Spaces:
Sleeping
Sleeping
Commit
•
7a4c31b
1
Parent(s):
c74d280
update
Browse files
README.md
CHANGED
@@ -4,7 +4,7 @@ emoji: ✏️
|
|
4 |
colorFrom: yellow
|
5 |
colorTo: gray
|
6 |
sdk: gradio
|
7 |
-
sdk_version:
|
8 |
app_file: app.py
|
9 |
pinned: true
|
10 |
license: apache-2.0
|
|
|
4 |
colorFrom: yellow
|
5 |
colorTo: gray
|
6 |
sdk: gradio
|
7 |
+
sdk_version: 3.48.0
|
8 |
app_file: app.py
|
9 |
pinned: true
|
10 |
license: apache-2.0
|
app.py
CHANGED
@@ -11,174 +11,172 @@ import cv2
|
|
11 |
import numpy as np
|
12 |
import os
|
13 |
import torch
|
|
|
|
|
|
|
|
|
|
|
14 |
|
15 |
-
|
16 |
-
|
17 |
-
|
18 |
-
|
19 |
-
|
20 |
-
|
21 |
-
device = "cpu"
|
22 |
-
|
23 |
-
automatic_coloring_pipeline = StableDiffusionReferenceOnlyPipeline.from_pretrained(
|
24 |
-
"AisingioroHao0/stable-diffusion-reference-only-automatic-coloring-0.1.2"
|
25 |
-
).to(device)
|
26 |
-
automatic_coloring_pipeline.scheduler = UniPCMultistepScheduler.from_config(
|
27 |
-
automatic_coloring_pipeline.scheduler.config
|
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 |
-
# Stable Diffusion Reference Only Automatic Coloring 0.1.2\n\n
|
94 |
-
demo for [https://github.com/aihao2000/stable-diffusion-reference-only](https://github.com/aihao2000/stable-diffusion-reference-only)
|
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 |
-
|
147 |
-
|
148 |
-
|
149 |
-
|
150 |
-
|
151 |
-
|
152 |
-
|
153 |
-
|
154 |
-
|
155 |
-
|
156 |
-
|
157 |
-
style_transfer_button = gr.Button("style transfer")
|
158 |
-
style_transfer_button.click(
|
159 |
-
style_transfer,
|
160 |
-
inputs=[
|
161 |
-
prompt_input_compoent,
|
162 |
-
blueprint_input_compoent,
|
163 |
-
num_inference_steps_input_component,
|
164 |
-
],
|
165 |
-
outputs=result_output_component,
|
166 |
-
)
|
167 |
-
with gr.Row():
|
168 |
-
gr.Examples(
|
169 |
-
examples=[
|
170 |
-
[
|
171 |
-
os.path.join(
|
172 |
-
os.path.dirname(__file__), "README.assets", "3x9_prompt.png"
|
173 |
-
),
|
174 |
-
os.path.join(
|
175 |
-
os.path.dirname(__file__), "README.assets", "3x9_blueprint.png"
|
176 |
-
),
|
177 |
-
],
|
178 |
],
|
179 |
-
inputs=[prompt_input_compoent, blueprint_input_compoent],
|
180 |
outputs=result_output_component,
|
181 |
-
fn=lambda x, y: None,
|
182 |
-
cache_examples=True,
|
183 |
)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
184 |
demo.queue(max_size=10).launch()
|
|
|
11 |
import numpy as np
|
12 |
import os
|
13 |
import torch
|
14 |
+
print(f"Is CUDA available: {torch.cuda.is_available()}")
|
15 |
+
if torch.cuda.is_available():
|
16 |
+
device = "cuda"
|
17 |
+
else:
|
18 |
+
device = "cpu"
|
19 |
|
20 |
+
automatic_coloring_pipeline = StableDiffusionReferenceOnlyPipeline.from_pretrained(
|
21 |
+
"AisingioroHao0/stable-diffusion-reference-only-automatic-coloring-0.1.2"
|
22 |
+
).to(device)
|
23 |
+
