🚀 RT-DETR (Real-Time DEtection TRansformer) is now available on Hugging Face Transformers! Developed by experts at Peking University and Baidu, Inc., RT-DETR is setting new standards in real-time object detection. It builds upon the foundational DETR model, initially created by AI researchers at Meta.
What Sets RT-DETR Apart?
✅ End-to-End Design: Eliminates the need for NMS, enhancing both speed and accuracy.
✅ Hybrid Encoder: Optimizes multi-scale feature processing for faster performance.
✅ Uncertainty-Minimal Queries: Boosts accuracy with high-quality initial decoder queries.
✅ Superior Performance: Achieves up to 54.3% AP and 108 FPS on COCO, outperforming traditional models.
What are your thoughts on the trade-offs between DETR’s robustness and YOLO’s speed, especially considering YOLO's sensitivity to NMS issues? Share your insights in the comments below! 👀🚀
Source Code: github.com/farukalamai/cvpr-2...
🔗 For inquiries or to discuss your own computer vision project or want to do something using RT-DETR (Real-Time DEtection TRansformer), feel free to contact us:
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