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46ea120
1
Parent(s):
fa17459
added object detection imporved
Browse files- .gitignore +0 -19
- tool_utils/yolo_world.py +4 -4
.gitignore
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@@ -100,19 +100,6 @@ ipython_config.py
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# install all needed dependencies.
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#Pipfile.lock
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# poetry
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# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
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# This is especially recommended for binary packages to ensure reproducibility, and is more
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# commonly ignored for libraries.
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# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
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#poetry.lock
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# pdm
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# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
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#pdm.lock
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# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
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# in version control.
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# https://pdm.fming.dev/latest/usage/project/#working-with-version-control
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.pdm.toml
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.pdm-python
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.pdm-build/
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# Cython debug symbols
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cython_debug/
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# PyCharm
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# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
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# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
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# and can be added to the global gitignore or merged into this file. For a more nuclear
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# option (not recommended) you can uncomment the following to ignore the entire idea folder.
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#.idea/
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*.json
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image_store/
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# install all needed dependencies.
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#Pipfile.lock
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.pdm.toml
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.pdm-python
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.pdm-build/
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# Cython debug symbols
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cython_debug/
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*.json
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image_store/
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tool_utils/yolo_world.py
CHANGED
@@ -85,8 +85,8 @@ class YoloWorld:
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cv2.imwrite('final_mask.png', cv2.cvtColor(detected_image,cv2.COLOR_BGR2RGB))
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return "Predicted image : final_mask.jpg . Details :{}".format(processed_predictions[0])
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if __name__ == "__main__":
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cv2.imwrite('final_mask.png', cv2.cvtColor(detected_image,cv2.COLOR_BGR2RGB))
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return "Predicted image : final_mask.jpg . Details :{}".format(processed_predictions[0])
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# if __name__ == "__main__":
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# yolo = YoloWorld()
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# predicted_data = yolo.run_yolo_infer('../image_store/demo2.jpg',['person','hat','building'])
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# print(predicted_data)
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