automatic_coloring_pipeline.scheduler = UniPCMultistepScheduler.from_config(
|
24 |
+
automatic_coloring_pipeline.scheduler.config
|
25 |
+
)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
26 |
|
27 |
+
segment_model = get_anime_segmentation_model(
|
28 |
+
model_path=huggingface_hub.hf_hub_download("skytnt/anime-seg", "isnetis.ckpt")
|
29 |
+
).to(device)
|
30 |
|
31 |
+
def character_segment(img):
|
32 |
+
if img is None:
|
33 |
+
return None
|
34 |
+
img = anime_character_segment(segment_model, img)
|
35 |
+
img = cv2.cvtColor(img, cv2.COLOR_RGBA2RGB)
|
36 |
+
return img
|
37 |
|
38 |
+
def color_inversion(img):
|
39 |
+
if img is None:
|
40 |
+
return None
|
41 |
+
return 255 - img
|
42 |
|
43 |
|
44 |
+
def get_line_art(img):
|
45 |
+
if img is None:
|
46 |
+
return None
|
47 |
+
img = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
|
48 |
+
img = cv2.adaptiveThreshold(
|
49 |
+
img,
|
50 |
+
255,
|
51 |
+
cv2.ADAPTIVE_THRESH_MEAN_C,
|
52 |
+
cv2.THRESH_BINARY,
|
53 |
+
blockSize=5,
|
54 |
+
C=7,
|
55 |
+
)
|
56 |
+
img = cv2.cvtColor(img, cv2.COLOR_GRAY2RGB)
|
57 |
+
return img
|
58 |
|
59 |
|
60 |
+
def inference(prompt, blueprint, num_inference_steps):
|
61 |
+
if prompt is None or blueprint is None:
|
62 |
+
return None
|
63 |
+
return np.array(
|
64 |
+
automatic_coloring_pipeline(
|
65 |
+
prompt=Image.fromarray(prompt),
|
66 |
+
blueprint=Image.fromarray(blueprint),
|
67 |
+
num_inference_steps=num_inference_steps,
|
68 |
+
).images[0]
|
69 |
+
)
|
70 |
|
71 |
|
72 |
+
def automatic_coloring(prompt, blueprint, num_inference_steps):
|
73 |
+
if prompt is None or blueprint is None:
|
74 |
+
return None
|
75 |
+
blueprint = color_inversion(blueprint)
|
76 |
+
return inference(prompt, blueprint, num_inference_steps)
|
77 |
|
78 |
|
79 |
+
def style_transfer(prompt, blueprint, num_inference_steps):
|
80 |
+
if prompt is None or blueprint is None:
|
81 |
+
return None
|
82 |
+
prompt = character_segment(prompt)
|
83 |
+
blueprint = character_segment(blueprint)
|
84 |
+
blueprint = get_line_art(blueprint)
|
85 |
+
blueprint = color_inversion(blueprint)
|
86 |
+
return inference(prompt, blueprint, num_inference_steps)
|
87 |
+
with gr.Blocks() as demo:
|
88 |
+
gr.Markdown(
|
|
|
|
|
|
|
89 |
"""
|
90 |
+
# Stable Diffusion Reference Only Automatic Coloring 0.1.2\n\n
|
91 |
+
demo for [https://github.com/aihao2000/stable-diffusion-reference-only](https://github.com/aihao2000/stable-diffusion-reference-only)
|
92 |
+
"""
|
93 |
+
)
|
94 |
+
with gr.Row():
|
95 |
+
with gr.Column():
|
96 |
+
prompt_input_compoent = gr.Image(shape=(512, 512), label="prompt")
|
97 |
+
prompt_character_segment_button = gr.Button(
|
98 |
+
"character segment",
|
99 |
+
)
|
100 |
+
prompt_character_segment_button.click(
|
101 |
+
character_segment,
|
102 |
+
inputs=prompt_input_compoent,
