Update app.py
Browse files
app.py
CHANGED
@@ -1,6 +1,10 @@
|
|
1 |
#!/usr/bin/env python
|
2 |
from __future__ import annotations
|
3 |
|
|
|
|
|
|
|
|
|
4 |
import os
|
5 |
import random
|
6 |
import time
|
@@ -55,6 +59,21 @@ pipe.vae_decoder = CustomOVModelVaeDecoder(model = OVBaseModel.load_model(f"{tae
|
|
55 |
pipe.reshape(batch_size=batch_size, height=height, width=width, num_images_per_prompt=num_images)
|
56 |
pipe.compile()
|
57 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
58 |
def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
|
59 |
if randomize_seed:
|
60 |
seed = random.randint(0, MAX_SEED)
|
@@ -73,6 +92,7 @@ def save_images(image_array, profile: gr.OAuthProfile | None, metadata: dict):
|
|
73 |
|
74 |
def generate(
|
75 |
prompt: str,
|
|
|
76 |
seed: int = 0,
|
77 |
guidance_scale: float = 8.0,
|
78 |
num_inference_steps: int = 4,
|
@@ -88,6 +108,7 @@ def generate(
|
|
88 |
seed = randomize_seed_fn(seed, randomize_seed)
|
89 |
np.random.seed(seed)
|
90 |
start_time = time.time()
|
|
|
91 |
result = pipe(
|
92 |
prompt=prompt,
|
93 |
width=width,
|
@@ -99,7 +120,7 @@ def generate(
|
|
99 |
).images
|
100 |
paths = save_images(result, profile, metadata={"prompt": prompt, "seed": seed, "width": width, "height": height, "guidance_scale": guidance_scale, "num_inference_steps": num_inference_steps})
|
101 |
print(time.time() - start_time)
|
102 |
-
return paths, seed
|
103 |
|
104 |
examples = [
|
105 |
"portrait photo of a girl, photograph, highly detailed face, depth of field, moody light, golden hour, style by Dan Winters, Russell James, Steve McCurry, centered, extremely detailed, Nikon D850, award winning photography",
|
@@ -115,6 +136,7 @@ with gr.Blocks(css="style.css") as demo:
|
|
115 |
elem_id="duplicate-button",
|
116 |
visible=os.getenv("SHOW_DUPLICATE_BUTTON") == "1",
|
117 |
)
|
|
|
118 |
with gr.Group():
|
119 |
with gr.Row():
|
120 |
prompt = gr.Text(
|
@@ -153,6 +175,15 @@ with gr.Blocks(css="style.css") as demo:
|
|
153 |
step=1,
|
154 |
value=4,
|
155 |
)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
156 |
|
157 |
gr.Examples(
|
158 |
examples=examples,
|
@@ -171,15 +202,17 @@ with gr.Blocks(css="style.css") as demo:
|
|
171 |
inputs=[
|
172 |
prompt,
|
173 |
seed,
|
|
|
174 |
guidance_scale,
|
175 |
num_inference_steps,
|
176 |
randomize_seed
|
177 |
],
|
178 |
-
outputs=[result, seed],
|
179 |
api_name="run",
|
180 |
)
|
181 |
|
182 |
if __name__ == "__main__":
|
183 |
demo.queue(api_open=False)
|
|
|
184 |
# demo.queue(max_size=20).launch()
|
185 |
-
demo.launch()
|
|
|
1 |
#!/usr/bin/env python
|
2 |
from __future__ import annotations
|
3 |
|
4 |
+
import requests
|
5 |
+
import re
|
6 |
+
import threading
|
7 |
+
|
8 |
import os
|
9 |
import random
|
10 |
import time
|
|
|
59 |
pipe.reshape(batch_size=batch_size, height=height, width=width, num_images_per_prompt=num_images)
|
60 |
pipe.compile()
|
61 |
|
62 |
+
# Personal Thing-----------------------------------
|
63 |
+
api_url = None
|
64 |
+
def make_api_request():
|
65 |
+
global api_url
|
66 |
+
response = requests.get("https://genielamp-image2.hf.space/")
|
67 |
+
api_url = response.text
|
68 |
+
match = re.search(r'"root"\s*:\s*"([^"]+)"', response.text)
|
69 |
+
api_url = match.group(1) + "/file="
|
70 |
+
print(api_url)
|
71 |
+
|
72 |
+
|
73 |
+
def delayed_api_request():
|
74 |
+
threading.Timer(10, make_api_request).start()
|
75 |
+
#------------------------------------------------------
|
76 |
+
|
77 |
def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
|
78 |
if randomize_seed:
|
79 |
seed = random.randint(0, MAX_SEED)
|
|
|
92 |
|
93 |
def generate(
|
94 |
prompt: str,
|
95 |
+
url: str,
|
96 |
seed: int = 0,
|
97 |
guidance_scale: float = 8.0,
|
98 |
num_inference_steps: int = 4,
|
|
|
108 |
seed = randomize_seed_fn(seed, randomize_seed)
|
109 |
np.random.seed(seed)
|
110 |
start_time = time.time()
|
111 |
+
url = api_url
|
112 |
result = pipe(
|
113 |
prompt=prompt,
|
114 |
width=width,
|
|
|
120 |
).images
|
121 |
paths = save_images(result, profile, metadata={"prompt": prompt, "seed": seed, "width": width, "height": height, "guidance_scale": guidance_scale, "num_inference_steps": num_inference_steps})
|
122 |
print(time.time() - start_time)
|
123 |
+
return paths, seed, url
|
124 |
|
125 |
examples = [
|
126 |
"portrait photo of a girl, photograph, highly detailed face, depth of field, moody light, golden hour, style by Dan Winters, Russell James, Steve McCurry, centered, extremely detailed, Nikon D850, award winning photography",
|
|
|
136 |
elem_id="duplicate-button",
|
137 |
visible=os.getenv("SHOW_DUPLICATE_BUTTON") == "1",
|
138 |
)
|
139 |
+
|
140 |
with gr.Group():
|
141 |
with gr.Row():
|
142 |
prompt = gr.Text(
|
|
|
175 |
step=1,
|
176 |
value=4,
|
177 |
)
|
178 |
+
url = gr.Text(
|
179 |
+
label="url",
|
180 |
+
value="Null",
|
181 |
+
show_label=False,
|
182 |
+
placeholder="Null",
|
183 |
+
max_lines=1,
|
184 |
+
container=False,
|
185 |
+
interactive=False,
|
186 |
+
)
|
187 |
|
188 |
gr.Examples(
|
189 |
examples=examples,
|
|
|
202 |
inputs=[
|
203 |
prompt,
|
204 |
seed,
|
205 |
+
url,
|
206 |
guidance_scale,
|
207 |
num_inference_steps,
|
208 |
randomize_seed
|
209 |
],
|
210 |
+
outputs=[result, seed, url],
|
211 |
api_name="run",
|
212 |
)
|
213 |
|
214 |
if __name__ == "__main__":
|
215 |
demo.queue(api_open=False)
|
216 |
+
delayed_api_request()
|
217 |
# demo.queue(max_size=20).launch()
|
218 |
+
demo.launch()
|