Hugging Face's logo

happyme531
/
wd-convnext-tagger-v3-RKNN2

rknn
Model card Files Community
wd-convnext-tagger-v3-RKNN2
File size: 2,847 Bytes 
09349b9
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7b3db4c
 
 
09349b9
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
da85c18
09349b9
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7b3db4c
 
 
09349b9
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
 
---
license: agpl-3.0
base_model: SmilingWolf/wd-convnext-tagger-v3
tags:
- rknn
---

# WD ConvNext Tagger v3 RKNN2

## (English README see below)

在RK3588上运行WaifuDiffusion图像标签模型!

- 推理速度(RK3588):
  - 单NPU核: 320ms
  
- 内存占用(RK3588): 
  - 0.45GB

## 使用方法

1. 克隆或者下载此仓库到本地
   
2. 安装依赖

```bash
pip install numpy<2 pandas opencv-python rknn-toolkit-lite2
```

3. 运行
   
```bash
python run_rknn.py input.jpg
```

输出结果示例:

![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/6319d0860d7478ae0069cd92/FUx2XdHnAuxIPr464B-_l.jpeg)

```log
       tag_id           name     probs
0     9999999        general  0.521484
5      212816           solo  0.929199
12      15080     short_hair  0.520508
25     540830           1boy  0.947754
40      16613        jewelry  0.577148
72    1300281     male_focus  0.907227
130     10926          pants  0.803223
346   1094664   colored_skin  0.570312
373      4009     turtleneck  0.552246
1532  1314823  black_sweater  0.514160
```

## 模型转换

1. 安装依赖

```bash
pip install numpy<2 onnxruntime rknn-toolkit2
```

2. 下载原始onnx模型

3. 转换onnx模型到rknn模型:

```bash
python convert_rknn.py
```

## 已知问题

- int8量化后精度损失极大, 基本不可用. 不建议使用量化推理.

## 参考

- [SmilingWolf/wd-convnext-tagger-v3](https://huggingface.co/SmilingWolf/wd-convnext-tagger-v3)

## English README

Run WaifuDiffusion image tagging model on RK3588!

- Inference Speed (RK3588):
  - Single NPU Core: 320ms

- Memory Usage (RK3588):
  - 0.45GB

## Usage

1. Clone or download this repository

2. Install dependencies

```bash
pip install numpy<2 pandas opencv-python rknn-toolkit-lite2
```

3. Run

```bash
python run_rknn.py input.jpg
```

Output example:

![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/6319d0860d7478ae0069cd92/FUx2XdHnAuxIPr464B-_l.jpeg)

```log
       tag_id           name     probs
0     9999999        general  0.521484
5      212816           solo  0.929199
12      15080     short_hair  0.520508
25     540830           1boy  0.947754
40      16613        jewelry  0.577148
72    1300281     male_focus  0.907227
130     10926          pants  0.803223
346   1094664   colored_skin  0.570312
373      4009     turtleneck  0.552246
1532  1314823  black_sweater  0.514160
```


## Model Conversion

1. Install dependencies

```bash
pip install numpy<2 onnxruntime rknn-toolkit2
```

2. Download original onnx model

3. Convert onnx model to rknn model:

```bash
python convert_rknn.py
```

## Known Issues

- Huge precision loss after int8 quantization, not recommended to use quantized inference.

## References

- [SmilingWolf/wd-convnext-tagger-v3](https://huggingface.co/SmilingWolf/wd-convnext-tagger-v3)