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.
Performance
| Model | Test Size | APtest | AP50test | AP75test | batch 1 fps | batch 32 average time |
|---|---|---|---|---|---|---|
| YOLOv7 | 640 | 51.4% | 69.7% | 55.9% | 161 fps | 2.8 ms |
Citation
@article{wang2022yolov7,
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},
year={2022}
}