|
103 |
+
outputs=prompt_input_compoent,
|
104 |
+
)
|
105 |
+
with gr.Column():
|
106 |
+
blueprint_input_compoent = gr.Image(shape=(512, 512), label="blueprint")
|
107 |
+
blueprint_character_segment_button = gr.Button("character segment")
|
108 |
+
blueprint_character_segment_button.click(
|
109 |
+
character_segment,
|
110 |
+
inputs=blueprint_input_compoent,
|
111 |
+
outputs=blueprint_input_compoent,
|
112 |
+
)
|
113 |
+
get_line_art_button = gr.Button(
|
114 |
+
"get line art",
|
115 |
+
)
|
116 |
+
get_line_art_button.click(
|
117 |
+
get_line_art,
|
118 |
+
inputs=blueprint_input_compoent,
|
119 |
+
outputs=blueprint_input_compoent,
|
120 |
+
)
|
121 |
+
color_inversion_button = gr.Button(
|
122 |
+
"color inversion",
|
123 |
+
)
|
124 |
+
color_inversion_button.click(
|
125 |
+
color_inversion,
|
126 |
+
inputs=blueprint_input_compoent,
|
127 |
+
outputs=blueprint_input_compoent,
|
128 |
+
)
|
129 |
+
with gr.Column():
|
130 |
+
result_output_component = gr.Image(shape=(512, 512), label="result")
|
131 |
+
num_inference_steps_input_component = gr.Number(
|
132 |
+
20, label="num inference steps", minimum=1, maximum=1000, step=1
|
133 |
+
)
|
134 |
+
inference_button = gr.Button("inference")
|
135 |
+
inference_button.click(
|
136 |
+
inference,
|
137 |
+
inputs=[
|
138 |
+
prompt_input_compoent,
|
139 |
+
blueprint_input_compoent,
|
140 |
+
num_inference_steps_input_component,
|
141 |
+
],
|
142 |
+
outputs=result_output_component,
|
143 |
+
)
|
144 |
+
automatic_coloring_button = gr.Button("automatic coloring")
|
145 |
+
automatic_coloring_button.click(
|
146 |
+
automatic_coloring,
|
147 |
+
inputs=[
|
148 |
+
prompt_input_compoent,
|
149 |
+
blueprint_input_compoent,
|
150 |
+
num_inference_steps_input_component,
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
151 |
],
|
|
|
152 |
outputs=result_output_component,
|
|
|
|
|
153 |
)
|
154 |
+
style_transfer_button = gr.Button("style transfer")
|
155 |
+
style_transfer_button.click(
|
156 |
+
style_transfer,
|
157 |
+
inputs=[
|
158 |
+
prompt_input_compoent,
|
159 |
+
blueprint_input_compoent,
|
160 |
+
num_inference_steps_input_component,
|
161 |
+
],
|
162 |
+
outputs=result_output_component,
|
163 |
+
)
|
164 |
+
with gr.Row():
|
165 |
+
gr.Examples(
|
166 |
+
examples=[
|
167 |
+
[
|
168 |
+
os.path.join(
|
169 |
+
os.path.dirname(__file__), "README.assets", "3x9_prompt.png"
|
170 |
+
),
|
171 |
+
os.path.join(
|
172 |
+
os.path.dirname(__file__), "README.assets", "3x9_blueprint.png"
|
173 |
+
),
|
174 |
+
],
|
175 |
+
],
|
176 |
+
inputs=[prompt_input_compoent, blueprint_input_compoent],
|
177 |
+
outputs=result_output_component,
|
178 |
+
fn=lambda x, y: None,
|
179 |
+
cache_examples=True,
|
180 |
+
)
|
181 |
+
if __name__ == "__main__":
|
182 |
demo.queue(max_size=10).launch()
|