# Model Zoos and Baselines # Content - [Basic Settings](#Basic-Settings) - [Test Environment](#Test-Environment) - [General Settings](#General-Settings) - [Training strategy](#Training-strategy) - [ImageNet pretraining model](#ImageNet-pretraining-model) - [Baseline](#Baseline) - [Object Detection](#Object-Detection) - [Instance Segmentation](#Instance-Segmentation) - [PaddleYOLO](#PaddleYOLO) - [Face Detection](#Face-Detection) - [Rotated Object detection](#Rotated-Object-detection) - [KeyPoint Detection](#KeyPoint-Detection) - [Multi Object Tracking](#Multi-Object-Tracking) # Basic Settings ## Test Environment - Python 3.7 - PaddlePaddle Daily version - CUDA 10.1 - cuDNN 7.5 - NCCL 2.4.8 ## General Settings - All models were trained and tested in the COCO17 dataset. - The codes of [YOLOv5](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov5),[YOLOv6](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov6) and [YOLOv7](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov7) can be found in [PaddleYOLO](https://github.com/PaddlePaddle/PaddleYOLO). Note that **the LICENSE of PaddleYOLO is GPL 3.0**. - Unless special instructions, all the ResNet backbone network using [ResNet-B](https://arxiv.org/pdf/1812.01187) structure. - **Inference time (FPS)**: The reasoning time was calculated on a Tesla V100 GPU by `tools/eval.py` testing all validation sets in FPS (number of pictures/second). CuDNN version is 7.5, including data loading, network forward execution and post-processing, and Batch size is 1. ## Training strategy - We adopt and [Detectron](https://github.com/facebookresearch/Detectron/blob/master/MODEL_ZOO.md#training-schedules) in the same training strategy. - 1x strategy indicates that when the total batch size is 8, the initial learning rate is 0.01, and the learning rate decreases by 10 times after 8 epoch and 11 epoch, respectively, and the final training is 12 epoch. - 2x strategy is twice as much as strategy 1x, and the learning rate adjustment position of epochs is twice as much as strategy 1x. ## ImageNet pretraining model Paddle provides a skeleton network pretraining model based on ImageNet. All pre-training models were trained by standard Imagenet 1K dataset. ResNet and MobileNet are high-precision pre-training models obtained by cosine learning rate adjustment strategy or SSLD knowledge distillation training. Model details are available at [PaddleClas](https://github.com/PaddlePaddle/PaddleClas). # Baseline ## Object Detection ### Faster R-CNN Please refer to [Faster R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/faster_rcnn/) ### YOLOv3 Please refer to [YOLOv3](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/) ### PP-YOLOE/PP-YOLOE+ Please refer to [PP-YOLOE](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyoloe/) ### PP-YOLO/PP-YOLOv2 Please refer to [PP-YOLO](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/) ### PicoDet Please refer to [PicoDet](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet) ### RetinaNet Please refer to [RetinaNet](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/retinanet/) ### Cascade R-CNN Please refer to [Cascade R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn) ### SSD/SSDLite Please refer to [SSD](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ssd/) ### FCOS Please refer to [FCOS](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/fcos/) ### CenterNet Please refer to [CenterNet](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/centernet/) ### TTFNet/PAFNet Please refer to [TTFNet](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ttfnet/) ### Group Normalization Please refer to [Group Normalization](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/gn/) ### Deformable ConvNets v2 Please refer to [Deformable ConvNets v2](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dcn/) ### HRNets Please refer to [HRNets](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/hrnet/) ### Res2Net Please refer to [Res2Net](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/res2net/) ### ConvNeXt Please refer to [ConvNeXt](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/convnext/) ### GFL Please refer to [GFL](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/gfl) ### TOOD Please refer to [TOOD](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/tood) ### PSS-DET(RCNN-Enhance) Please refer to [PSS-DET](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/rcnn_enhance) ### DETR Please refer to [DETR](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/detr) ### Deformable DETR Please refer to [Deformable DETR](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/deformable_detr) ### Sparse R-CNN Please refer to [Sparse R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/sparse_rcnn) ### Vision Transformer Please refer to [Vision Transformer](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/vitdet) ### YOLOX Please refer to [YOLOX](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolox) ## Instance-Segmentation ### Mask R-CNN Please refer to [Mask R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/) ### Cascade R-CNN Please refer to [Cascade R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn) ### SOLOv2 Please refer to [SOLOv2](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/solov2/) ## [PaddleYOLO](https://github.com/PaddlePaddle/PaddleYOLO) Please refer to [Model Zoo for PaddleYOLO](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/docs/MODEL_ZOO_en.md) ### YOLOv5 Please refer to [YOLOv5](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov5) ### YOLOv6 Please refer to [YOLOv6](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov6) ### YOLOv7 Please refer to [YOLOv7](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov7) ### RTMDet Please refer to [RTMDet](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/rtmdet) ## Face Detection Please refer to [Model Zoo for Face Detection](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/face_detection) ### BlazeFace Please refer to [BlazeFace](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/face_detection/) ## Rotated Object detection Please refer to [Model Zoo for Rotated Object Detection](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/rotate) ### PP-YOLOE-R Please refer to [PP-YOLOE-R](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/rotate/ppyoloe_r) ### FCOSR Please refer to [FCOSR](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/rotate/fcosr) ### S2ANet Please refer to [S2ANet](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/rotate/s2anet) ## KeyPoint Detection Please refer to [Model Zoo for KeyPoint Detection](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/keypoint) ### PP-TinyPose Please refer to [PP-TinyPose](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/keypoint/tiny_pose) ### HRNet Please refer to [HRNet](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/keypoint/hrnet) ### Lite-HRNet Please refer to [Lite-HRNet](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/keypoint/lite_hrnet) ### HigherHRNet Please refer to [HigherHRNet](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/keypoint/higherhrnet) ## Multi-Object Tracking Please refer to [Model Zoo for Multi-Object Tracking](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot) ### DeepSORT Please refer to [DeepSORT](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/deepsort) ### ByteTrack Please refer to [ByteTrack](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/bytetrack) ### OC-SORT Please refer to [OC-SORT](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/ocsort) ### FairMOT/MC-FairMOT Please refer to [FairMOT](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/fairmot) ### JDE Please refer to [JDE](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde)