* Apple Metal Performance Shader (MPS) device support
Following https://pytorch.org/blog/introducing-accelerated-pytorch-training-on-mac/
Should work with Apple M1 devices with PyTorch nightly installed with command `--device mps`. Usage examples:
```bash
python train.py --device mps
python detect.py --device mps
python val.py --device mps
```
* Update device strategy to fix MPS issue
* Write .yaml file when exporting model to openvino
Write .yaml file automatically when exporting model to openvino to be used during inference
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* Update export.py
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* Add PyTorch AMP check
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* Cleanup
* Cleanup
* Cleanup
* Robust for DDP
* Fixes
* Add amp enabled boolean to check_train_batch_size
* Simplify
* space to prefix
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* Add DWConvTranspose2d() module
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* Add DWConvTranspose2d() module
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* Fix
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* Fix
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* Uses OpenVINO runtime instead of openvino-dev
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* export with openvino package
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* New TensorFlow `TFCrossConv()` module
* Move from experimental to common
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* Add C3x
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* Add to C3x to yolo.py
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* TFC3x bug fix
* TFC3x bug fix
* TFC3x bug fix
* Add TFDWConv g==c1==c2 check
* Add comment
* Update tf.py
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* set common default stride as 32
* restore default stride, and set it on argument optional
* fix wrong use of opt
* fix missing parameter of stride
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* fix format of parameters
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* precommit: yapf
* align isort
* fix
# Conflicts:
# utils/plots.py
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* Update setup.cfg
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* Update wandb_utils.py
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* simplify colorstr
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* val run fix
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* Update hubconf.py
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* PyTorch Hub tuple fix
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* refactor: use edgetpu flag
* fix: remove bitwise and assignation to tflite
* Cleanup and fix tflite
* Cleanup
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* Fix CoreML P6 inference
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* Fix exporting saved_model: pb exceeds 2GB
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* Replace TF v1.x API with TF v2.x API for saved_model export
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* Clean up
* Remove lambda in tf.function()
* Revert "Remove lambda in tf.function()" to be compatible with TF v2.4
This reverts commit 46c7931f11dfdea6ae340c77287c35c30b9e0779.
* Fix for pre-commit.ci
* Cleanup1
* Cleanup2
* Backwards compatibility update
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* Cleanup3
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* Edge TPU `tf.lite.experimental.load_delegate` fix
Fix attempt for #6535
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* import tflite_runtime if tensorflow not installed
* rename tflite to tfli
* Attempt tflite_runtime for all TFLite workflows
Also rename tfli to tfl
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* 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()
* 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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* Check TensorRT>=8.0.0 version
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* Fix tolist() to add the file for each Detection
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* Fix PEP8 requirement for 2 spaces before an inline comment
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* Cleanup
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Glenn Jocher
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DavidB
Raffaele Galliera
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