Spaces:
Running
Running
Update app.py
Browse files
app.py
CHANGED
@@ -1,17 +1,21 @@
|
|
1 |
import gradio as gr
|
2 |
import torch
|
3 |
-
from diffusers import StableDiffusionXLPipeline, AutoencoderKL, KDPM2AncestralDiscreteScheduler
|
4 |
from huggingface_hub import hf_hub_download
|
5 |
import spaces
|
6 |
from PIL import Image
|
7 |
import requests
|
8 |
from translatepy import Translator
|
|
|
|
|
|
|
9 |
|
10 |
translator = Translator()
|
11 |
|
12 |
# Constants
|
13 |
model = "Corcelio/mobius"
|
14 |
vae_model = "madebyollin/sdxl-vae-fp16-fix"
|
|
|
15 |
|
16 |
CSS = """
|
17 |
.gradio-container {
|
@@ -37,7 +41,8 @@ vae = AutoencoderKL.from_pretrained(
|
|
37 |
|
38 |
# Ensure model and scheduler are initialized in GPU-enabled function
|
39 |
if torch.cuda.is_available():
|
40 |
-
|
|
|
41 |
|
42 |
pipe.scheduler = KDPM2AncestralDiscreteScheduler.from_config(pipe.scheduler.config)
|
43 |
|
@@ -49,13 +54,21 @@ def generate_image(
|
|
49 |
negative="low quality",
|
50 |
width=1024,
|
51 |
height=1024,
|
|
|
|
|
52 |
scale=1.5,
|
53 |
steps=30,
|
54 |
clip=3):
|
55 |
|
|
|
|
|
|
|
|
|
|
|
56 |
prompt = str(translator.translate(prompt, 'English'))
|
57 |
|
58 |
print(f'prompt:{prompt}')
|
|
|
59 |
|
60 |
image = pipe(
|
61 |
prompt,
|
@@ -63,10 +76,12 @@ def generate_image(
|
|
63 |
width=width,
|
64 |
height=height,
|
65 |
guidance_scale=scale,
|
|
|
66 |
num_inference_steps=steps,
|
|
|
67 |
clip_skip=clip,
|
68 |
-
)
|
69 |
-
return image
|
70 |
|
71 |
|
72 |
examples = [
|
@@ -84,15 +99,15 @@ examples = [
|
|
84 |
|
85 |
with gr.Blocks(css=CSS, js=JS, theme="soft") as demo:
|
86 |
gr.HTML("<h1><center>Mobius💠</center></h1>")
|
87 |
-
gr.HTML("<p><center><a href='https://huggingface.co/Corcelio/mobius'>mobius</a> text-to-image generation</center><br><center>
|
88 |
with gr.Group():
|
89 |
with gr.Row():
|
90 |
-
prompt = gr.Textbox(label='Enter Your Prompt', value="best quality, HD, aesthetic", scale=6)
|
91 |
submit = gr.Button(scale=1, variant='primary')
|
92 |
-
img = gr.
|
93 |
with gr.Accordion("Advanced Options", open=False):
|
94 |
with gr.Row():
|
95 |
-
negative = gr.Textbox(label="Negative prompt", value="low quality")
|
96 |
with gr.Row():
|
97 |
width = gr.Slider(
|
98 |
label="Width",
|
@@ -108,6 +123,23 @@ with gr.Blocks(css=CSS, js=JS, theme="soft") as demo:
|
|
108 |
step=8,
|
109 |
value=1024,
|
110 |
)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
111 |
with gr.Row():
|
112 |
scale = gr.Slider(
|
113 |
label="Guidance",
|
@@ -129,7 +161,7 @@ with gr.Blocks(css=CSS, js=JS, theme="soft") as demo:
|
|
129 |
maximum=10,
|
130 |
step=1,
|
131 |
value=3,
|
132 |
-
)
|
133 |
gr.Examples(
|
134 |
examples=examples,
|
135 |
inputs=prompt,
|
@@ -139,11 +171,11 @@ with gr.Blocks(css=CSS, js=JS, theme="soft") as demo:
|
|
139 |
)
|
140 |
|
141 |
prompt.submit(fn=generate_image,
|
142 |
-
inputs=[prompt, negative, width, height, scale, steps, clip],
|
143 |
outputs=img,
|
144 |
)
|
145 |
submit.click(fn=generate_image,
|
146 |
-
inputs=[prompt, negative, width, height, scale, steps, clip],
|
147 |
outputs=img,
|
148 |
)
|
149 |
|
|
|
1 |
import gradio as gr
|
2 |
import torch
|
3 |
+
from diffusers import StableDiffusionXLPipeline, AutoencoderKL, KDPM2AncestralDiscreteScheduler, UNet2DConditionModel
|
4 |
from huggingface_hub import hf_hub_download
|
5 |
import spaces
|
6 |
from PIL import Image
|
7 |
import requests
|
8 |
