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革命神经网络

暗网#暗网是用C和CUDA书写的开源神经网络框架. 它快速,容易安装,并支持CPU和GPU的计算. Discord 邀请链接用于通讯和提问 : https://discord.gg/zSq8rtW (中文(简体) ). YOLOv7:相纸-YOLOv7:可训练袋活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活活 https://GitHub.com/WongKinYiu/yolov7 (中文(简体) ). - - - - - 说说看官方YOLOv7比YOLOv5的FPS高120%,比YOLOX高180%的FPS高120%的FPS,比ConvNext高150%的FPS高120%的FPS,比SWIN-L高500. YOLOv7在从5个FPS到160个FPS之间速度和准确度均超过了所有已知物体探测器,在所有已知的实时物体探测器中,AP的精度最高为56.8%,在GPU V100,分批=1. YOLOv7-e6(55.9%AP,56

核心特点

•paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors: https://arxiv.org/abs/2207.02696

•source code - Pytorch (use to reproduce results): https://github.com/WongKinYiu/yolov7

•YOLOv7-e6 (55.9% AP, 56 FPS V100 b=1) by +500% FPS faster than SWIN-L Cascade-Mask R-CNN (53.9% AP, 9.2 FPS A100 b=1)

•YOLOv7-e6 (55.9% AP, 56 FPS V100 b=1) by +550% FPS faster than ConvNeXt-XL C-M-RCNN (55.2% AP, 8.6 FPS A100 b=1)

•YOLOv7-w6 (54.6% AP, 84 FPS V100 b=1) by +120% FPS faster than YOLOv5-X6-r6.1 (55.0% AP, 38 FPS V100 b=1)

•YOLOv7-w6 (54.6% AP, 84 FPS V100 b=1) by +1200% FPS faster than Dual-Swin-T C-M-RCNN (53.6% AP, 6.5 FPS V100 b=1)

•YOLOv7x (52.9% AP, 114 FPS V100 b=1) by +150% FPS faster than PPYOLOE-X (51.9% AP, 45 FPS V100 b=1)

•YOLOv7 (51.2% AP, 161 FPS V100 b=1) by +180% FPS faster than YOLOX-X (51.1% AP, 58 FPS V100 b=1)

•paper (CVPR 2021): https://openaccess.thecvf.com/content/CVPR2021/html/Wang_Scaled-YOLOv4_Scaling_Cross_Stage_Partial_Network_CVPR_2021_paper.html

•source code - Pytorch (use to reproduce results): https://github.com/WongKinYiu/ScaledYOLOv4

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