The new state-of-the-art for real-time item detectors is a trainable bag of goodies.

Ramesh Koul

Abstract


In the range of 5 FPS to 160 FPS, YOLOv7 outperforms all other known object detectors in terms of speed and accuracy, and on GPU V100, it has the greatest accuracy of 56.8% AP of all real-time object detectors with 30 FPS or more. YOLOv7-E6 object detector (56 FPS V100, 55.9% AP) outperforms both transformer-based detector SWIN-L Cascade-Mask R-CNN (9.2 FPS A100, 53.9% AP) and convolutional-based detector ConvNeXt-XL Cascade-Mask R-CNN (8.6 FPS A100, 55.2% AP) by 509% in speed and 2% In addition, we train YOLOv7 from scratch using only the MS COCO dataset, not employing.

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