YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

by   Chien-Yao Wang, et al.

YOLOv7 surpasses all known object detectors in both speed and accuracy in the range from 5 FPS to 160 FPS and has the highest accuracy 56.8 known real-time object detectors with 30 FPS or higher on GPU V100. YOLOv7-E6 object detector (56 FPS V100, 55.9 detector SWIN-L Cascade-Mask R-CNN (9.2 FPS A100, 53.9 and 2 R-CNN (8.6 FPS A100, 55.2 well as YOLOv7 outperforms: YOLOR, YOLOX, Scaled-YOLOv4, YOLOv5, DETR, Deformable DETR, DINO-5scale-R50, ViT-Adapter-B and many other object detectors in speed and accuracy. Moreover, we train YOLOv7 only on MS COCO dataset from scratch without using any other datasets or pre-trained weights. Source code is released in https://github.com/WongKinYiu/yolov7.


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