* Import Annotator class from `ultralytics` package
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* Import Annotator class from `ultralytics` package
* Update requirements.txt
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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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* Security improvements
* Security improvements
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* Update streams.txt default
Signed-off-by: Colin Wong <cwongmath@gmail.com>
* Change streams list extension to .streams
* Read txt as media per line
* Missed one
* Missed another one
* Update dataloaders.py
* Update detect.py
* Update dataloaders.py
* Update detect.py
* Update predict.py
* Update predict.py
* Update README.md
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* process_mask_native() cleanup
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* fix plot&&speed up
* fix segment save-txt
* fix channel
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* AutoCache
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* Add segment line predictions
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* update coco128-seg comments
* Enables detect.py to use Triton for inference
Triton Inference Server is an open source inference serving software
that streamlines AI inferencing.
https://github.com/triton-inference-server/server
The user can now provide a "--triton-url" argument to detect.py to use
a local or remote Triton server for inference.
For e.g., http://localhost:8000 will use http over port 8000
and grpc://localhost:8001 will use grpc over port 8001.
Note, it is not necessary to specify a weights file to use Triton.
A Triton container can be created by first exporting the Yolov5 model
to a Triton supported runtime. Onnx, Torchscript, TensorRT are
supported by both Triton and the export.py script.
The exported model can then be containerized via the OctoML CLI.
See https://github.com/octoml/octo-cli#getting-started for a guide.
* added triton client to requirements
* fixed support for TFSavedModels in Triton
* reverted change
* Test CoreML update
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
* Use pathlib
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
* Refacto DetectMultiBackend to directly accept triton url as --weights http://...
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
* Deploy category
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
* Update common.py
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
* Update common.py
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
* Update predict.py
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* Update predict.py
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
* Update predict.py
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
* Update triton.py
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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* triton fixes
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* fixed triton model query over grpc
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* group imports
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* Fix likely remote URL bug
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Glenn Jocher
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