Spaces:
Running
Running
Delete app.py
Browse files
app.py
DELETED
@@ -1,185 +0,0 @@
|
|
1 |
-
#!/usr/bin/env python
|
2 |
-
|
3 |
-
从__未来_ _进口附注
|
4 |
-
|
5 |
-
进口argparse
|
6 |
-
进口functools
|
7 |
-
进口操作系统(操作系统)
|
8 |
-
进口超文本标记语言
|
9 |
-
进口pathlib
|
10 |
-
进口目标文件
|
11 |
-
|
12 |
-
进口deepdanbooru如同截止日期(截止日期的缩写)
|
13 |
-
进口格拉迪欧如同希腊
|
14 |
-
进口拥抱脸_集线器
|
15 |
-
进口numpy如同铭牌
|
16 |
-
进口PIL。图像
|
17 |
-
进口张量流如同法国南部(法国南部领地的缩写)
|
18 |
-
进口皮耶西弗
|
19 |
-
进口piexif.helper
|
20 |
-
|
21 |
-
标题=DeepDanbooru字符串'
|
22 |
-
|
23 |
-
TOKEN = os.environ['令牌']
|
24 |
-
型号_回购=yo2266911/DeepDanbooru_string'
|
25 |
-
型号文件名='型号-resnet_custom_v3.h5 '
|
26 |
-
标签文件名=' tags.txt '
|
27 |
-
|
28 |
-
|
29 |
-
极好的 解析参数()-> argparse。命名空间:
|
30 |
-
parser = argparse。ArgumentParser()
|
31 |
-
parser.add_argument(-分数-滑块-步长,类型=浮点型,默认值=0.05)
|
32 |
-
parser.add_argument("分数阈值",类型=浮点型,默认值=0.5)
|
33 |
-
parser.add_argument(主题,类型=字符串,默认值="暗草")
|
34 |
-
parser.add_argument(-直播,动作=' store_true ')
|
35 |
-
parser.add_argument(分享,动作=' store_true ')
|
36 |
-
parser.add_argument(-港口,type=int)
|
37 |
-
parser.add_argument(-禁用队列,
|
38 |
-
目标='启用队列',
|
39 |
-
动作=' store_false ')
|
40 |
-
parser.add_argument(-允许标记,类型=字符串,默认值=从来没有)
|
41 |
-
返回parser.parse_args()
|
42 |
-
|
43 |
-
|
44 |
-
极好的 加载_样本_图像_路径()-> list[pathlib。路径]:
|
45 |
-
image_dir = pathlib。路径('图像')
|
46 |
-
如果 不image_dir.exists():
|
47 |
-
数据集报告=' hysts/sample-images-TADNE '
|
48 |
-
路径=拥抱脸_集线器.HF _ hub _ download(数据集_报告
|
49 |
-
images.tar.gz的,
|
50 |
-
回购类型='数据集',
|
51 |
-
使用_认证_令牌=令牌)
|
52 |
-
随着tarfile.open(路径)如同女:
|
53 |
-
萃取塔
|
54 |
-
返回已排序(图片_目录.全球'*'))
|
55 |
-
|
56 |
-
|
57 |
-
极好的 负载模型()-> tf.keras.Model:
|
58 |
-
路径=拥抱脸_集线器.HF _ hub _下载(车型_ REPO,
|
59 |
-
型号_文件名,
|
60 |
-
使用_认证_令牌=令牌)
|
61 |
-
型号= TF .喀拉斯。模特。负载模型(路径)
|
62 |
-
返回模型
|
63 |
-
|
64 |
-
|
65 |
-
极好的 加载标签()-> list[str]:
|
66 |
-
路径=拥抱脸_集线器.HF _ hub _下载(车型_ REPO,
|
67 |
-
标签文件名,
|
68 |
-
使用_认证_令牌=令牌)
|
69 |
-
随着打开(路径)如同女:
|
70 |
-
labels = [line.strip()为线条在f.readlines()]
|
71 |
-
返回标签
|
72 |
-
|
73 |
-
极好的 明文转换为html(文本):
|
74 |
-
文本=" < p > " + " < br>\n "。加入([f "{html.escape(x)} "为x在文本分割(\n)]) +" </p > "
|
75 |
-
返回文本
|
76 |
-
|
77 |
-
极好的预测(图片:PIL .形象。Image,score_threshold: float,
|
78 |
-
模型:tf.keras.Model,标签:list[str]) -> dict[str,float]:
|
79 |
-
原始图像=图像
|
80 |
-
_,高度,宽度,_ =模型。输入_形状
|
81 |
-
image = np.asarray(image)
|
82 |
-
image = tf.image.resize(image,
|
83 |
-
大小=(高,宽),
|
84 |
-
方法= TF . image . size method . area,
|
85 |
-
preserve_aspect_ratio=真实的
|
86 |
-
image = image.numpy()
|
87 |
-
image = DD。形象。转换_和_ pad _ image(图像,宽度,高度)
|
88 |
-
图像=图像/255。
|
89 |
-
probs =模型。预测(图片[无,...])[0]
|
90 |
-
probs = probs.astype(float)
|
91 |
-
res = dict()
|
92 |
-
对于prob,zip中的标签(probs.tolist(),标签):
|
93 |
-
如果概率<分数阈值:
|
94 |
-
继续
|
95 |
-
RES[标签] = prob
|
96 |
-
b = dict(sorted(res.items(),key=希腊字母的第11个项目:项目[1],反向=真实的))
|
97 |
-
a =','。join(list(b.keys())).替换(' _ ',' ')。替换('(',' \(')。替换(')',' \)')
|
98 |
-
c =','。join(list(b.keys()))
