* Update `check_requirements(args, cmds='')`
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* New export decorator
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* New export decorator
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* Cleanup
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* rename fcn to func
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* export.py replace `check_file` -> `check_yaml`
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* Add check_file(data) i.e. `--data coco128.yaml`
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* Dynamic batch size support for TensorRT
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* Fix optimization profile when batch size is 1
* Warn users if they use batch-size=1 with dynamic
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* More descriptive assertion error
* Fix syntax
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* pre-commit formatting sucked
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* Update export.py
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* Add `--hard-fail` list argument to benchmarks for CI
Will cause CI to fail on a benchmark failure for given indices.
* Update ci-testing.yml
* Attempt Failure (CI should fail)
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* Update ci-testing.yml
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* 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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* Load metadata on inference
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* Removed shell=True from subprocess commands that require user inputs. Also removed unused arguments
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* Added check=True
* Revert line add
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* FROM nvcr.io/nvidia/pytorch:22.04-py3
* Update Docker
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* Update TRT auto-install
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* Cleanup
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* disallow dynamic arg when half is given
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* Autoinstall TensorRT if missing
May resolve https://github.com/ultralytics/yolov5/issues/7464
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* Update export.py
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* add fp16 for coreml using --half
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* fix
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* Update export.py
Simplify code.
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* enable TensorFlow ops if flag --nms or --agnostic-nms is used
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* Update export.py
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* Update
* Update
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Katteria
Glenn Jocher
Colin Wong
daquexian
Sahil Chachra
xylieong
Jaewon Lee
David Matos
Duncan Moss
Cedric Perauer
leeflix