Hugging Face's logo

SUM010
/
model_fall

PaddlePaddle
Model card Files
xet
Community
model_fall
File size: 9,059 Bytes
7b7527a
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
 
# 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/release/2.6/configs/faster_rcnn/)

### YOLOv3

请参考[YOLOv3](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/yolov3/)

### PP-YOLOE/PP-YOLOE+

请参考[PP-YOLOE](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/ppyoloe/)

### PP-YOLO/PP-YOLOv2

请参考[PP-YOLO](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/ppyolo/)

### PicoDet

请参考[PicoDet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/picodet)

### RetinaNet

请参考[RetinaNet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/retinanet/)

### Cascade R-CNN

请参考[Cascade R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/cascade_rcnn)

### SSD/SSDLite

请参考[SSD](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/ssd/)

### FCOS

请参考[FCOS](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/fcos/)

### CenterNet

请参考[CenterNet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/centernet/)

### TTFNet/PAFNet

请参考[TTFNet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/ttfnet/)

### Group Normalization

请参考[Group Normalization](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/gn/)

### Deformable ConvNets v2

请参考[Deformable ConvNets v2](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/dcn/)

### HRNets

请参考[HRNets](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/hrnet/)

### Res2Net

请参考[Res2Net](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/res2net/)

### ConvNeXt

请参考[ConvNeXt](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/convnext/)

### GFL

请参考[GFL](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/gfl)

### TOOD

请参考[TOOD](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/tood)

### PSS-DET(RCNN-Enhance)

请参考[PSS-DET](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/rcnn_enhance)

### DETR

请参考[DETR](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/detr)

### Deformable DETR

请参考[Deformable DETR](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/deformable_detr)

### Sparse R-CNN

请参考[Sparse R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/sparse_rcnn)

###  Vision Transformer

请参考[Vision Transformer](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/vitdet)

### DINO

请参考[DINO](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/dino)

### YOLOX

请参考[YOLOX](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/yolox)

### YOLOF

请参考[YOLOF](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/yolof)


## 实例分割

### Mask R-CNN

请参考[Mask R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/mask_rcnn/)

### Cascade R-CNN

请参考[Cascade R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/cascade_rcnn)

### SOLOv2

请参考[SOLOv2](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/solov2/)

### QueryInst

请参考[QueryInst](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/queryinst)


## [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/release/2.6/configs/face_detection)

### BlazeFace

请参考[BlazeFace](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/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/release/2.6/configs/rotate)

### PP-YOLOE-R

请参考[PP-YOLOE-R](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/rotate/ppyoloe_r)

### FCOSR

请参考[FCOSR](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/rotate/fcosr)

### S2ANet

请参考[S2ANet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/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/release/2.6/configs/keypoint)

### PP-TinyPose

请参考[PP-TinyPose](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/keypoint/tiny_pose)

### HRNet

请参考[HRNet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/keypoint/hrnet)

### Lite-HRNet

请参考[Lite-HRNet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/keypoint/lite_hrnet)

### HigherHRNet

请参考[HigherHRNet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/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/release/2.6/configs/mot)

### DeepSORT

请参考[DeepSORT](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/mot/deepsort)

### ByteTrack

请参考[ByteTrack](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/mot/bytetrack)

### OC-SORT

请参考[OC-SORT](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/mot/ocsort)

### BoT-SORT

请参考[BoT-SORT](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/mot/botsort)

### CenterTrack

请参考[CenterTrack](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/mot/centertrack)

### FairMOT/MC-FairMOT

请参考[FairMOT](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/mot/fairmot)

### JDE

请参考[JDE](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/mot/jde)