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The code uses multiple frameworks to run YOLOv5 detection in C++. Unlike many existing tutorials, this repo implements dynamic input shape detection for all frameworks, which can accelerate inference speed a lot, but is not actively mentioned in many tutorials. Check out the link for more content.
Many thanks to ultralytics/yolov5 community because this repository helped many people learn and use YOLO.
Some demos:
The text was updated successfully, but these errors were encountered:
👋 Hello @Avafly, thank you for sharing your amazing work with us! 🚀 Your repository looks like a fantastic resource for the community, and we appreciate your contribution and support. It's great to see new implementations that optimize and extend the use of YOLOv5 across various frameworks.
If you have any questions or encounters with bugs in YOLOv5, please feel free to provide a minimum reproducible example to help us understand and address the issue effectively.
An Ultralytics engineer will review your message and assist you soon. In the meantime, don't forget to check our ⭐️ Tutorials for more insights and guidance on using YOLOv5.
Happy coding! 😃
Avafly
changed the title
YOLOv5 ncnn OpenVINO MNN ONNXRuntime OpenCV CPP Implementation
YOLOv5 ncnn OpenVINO MNN ONNXRuntime OpenCV CPP Implementations
Oct 17, 2024
Hi YOLOv5 community!
I created a repository that might be helpful to some people: YOLOv5-ncnn-OpenVINO-MNN-ONNXRuntime-OpenCV-CPP.
The code uses multiple frameworks to run YOLOv5 detection in C++. Unlike many existing tutorials, this repo implements dynamic input shape detection for all frameworks, which can accelerate inference speed a lot, but is not actively mentioned in many tutorials. Check out the link for more content.
Many thanks to ultralytics/yolov5 community because this repository helped many people learn and use YOLO.
Some demos:
The text was updated successfully, but these errors were encountered: