In the above figure, we can see that at 13 (ms) YOLOv7 gives approximately 55AP while YOLOv5 (r6.1) shows the same AP at approximately 27 (ms), which makes YOLOv7 120% faster than YOLOv5 (r6.1) on V100 GPU with a batch size of 1. In addition, from the figure, we can see that it has a higher AP than all the state of art detectors shown in the figure.

To learn more about the architecture behind the YOLOv7, click here.


ModelTest SizeAPtestAP50testAP75testbatch 1 fpsbatch 32 average time
YOLOv764051.4%69.7%55.9%161 fps2.8 ms




  title={{YOLOv7}: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors},

  author={Wang, Chien-Yao and Bochkovskiy, Alexey and Liao, Hong-Yuan Mark},

  journal={arXiv preprint arXiv:2207.02696},



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