|
99 |
-
|
100 |
-
items = rawimage.info
|
101 |
-
geninfo =' '
|
102 |
-
|
103 |
-
if "exif" in rawimage.info:
|
104 |
-
exif = piexif.load(rawimage.info["exif"])
|
105 |
-
exif_comment = (exif or {}).get("Exif", {}).get(piexif.ExifIFD.UserComment, b'')
|
106 |
-
try:
|
107 |
-
exif_comment = piexif.helper.UserComment.load(exif_comment)
|
108 |
-
except ValueError:
|
109 |
-
exif_comment = exif_comment.decode('utf8', errors="ignore")
|
110 |
-
|
111 |
-
items['exif comment'] = exif_comment
|
112 |
-
geninfo = exif_comment
|
113 |
-
|
114 |
-
for field in ['jfif', 'jfif_version', 'jfif_unit', 'jfif_density', 'dpi', 'exif',
|
115 |
-
'loop', 'background', 'timestamp', 'duration']:
|
116 |
-
items.pop(field, None)
|
117 |
-
|
118 |
-
geninfo = items.get('parameters', geninfo)
|
119 |
-
|
120 |
-
info = f"""
|
121 |
-
<p><h4>PNG Info</h4></p>
|
122 |
-
"""
|
123 |
-
for key, text in items.items():
|
124 |
-
info += f"""
|
125 |
-
<div>
|
126 |
-
<p><b>{plaintext_to_html(str(key))}</b></p>
|
127 |
-
<p>{plaintext_to_html(str(text))}</p>
|
128 |
-
</div>
|
129 |
-
""".strip()+"\n"
|
130 |
-
|
131 |
-
if len(info) == 0:
|
132 |
-
message = "Nothing found in the image."
|
133 |
-
info = f"<div><p>{message}<p></div>"
|
134 |
-
|
135 |
-
return (a,c,res,info)
|
136 |
-
|
137 |
-
|
138 |
-
def main():
|
139 |
-
args = parse_args()
|
140 |
-
model = load_model()
|
141 |
-
labels = load_labels()
|
142 |
-
|
143 |
-
func = functools.partial(predict, model=model, labels=labels)
|
144 |
-
func = functools.update_wrapper(func, predict)
|
145 |
-
|
146 |
-
gr.Interface(
|
147 |
-
func,
|
148 |
-
[
|
149 |
-
gr.inputs.Image(type='pil', label='Input'),
|
150 |
-
gr.inputs.Slider(0,
|
151 |
-
1,
|
152 |
-
step=args.score_slider_step,
|
153 |
-
default=args.score_threshold,
|
154 |
-
label='Score Threshold'),
|
155 |
-
],
|
156 |
-
[
|
157 |
-
gr.outputs.Textbox(label='Output (string)'),
|
158 |
-
gr.outputs.Textbox(label='Output (raw string)'),
|
159 |
-
gr.outputs.Label(label='Output (label)'),
|
160 |
-
gr.outputs.HTML()
|
161 |
-
],
|
162 |
-
examples=[
|
163 |
-
['miku.jpg',0.5],
|
164 |
-
['miku2.jpg',0.5]
|
165 |
-
],
|
166 |
-
title=TITLE,
|
167 |
-
description='''
|
168 |
-
Demo for [KichangKim/DeepDanbooru](https://github.com/KichangKim/DeepDanbooru) with "ready to copy" prompt and a prompt analyzer.
|
169 |
-
|
170 |
-
Modified from [hysts/DeepDanbooru](https://huggingface.co/spaces/hysts/DeepDanbooru)
|
171 |
-
|
172 |
-
PNG Info code forked from [AUTOMATIC1111/stable-diffusion-webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui)
|
173 |
-
''',
|
174 |
-
theme=args.theme,
|
175 |
-
allow_flagging=args.allow_flagging,
|
176 |
-
live=args.live,
|
177 |
-
).launch(
|
178 |
-
enable_queue=args.enable_queue,
|
179 |
-
server_port=args.port,
|
180 |
-
share=args.share,
|
181 |
-
)
|
182 |
-
|
183 |
-
|
184 |
-
if __name__ == '__main__':
|
185 |
-
main()
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|