* Add option to quantize per-tensor
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* Limit tensorflow version and add checks
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* Moving check in export script
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* Update export.py
Signed-off-by: Luis Filipe Araujo de Souza <58831491+Doquey@users.noreply.github.com>
* Update export.py
Signed-off-by: Luis Filipe Araujo de Souza <58831491+Doquey@users.noreply.github.com>
* Update export.py
Transformed the f variable into a string on the export onnx. This bug was making it impossible to export any models in .onnx, since it was making the typehint not accept the users input as it is specified in the functions documentation
Signed-off-by: Luis Filipe Araujo de Souza <58831491+Doquey@users.noreply.github.com>
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* Add NMS to CoreML exports
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* Update LICENSE to AGPL-3.0
This pull request updates the license of the YOLOv5 project from GNU General Public License v3.0 (GPL-3.0) to GNU Affero General Public License v3.0 (AGPL-3.0).
We at Ultralytics have decided to make this change in order to better protect our intellectual property and ensure that any modifications made to the YOLOv5 source code will be shared back with the community when used over a network.
AGPL-3.0 is very similar to GPL-3.0, but with an additional clause to address the use of software over a network. This change ensures that if someone modifies YOLOv5 and provides it as a service over a network (e.g., through a web application or API), they must also make the source code of their modified version available to users of the service.
This update includes the following changes:
- Replace the `LICENSE` file with the AGPL-3.0 license text
- Update the license reference in the `README.md` file
- Update the license headers in source code files
We believe that this change will promote a more collaborative environment and help drive further innovation within the YOLOv5 community.
Please review the changes and let us know if you have any questions or concerns.
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
* Update headers to AGPL-3.0
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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
* Allow int8 quantization for export_tfjs
--int8 param currently has no effect on export_tfjs. With this change,
` python export.py --weights ../path/to/best.pt --include tfjs --int8` will add the --quantize_uint8 param to the tensorflowjs_converter script, greatly reducing model size for web usage.
Signed-off-by: David Strahm <david.strahm@lambda-it.ch>
* Update Dockerfile
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Signed-off-by: David Strahm <david.strahm@lambda-it.ch>
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Update parse_opt() to work as in train.py
Change parse_opt() be able to use parse_known_args(), same as in train.py, so export.main() can be called from other script without error.
e.g.:
from yolov5 import export
opt = export.parse_opt(True)
opt.weights = <model_path>
opt.include = ("torchscript", "onnx")
opt.data = <data>
opt.imgsz = [<height>, <width>]
export.main(opt)
Signed-off-by: Johan Bergman <35481994+duran67@users.noreply.github.com>
Signed-off-by: Johan Bergman <35481994+duran67@users.noreply.github.com>
* added embedded meta data to tflite models
* added try block for inference
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* refactored tfite meta data into separate function
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* Creat tmp file in /tmp
* Update export.py
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* Update export.py
* Update export.py
* Update export.py
* Update export.py
* Update common.py
* Update export.py
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* Update common.py
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* import re
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* TensorFlow macOS AutoUpdate
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* Standardize warnings
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* Remove `.train()` mode exports
No common use cases.
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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* 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
* rename to @try_export
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