from translatepy import Translator
|
9 |
+
import numpy as np
|
10 |
+
import random
|
11 |
+
|
12 |
|
13 |
translator = Translator()
|
14 |
|
15 |
# Constants
|
16 |
model = "Corcelio/mobius"
|
17 |
vae_model = "madebyollin/sdxl-vae-fp16-fix"
|
18 |
+
MAX_SEED = np.iinfo(np.int32).max
|
19 |
|
20 |
CSS = """
|
21 |
.gradio-container {
|
|
|
41 |
|
42 |
# Ensure model and scheduler are initialized in GPU-enabled function
|
43 |
if torch.cuda.is_available():
|
44 |
+
unet = UNet2DConditionModel.from_pretrained(model, subfolder="unet").to("cuda", torch.float16)
|
45 |
+
pipe = StableDiffusionXLPipeline.from_pretrained(model, vae=vae, unet=unet, torch_dtype=torch.float16).to("cuda")
|
46 |
|
47 |
pipe.scheduler = KDPM2AncestralDiscreteScheduler.from_config(pipe.scheduler.config)
|
48 |
|
|
|
54 |
negative="low quality",
|
55 |
width=1024,
|
56 |
height=1024,
|
57 |
+
seed=-1,
|
58 |
+
nums=1,
|
59 |
scale=1.5,
|
60 |
steps=30,
|
61 |
clip=3):
|
62 |
|
63 |
+
if seed == -1:
|
64 |
+
seed = random.randint(0, MAX_SEED)
|
65 |
+
|
66 |
+
generator = torch.Generator().manual_seed(seed)
|
67 |
+
|
68 |
prompt = str(translator.translate(prompt, 'English'))
|
69 |
|
70 |
print(f'prompt:{prompt}')
|
71 |
+
|
72 |
|
73 |
image = pipe(
|
74 |
prompt,
|
|
|
76 |
width=width,
|
77 |
height=height,
|
78 |
guidance_scale=scale,
|
79 |
+
generator = generator,
|
80 |
num_inference_steps=steps,
|
81 |
+
num_images_per_prompt=nums,
|
82 |
clip_skip=clip,
|
83 |
+
).images
|
84 |
+
return image, seed
|
85 |
|
86 |
|
87 |
examples = [
|
|
|
99 |
|
100 |
with gr.Blocks(css=CSS, js=JS, theme="soft") as demo:
|
101 |
gr.HTML("<h1><center>Mobius💠</center></h1>")
|
102 |
+
gr.HTML("<p><center><a href='https://huggingface.co/Corcelio/mobius'>mobius</a> text-to-image generation</center><br><center>Adding default prompts to enhance.</center></p>")
|
103 |
with gr.Group():
|
104 |
with gr.Row():
|
105 |
+
prompt = gr.Textbox(label='Enter Your Prompt(Multi-Languages)', value="best quality, HD, aesthetic", scale=6)
|
106 |
submit = gr.Button(scale=1, variant='primary')
|
107 |
+
img = gr.Gallery(label='Mobius Generated Image',columns = 1, preview=True)
|
108 |
with gr.Accordion("Advanced Options", open=False):
|
109 |
with gr.Row():
|
110 |
+
negative = gr.Textbox(label="Negative prompt", value="low quality, ugly, blurry, poor face, bad anatomy")
|
111 |
with gr.Row():
|
112 |
width = gr.Slider(
|
113 |
label="Width",
|
|
|
123 |
step=8,
|
124 |
value=1024,
|
125 |
)
|
126 |
+
with gr.Row():
|
127 |
+
seed = gr.Slider(
|
128 |
+
label="Seed (-1 Get Random)",
|
129 |
+
minimum=-1,
|
130 |
+
maximum=MAX_SEED,
|
131 |
+
step=1,
|
132 |
+
value=-1,
|
133 |
+
scale=2,
|
134 |
+
)
|
135 |
+
nums = gr.Slider(
|
136 |
+
label="Image Numbers",
|
137 |
+
minimum=1,
|
138 |
+
maximum=4,
|
139 |
+
step=1,
|
140 |
+
value=1,
|
141 |
+
scale=1,
|
142 |
+
)
|
143 |
with gr.Row():
|
144 |
scale = gr.Slider(
|
145 |
label="Guidance",
|
|
|
161 |
maximum=10,
|
162 |
step=1,
|
163 |
value=3,
|
164 |
+
)
|
165 |
gr.Examples(
|
166 |
examples=examples,
|
167 |
inputs=prompt,
|
|
|
171 |
)
|
172 |
|
173 |
prompt.submit(fn=generate_image,
|
174 |
+
inputs=[prompt, negative, width, height, seed, nums, scale, steps, clip],
|
175 |
outputs=img,
|
176 |
)
|
177 |
submit.click(fn=generate_image,
|
178 |
+
inputs=[prompt, negative, width, height, seed, nums, scale, steps, clip],
|
179 |
outputs=img,
|
180 |
)
|
181 |
|