“YoloV7”？目标检测算法终结篇：正式开源

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作者：Edison_G

请注意，这里的7，不是下一代YOLO，而是一个幸运数字，姑且可以看作是一个代号。它的目的是让YOLO全面开花，不仅仅只是做目标检测。也不是简单的加一个semantic head做分割，而是做一个体系的目标检测积木模块，即插即用，使之能够更简单的做复杂的上层任务，比如多个分类head，实例分割，甚至是加上姿态检测等等。

转自《知乎——金天》

链接：https://zhuanlan.zhihu.com/p/464007111

介绍

目前支持的东西就这么一些，现列举一些大家可能感兴趣的：

• 支持GridMask，Mosiac的数据增强，而且可以可视化；

• 支持YOLOX（很强），而且部署方式比原版更方便，可训练，官方不是唯一可选；

• 支持YOLOv7+实例分割，是SingleStage的方式，目前用的是OrienMaskHead，未来可能增加更多方式；

• 支持DETR，AnchorDETR等transformer，这是独一无二的，在一个框架里面同时被支持；

• YOLOv4 contained with CSP-Darknet53;

• YOLOv7 arch with resnets backbone;

• YOLOv7 arch with resnet-vd backbone (likely as PP-YOLO), deformable conv, Mish etc;

• GridMask augmentation from PP-YOLO included;

• YOLOv7 arch Swin-Transformer support (higher accuracy but lower speed);

• YOLOv7 arch Efficientnet + BiFPN;

• YOLOv5 style positive samples selection, new coordinates coding style;

• RandomColorDistortion, RandomExpand, RandomCrop, RandomFlip;

• CIoU loss (DIoU, GIoU) and label smoothing (from YOLOv5 & YOLOv4);

• YOLOF also included;

• YOLOv7 Res2net + FPN supported;

• Pyramid Vision Transformer v2 (PVTv2) supported;

• WBF (Weighted Box Fusion), this works better than NMS, link;

• YOLOX like head design and anchor design, also training support;

• YOLOX s,m,l backbone and PAFPN added, we have a new combination of YOLOX backbone and pafpn;

• YOLOv7 with Res2Net-v1d backbone, we found res2net-v1d have a better accuracy then darknet53;

• Added PPYOLOv2 PAN neck with SPP and dropblock;

• YOLOX arch added, now you can train YOLOX model (anchor free yolo) as well;

• DETR: transformer based detection model and onnx export supported, as well as TensorRT acceleration;

• AnchorDETR: Faster converge version of detr, now supported!