Hugging Face's logo

SUM010
/
model_fall

PaddlePaddle
Model card Files
xet
Community
model_fall
File size: 9,886 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
 
# 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/release/2.6/configs/faster_rcnn/)

### YOLOv3

Please refer to [YOLOv3](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/yolov3/)

### PP-YOLOE/PP-YOLOE+

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

### PP-YOLO/PP-YOLOv2

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

### PicoDet

Please refer to [PicoDet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/picodet)

### RetinaNet

Please refer to [RetinaNet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/retinanet/)

### Cascade R-CNN

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

### SSD/SSDLite

Please refer to [SSD](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/ssd/)

### FCOS

Please refer to [FCOS](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/fcos/)

### CenterNet

Please refer to [CenterNet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/centernet/)

### TTFNet/PAFNet

Please refer to [TTFNet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/ttfnet/)

### Group Normalization

Please refer to [Group Normalization](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/gn/)

### Deformable ConvNets v2

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

### HRNets

Please refer to [HRNets](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/hrnet/)

### Res2Net

Please refer to [Res2Net](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/res2net/)

### ConvNeXt

Please refer to [ConvNeXt](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/convnext/)

### GFL

Please refer to [GFL](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/gfl)

### TOOD

Please refer to [TOOD](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/tood)

### PSS-DET(RCNN-Enhance)

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

### DETR

Please refer to [DETR](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/detr)

### Deformable DETR

Please refer to [Deformable DETR](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/deformable_detr)

### Sparse R-CNN

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

###  Vision Transformer

Please refer to [Vision Transformer](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/vitdet)

### DINO

Please refer to [DINO](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/dino)

### YOLOX

Please refer to [YOLOX](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/yolox)

### YOLOF

Please refer to [YOLOF](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/yolof)


## Instance-Segmentation

### Mask R-CNN

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

### Cascade R-CNN

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

### SOLOv2

Please refer to [SOLOv2](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/solov2/)

### QueryInst

Please refer to [QueryInst](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/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/release/2.6/configs/face_detection)

### BlazeFace

Please refer to [BlazeFace](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/face_detection/)


## Rotated Object detection

Please refer to [Model Zoo for Rotated Object Detection](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/rotate)

### PP-YOLOE-R

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

### FCOSR

Please refer to [FCOSR](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/rotate/fcosr)

### S2ANet

Please refer to [S2ANet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/rotate/s2anet)


## KeyPoint Detection

Please refer to [Model Zoo for KeyPoint Detection](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/keypoint)

### PP-TinyPose

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

### HRNet

Please refer to [HRNet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/keypoint/hrnet)

### Lite-HRNet

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

### HigherHRNet

Please refer to [HigherHRNet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/keypoint/higherhrnet)


## Multi-Object Tracking

Please refer to [Model Zoo for Multi-Object Tracking](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/mot)

### DeepSORT

Please refer to [DeepSORT](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/mot/deepsort)

### ByteTrack

Please refer to [ByteTrack](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/mot/bytetrack)

### OC-SORT

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

### BoT-SORT

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

### CenterTrack

Please refer to [CenterTrack](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/mot/centertrack)

### FairMOT/MC-FairMOT

Please refer to [FairMOT](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/mot/fairmot)

### JDE

Please refer to [JDE](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6/configs/mot/jde)