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Arjun #13556

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@arjunramdascs arjunramdascs commented Apr 1, 2025

updated detect.py

πŸ› οΈ PR Summary

Made with ❀️ by Ultralytics Actions

🌟 Summary

This PR introduces MQTT integration and a sliding window mechanism for object detection focus tracking in YOLOv5, enhancing real-time applications and communication capabilities.

πŸ“Š Key Changes

  • MQTT Integration: Added support for publishing detection results to an MQTT broker for real-time communication.
  • Sliding Window Focus Tracking: Implemented a buffer-based mechanism to track the most consistently detected object in the center of the frame over multiple frames.
  • Dependency Update: Added paho-mqtt to requirements.txt for MQTT functionality.
  • Minor Updates: Adjusted .gitignore and pyproject.toml for better project organization.

🎯 Purpose & Impact

  • Enhanced Real-Time Communication: The MQTT integration allows seamless sharing of detection results with IoT systems or other applications. πŸ“‘
  • Improved Detection Stability: The sliding window mechanism ensures more reliable identification of the user's focus object, reducing noise in dynamic environments. 🎯
  • Broader Use Cases: These updates make YOLOv5 more suitable for automation, robotics, and smart surveillance systems. πŸ€–
  • Ease of Integration: Developers can now leverage MQTT for efficient data transmission without additional setup. πŸš€

arjunramdascs and others added 3 commits March 31, 2025 17:38
need to implement filtering candidate objects, and the concept to be used is minimum euclidean distance between centroid of image frame and centroid of bounding box of objects.

Signed-off-by: arjunramdascs <151497622+arjunramdascs@users.noreply.github.com>
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github-actions bot commented Apr 1, 2025


Thank you for your submission, we really appreciate it. Like many open-source projects, we ask that you all sign our Contributor License Agreement before we can accept your contribution. You can sign the CLA by just posting a Pull Request Comment same as the below format.


I have read the CLA Document and I sign the CLA


1 out of 2 committers have signed the CLA.
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You can retrigger this bot by commenting recheck in this Pull Request. Posted by the CLA Assistant Lite bot.

@UltralyticsAssistant UltralyticsAssistant added dependencies Dependencies and packages detect Object Detection issues, PR's enhancement New feature or request labels Apr 1, 2025
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πŸ‘‹ Hello @arjunramdascs, thank you for submitting a PR to the ultralytics/yolov5 πŸš€ repository! Your contributions are greatly appreciated. To ensure your enhancements are smoothly integrated, please review the checklist below:

  • βœ… Define a Purpose: Your PR description provides a good overview. However, ensure that it fully explains the purpose of the update, referencing any relevant issues or discussions.
  • βœ… Synchronize with Source: Confirm your PR is up-to-date with the main branch of ultralytics/yolov5. If it's behind, use the 'Update branch' button or run git pull and git merge main locally.
  • βœ… Ensure CI Checks Pass: Verify that all Ultralytics Continuous Integration (CI) checks pass. Address any failed checks if necessary.
  • βœ… Update Documentation: If applicable, update the documentation to reflect your changes, especially for new functionality like MQTT and sliding window mechanisms.
  • βœ… Add Tests: Include or update tests to validate your additions, ensuring all tests pass successfully.
  • βœ… Sign the CLA: If this is your first contribution to Ultralytics, please sign our Contributor License Agreement (CLA) by commenting "I have read the CLA Document and I sign the CLA."
  • βœ… Minimize Changes: Ensure your PR includes only the necessary changes to achieve the stated objectives. For example, avoid unrelated modifications to files unless absolutely required.

For more details on contributing, check our Contributing Guide. If you encounter any issues or have questions, feel free to comment here.

This is an automated response πŸ€–, but an Ultralytics engineer will review your PR and provide feedback soon. Thank you for helping improve YOLOv5! πŸš€βœ¨

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