable NNAPI

* Update README.me --img 640 -> 320

* Update README.me for Edge TPU

* Update README.md

* Fix reshape dim to support dynamic batching

* 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

* Remove android directory

* Update README.md

* Update README.md

* Add multiple OS support for EdgeTPU detection

* Fix export and detect

* Export 3 YOLO heads with Edge TPU models

* Remove xywh denormalization with Edge TPU models in detect.py

* Fix saved_model and pb detect error

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* Fix pre-commit.ci failure

* Add edgetpu in export.py docstring

* Fix Edge TPU model detection exported by TF 2.7

* Add class names for TF/TFLite in DetectMultibackend

* Fix assignment with nl in TFLite Detection

* Add check when getting Edge TPU compiler version

* Add UTF-8 encoding in opening --data file for Windows

* Remove redundant TensorFlow import

* Add Edge TPU in export.py's docstring

* Add the detect layer in Edge TPU model conversion

* Default `dnn=False`

* Cleanup data.yaml loading

* Update detect.py

* Update val.py

* Comments and generalize data.yaml names
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