# 模型库和基线 # 内容 - [基础设置](#基础设置) - [测试环境](#测试环境) - [通用设置](#通用设置) - [训练策略](#训练策略) - [ImageNet预训练模型](#ImageNet预训练模型) - [基线](#基线) - [目标检测](#目标检测) - [实例分割](#实例分割) - [PaddleYOLO](#PaddleYOLO) - [人脸检测](#人脸检测) - [旋转框检测](#旋转框检测) - [关键点检测](#关键点检测) - [多目标跟踪](#多目标跟踪) # 基础设置 ## 测试环境 - Python 3.7 - PaddlePaddle 每日版本 - CUDA 10.1 - cuDNN 7.5 - NCCL 2.4.8 ## 通用设置 - 所有模型均在COCO17数据集中训练和测试。 - [YOLOv5](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov5)、[YOLOv6](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov6)、[YOLOv7](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov7)和[YOLOv8](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov8)这几类模型的代码在[PaddleYOLO](https://github.com/PaddlePaddle/PaddleYOLO)中，**PaddleYOLO库开源协议为GPL 3.0**。 - 除非特殊说明，所有ResNet骨干网络采用[ResNet-B](https://arxiv.org/pdf/1812.01187)结构。 - **推理时间(fps)**: 推理时间是在一张Tesla V100的GPU上通过'tools/eval.py'测试所有验证集得到，单位是fps(图片数/秒), cuDNN版本是7.5，包括数据加载、网络前向执行和后处理, batch size是1。 ## 训练策略 - 我们采用和[Detectron](https://github.com/facebookresearch/Detectron/blob/master/MODEL_ZOO.md#training-schedules)相同的训练策略。 - 1x 策略表示：在总batch size为8时，初始学习率为0.01，在8 epoch和11 epoch后学习率分别下降10倍，最终训练12 epoch。 - 2x 策略为1x策略的两倍，同时学习率调整的epoch数位置也为1x的两倍。 ## ImageNet预训练模型 Paddle提供基于ImageNet的骨架网络预训练模型。所有预训练模型均通过标准的Imagenet-1k数据集训练得到，ResNet和MobileNet等是采用余弦学习率调整策略或SSLD知识蒸馏训练得到的高精度预训练模型，可在[PaddleClas](https://github.com/PaddlePaddle/PaddleClas)查看模型细节。 # 基线 ## 目标检测 ### Faster R-CNN 请参考[Faster R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/faster_rcnn/) ### YOLOv3 请参考[YOLOv3](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/) ### PP-YOLOE/PP-YOLOE+ 请参考[PP-YOLOE](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyoloe/) ### PP-YOLO/PP-YOLOv2 请参考[PP-YOLO](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/) ### PicoDet 请参考[PicoDet](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet) ### RetinaNet 请参考[RetinaNet](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/retinanet/) ### Cascade R-CNN 请参考[Cascade R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn) ### SSD/SSDLite 请参考[SSD](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ssd/) ### FCOS 请参考[FCOS](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/fcos/) ### CenterNet 请参考[CenterNet](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/centernet/) ### TTFNet/PAFNet 请参考[TTFNet](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ttfnet/) ### Group Normalization 请参考[Group Normalization](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/gn/) ### Deformable ConvNets v2 请参考[Deformable ConvNets v2](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dcn/) ### HRNets 请参考[HRNets](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/hrnet/) ### Res2Net 请参考[Res2Net](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/res2net/) ### ConvNeXt 请参考[ConvNeXt](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/convnext/) ### GFL 请参考[GFL](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/gfl) ### TOOD 请参考[TOOD](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/tood) ### PSS-DET(RCNN-Enhance) 请参考[PSS-DET](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/rcnn_enhance) ### DETR 请参考[DETR](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/detr) ### Deformable DETR 请参考[Deformable DETR](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/deformable_detr) ### Sparse R-CNN 请参考[Sparse R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/sparse_rcnn) ### Vision Transformer 请参考[Vision Transformer](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/vitdet) ### YOLOX 请参考[YOLOX](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolox) ### YOLOF 请参考[YOLOF](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolof) ## 实例分割 ### Mask R-CNN 请参考[Mask R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/) ### Cascade R-CNN 请参考[Cascade R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn) ### SOLOv2 请参考[SOLOv2](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/solov2/) ## [PaddleYOLO](https://github.com/PaddlePaddle/PaddleYOLO) 请参考[PaddleYOLO模型库](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/docs/MODEL_ZOO_cn.md) ### YOLOv5 请参考[YOLOv5](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov5) ### YOLOv6(v3.0) 请参考[YOLOv6](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov6) ### YOLOv7 请参考[YOLOv7](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov7) ### YOLOv8 请参考[YOLOv8](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov8) ### RTMDet 请参考[RTMDet](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/rtmdet) ## 人脸检测 请参考[人脸检测模型库](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/face_detection) ### BlazeFace 请参考[BlazeFace](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/face_detection/) ## 旋转框检测 请参考[旋转框检测模型库](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/rotate) ### PP-YOLOE-R 请参考[PP-YOLOE-R](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/rotate/ppyoloe_r) ### FCOSR 请参考[FCOSR](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/rotate/fcosr) ### S2ANet 请参考[S2ANet](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/rotate/s2anet) ## 关键点检测 请参考[关键点检测模型库](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/keypoint) ### PP-TinyPose 请参考[PP-TinyPose](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/keypoint/tiny_pose) ### HRNet 请参考[HRNet](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/keypoint/hrnet) ### Lite-HRNet 请参考[Lite-HRNet](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/keypoint/lite_hrnet) ### HigherHRNet 请参考[HigherHRNet](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/keypoint/higherhrnet) ## 多目标跟踪 请参考[多目标跟踪模型库](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot) ### DeepSORT 请参考[DeepSORT](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/deepsort) ### ByteTrack 请参考[ByteTrack](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/bytetrack) ### OC-SORT 请参考[OC-SORT](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/ocsort) ### BoT-SORT 请参考[BoT-SORT](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/botsort) ### CenterTrack 请参考[CenterTrack](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/centertrack) ### FairMOT/MC-FairMOT 请参考[FairMOT](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/fairmot) ### JDE 请参考[JDE](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde)