Spaces:
Sleeping
Sleeping
Update app.py
Browse files
app.py
CHANGED
@@ -1,20 +1,22 @@
|
|
1 |
import gradio as gr
|
2 |
import numpy as np
|
3 |
-
import random
|
4 |
import torch
|
5 |
from diffusers import DiffusionPipeline
|
|
|
6 |
|
|
|
7 |
device = "cuda" if torch.cuda.is_available() else "cpu"
|
8 |
-
|
9 |
|
10 |
-
|
11 |
-
|
12 |
-
else:
|
13 |
-
torch_dtype = torch.float32
|
14 |
|
15 |
-
|
16 |
-
|
17 |
-
|
|
|
|
|
|
|
18 |
|
19 |
MAX_SEED = np.iinfo(np.int32).max
|
20 |
MAX_IMAGE_SIZE = 1024
|
@@ -31,28 +33,34 @@ def infer(
|
|
31 |
progress=gr.Progress(track_tqdm=True),
|
32 |
):
|
33 |
global model_repo_id, pipe
|
34 |
-
|
35 |
-
#
|
36 |
if model != model_repo_id:
|
|
|
|
|
37 |
try:
|
38 |
-
new_pipe = DiffusionPipeline.from_pretrained(model, torch_dtype=torch_dtype)
|
39 |
-
new_pipe = new_pipe.to(device)
|
40 |
pipe = new_pipe
|
41 |
model_repo_id = model
|
42 |
except Exception as e:
|
43 |
raise gr.Error(f"Не удалось загрузить модель '{model}'.\nОшибка: {e}")
|
44 |
|
|
|
45 |
generator = torch.Generator(device=device).manual_seed(seed)
|
46 |
|
47 |
-
|
48 |
-
|
49 |
-
|
50 |
-
|
51 |
-
|
52 |
-
|
53 |
-
|
54 |
-
|
55 |
-
|
|
|
|
|
|
|
|
|
56 |
|
57 |
return image, seed
|
58 |
|
@@ -69,14 +77,13 @@ css = """
|
|
69 |
}
|
70 |
"""
|
71 |
|
72 |
-
# Убрали выпадающее меню, заменили на текстовое поле
|
73 |
with gr.Blocks(css=css) as demo:
|
74 |
with gr.Column(elem_id="col-container"):
|
75 |
-
gr.Markdown("
|
76 |
|
77 |
model = gr.Textbox(
|
78 |
label="Model",
|
79 |
-
value="
|
80 |
interactive=True
|
81 |
)
|
82 |
|
@@ -87,14 +94,14 @@ with gr.Blocks(css=css) as demo:
|
|
87 |
placeholder="Enter your prompt",
|
88 |
container=False,
|
89 |
)
|
90 |
-
|
91 |
negative_prompt = gr.Text(
|
92 |
label="Negative prompt",
|
93 |
max_lines=1,
|
94 |
placeholder="Enter a negative prompt",
|
95 |
visible=True,
|
96 |
)
|
97 |
-
|
98 |
seed = gr.Slider(
|
99 |
label="Seed",
|
100 |
minimum=0,
|
@@ -102,7 +109,7 @@ with gr.Blocks(css=css) as demo:
|
|
102 |
step=1,
|
103 |
value=42,
|
104 |
)
|
105 |
-
|
106 |
guidance_scale = gr.Slider(
|
107 |
label="Guidance scale",
|
108 |
minimum=0.0,
|
@@ -118,8 +125,8 @@ with gr.Blocks(css=css) as demo:
|
|
118 |
step=1,
|
119 |
value=20,
|
120 |
)
|
121 |
-
|
122 |
-
run_button = gr.Button("Run",
|
123 |
result = gr.Image(label="Result", show_label=False)
|
124 |
|
125 |
with gr.Accordion("Advanced Settings", open=False):
|
@@ -129,33 +136,32 @@ with gr.Blocks(css=css) as demo:
|
|
129 |
minimum=256,
|
130 |
maximum=MAX_IMAGE_SIZE,
|
131 |
step=32,
|
132 |
-
value=
|
133 |
)
|
134 |
height = gr.Slider(
|
135 |
label="Height",
|
136 |
minimum=256,
|
137 |
maximum=MAX_IMAGE_SIZE,
|
138 |
step=32,
|
139 |
-
value=
|
140 |
)
|
141 |
|
142 |
gr.Examples(examples=examples, inputs=[prompt])
|
143 |
|
144 |
-
|
145 |
-
|
146 |
-
|
147 |
-
|
148 |
-
|
149 |
-
|
150 |
-
|
151 |
-
|
152 |
-
|
153 |
-
|
154 |
-
|
155 |
-
|
156 |
-
|
157 |
-
|
158 |
-
)
|
159 |
|
160 |
if __name__ == "__main__":
|
161 |
demo.launch()
|
|
|
1 |
import gradio as gr
|
2 |
import numpy as np
|
|
|
3 |
import torch
|
4 |
from diffusers import DiffusionPipeline
|
5 |
+
import re
|
6 |
|
7 |
+
# Устройство и параметры загрузки модели
|
8 |
device = "cuda" if torch.cuda.is_available() else "cpu"
|
9 |
+
torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32
|
10 |
|
11 |
+
# Регулярное выражение для проверки корректности модели
|
12 |
+
VALID_REPO_ID_REGEX = re.compile(r"^[a-zA-Z0-9._\-]+/[a-zA-Z0-9._\-]+$")
|
|
|
|
|
13 |
|
14 |
+
def is_valid_repo_id(repo_id):
|
15 |
+
return bool(VALID_REPO_ID_REGEX.match(repo_id)) and not repo_id.endswith(('-', '.'))
|
16 |
+
|
17 |
+
# Изначально загружаем модель по умолчанию
|
18 |
+
model_repo_id = "CompVis/stable-diffusion-v1-4"
|
19 |
+
pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype).to(device)
|
20 |
|
21 |
MAX_SEED = np.iinfo(np.int32).max
|
22 |
MAX_IMAGE_SIZE = 1024
|
|
|
33 |
progress=gr.Progress(track_tqdm=True),
|
34 |
):
|
35 |
global model_repo_id, pipe
|
36 |
+
|
37 |
+
# Проверяем и загружаем новую модель, если она изменена
|
38 |
if model != model_repo_id:
|
39 |
+
if not is_valid_repo_id(model):
|
40 |
+
raise gr.Error(f"Некорректный идентификатор модели: '{model}'. Проверьте название.")
|
41 |
try:
|
42 |
+
new_pipe = DiffusionPipeline.from_pretrained(model, torch_dtype=torch_dtype).to(device)
|
|
|
43 |
pipe = new_pipe
|
44 |
model_repo_id = model
|
45 |
except Exception as e:
|
46 |
raise gr.Error(f"Не удалось загрузить модель '{model}'.\nОшибка: {e}")
|
47 |
|
48 |
+
# Генератор случайных чисел для детерминированности
|
49 |
generator = torch.Generator(device=device).manual_seed(seed)
|
50 |
|
51 |
+
# Генерация изображения
|
52 |
+
try:
|
53 |
+
image = pipe(
|
54 |
+
prompt=prompt,
|
55 |
+
negative_prompt=negative_prompt,
|
56 |
+
guidance_scale=guidance_scale,
|
57 |
+
num_inference_steps=num_inference_steps,
|
58 |
+
width=width,
|
59 |
+
height=height,
|
60 |
+
generator=generator,
|
61 |
+
).images[0]
|
62 |
+
except Exception as e:
|
63 |
+
raise gr.Error(f"Ошибка при генерации изображения: {e}")
|
64 |
|
65 |
return image, seed
|
66 |
|
|
|
77 |
}
|
78 |
"""
|
79 |
|
|
|
80 |
with gr.Blocks(css=css) as demo:
|
81 |
with gr.Column(elem_id="col-container"):
|
82 |
+
gr.Markdown("# Text-to-Image App")
|
83 |
|
84 |
model = gr.Textbox(
|
85 |
label="Model",
|
86 |
+
value="CompVis/stable-diffusion-v1-4", # Значение по умолчанию
|
87 |
interactive=True
|
88 |
)
|
89 |
|
|
|
94 |
placeholder="Enter your prompt",
|
95 |
container=False,
|
96 |
)
|
97 |
+
|
98 |
negative_prompt = gr.Text(
|
99 |
label="Negative prompt",
|
100 |
max_lines=1,
|
101 |
placeholder="Enter a negative prompt",
|
102 |
visible=True,
|
103 |
)
|
104 |
+
|
105 |
seed = gr.Slider(
|
106 |
label="Seed",
|
107 |
minimum=0,
|
|
|
109 |
step=1,
|
110 |
value=42,
|
111 |
)
|
112 |
+
|
113 |
guidance_scale = gr.Slider(
|
114 |
label="Guidance scale",
|
115 |
minimum=0.0,
|
|
|
125 |
step=1,
|
126 |
value=20,
|
127 |
)
|
128 |
+
|
129 |
+
run_button = gr.Button("Run", variant="primary")
|
130 |
result = gr.Image(label="Result", show_label=False)
|
131 |
|
132 |
with gr.Accordion("Advanced Settings", open=False):
|
|
|
136 |
minimum=256,
|
137 |
maximum=MAX_IMAGE_SIZE,
|
138 |
step=32,
|
139 |
+
value=512,
|
140 |
)
|
141 |
height = gr.Slider(
|
142 |
label="Height",
|
143 |
minimum=256,
|
144 |
maximum=MAX_IMAGE_SIZE,
|
145 |
step=32,
|
146 |
+
value=512,
|
147 |
)
|
148 |
|
149 |
gr.Examples(examples=examples, inputs=[prompt])
|
150 |
|
151 |
+
run_button.click(
|
152 |
+
infer,
|
153 |
+
inputs=[
|
154 |
+
model,
|
155 |
+
prompt,
|
156 |
+
negative_prompt,
|
157 |
+
seed,
|
158 |
+
width,
|
159 |
+
height,
|
160 |
+
guidance_scale,
|
161 |
+
num_inference_steps,
|
162 |
+
],
|
163 |
+
outputs=[result, seed],
|
164 |
+
)
|
|
|
165 |
|
166 |
if __name__ == "__main__":
|
167 |
demo.launch()
|