更换文档检测模型

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# 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),[YOLOv7](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov7) and [YOLOv8](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov8) 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)
### DINO
Please refer to [DINO](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dino)
### YOLOX
Please refer to [YOLOX](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolox)
### YOLOF
Please refer to [YOLOF](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolof)
## 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/)
### QueryInst
Please refer to [QueryInst](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/queryinst)
## [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(v3.0)
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)
### YOLOv8
Please refer to [YOLOv7](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov8)
### 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)
### BoT-SORT
Please refer to [BoT-SORT](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/botsort)
### CenterTrack
Please refer to [CenterTrack](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/centertrack)
### 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)