File size: 6,049 Bytes
4de728a
 
 
 
 
 
 
 
 
 
 
 
4428c33
4de728a
 
4428c33
4de728a
 
 
 
 
 
4428c33
4de728a
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
bc2311a
4de728a
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
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
94
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
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
import huggingface_hub
import gradio as gr
from stable_diffusion_reference_only.pipelines.stable_diffusion_reference_only_pipeline import (
    StableDiffusionReferenceOnlyPipeline,
)
import anime_segmentation
from diffusers.schedulers import UniPCMultistepScheduler
from PIL import Image
import cv2
import numpy as np
import os

device = "cpu"
automatic_coloring_pipeline = StableDiffusionReferenceOnlyPipeline.from_pretrained(
    "AisingioroHao0/stable-diffusion-reference-only-automatic-coloring-0.1.2"
).to(device)
automatic_coloring_pipeline.scheduler = UniPCMultistepScheduler.from_config(
    automatic_coloring_pipeline.scheduler.config
)

segment_model = anime_segmentation.get_model(
    model_path=huggingface_hub.hf_hub_download("skytnt/anime-seg", "isnetis.ckpt")
).to(device)


def character_segment(img):
    if img is None:
        return None
    img = anime_segmentation.character_segment(segment_model, img)
    img = cv2.cvtColor(img, cv2.COLOR_RGBA2RGB)
    return img


def color_inversion(img):
    if img is None:
        return None
    return 255 - img


def get_line_art(img):
    if img is None:
        return None
    img = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
    img = cv2.adaptiveThreshold(
        img,
        255,
        cv2.ADAPTIVE_THRESH_MEAN_C,
        cv2.THRESH_BINARY,
        blockSize=5,
        C=7,
    )
    img = cv2.cvtColor(img, cv2.COLOR_GRAY2RGB)
    return img


def inference(prompt, blueprint, num_inference_steps):
    if prompt is None or blueprint is None:
        return None
    return np.array(
        automatic_coloring_pipeline(
            prompt=Image.fromarray(prompt),
            blueprint=Image.fromarray(blueprint),
            num_inference_steps=num_inference_steps,
        ).images[0]
    )


def automatic_coloring(prompt, blueprint, num_inference_steps):
    if prompt is None or blueprint is None:
        return None
    blueprint = color_inversion(blueprint)
    return inference(prompt, blueprint, num_inference_steps)


def style_transfer(prompt, blueprint, num_inference_steps):
    if prompt is None or blueprint is None:
        return None
    prompt = character_segment(prompt)
    blueprint = character_segment(blueprint)
    blueprint = get_line_art(blueprint)
    blueprint = color_inversion(blueprint)
    return inference(prompt, blueprint, num_inference_steps)


with gr.Blocks() as demo:
    gr.Markdown(
        """
    # Stable Diffusion Reference Only Automatic Coloring 0.1.2\n\n
    demo for [https://github.com/aihao2000/stable-diffusion-reference-only](https://github.com/aihao2000/stable-diffusion-reference-only)
    """
    )
    with gr.Row():
        with gr.Column():
            prompt_input_compoent = gr.Image(shape=(512, 512), label="prompt")
            prompt_character_segment_button = gr.Button(
                "character segment",
            )
            prompt_character_segment_button.click(
                character_segment,
                inputs=prompt_input_compoent,
                outputs=prompt_input_compoent,
            )
        with gr.Column():
            blueprint_input_compoent = gr.Image(shape=(512, 512), label="blueprint")
            blueprint_character_segment_button = gr.Button("character segment")
            blueprint_character_segment_button.click(
                character_segment,
                inputs=blueprint_input_compoent,
                outputs=blueprint_input_compoent,
            )
            get_line_art_button = gr.Button(
                "get line art",
            )
            get_line_art_button.click(
                get_line_art,
                inputs=blueprint_input_compoent,
                outputs=blueprint_input_compoent,
            )
            color_inversion_button = gr.Button(
                "color inversion",
            )
            color_inversion_button.click(
                color_inversion,
                inputs=blueprint_input_compoent,
                outputs=blueprint_input_compoent,
            )
        with gr.Column():
            result_output_component = gr.Image(shape=(512, 512), label="result")
            num_inference_steps_input_component = gr.Number(
                20, label="num inference steps", minimum=1, maximum=1000, step=1
            )
            inference_button = gr.Button("inference")
            inference_button.click(
                inference,
                inputs=[
                    prompt_input_compoent,
                    blueprint_input_compoent,
                    num_inference_steps_input_component,
                ],
                outputs=result_output_component,
            )
            automatic_coloring_button = gr.Button("automatic coloring")
            automatic_coloring_button.click(
                automatic_coloring,
                inputs=[
                    prompt_input_compoent,
                    blueprint_input_compoent,
                    num_inference_steps_input_component,
                ],
                outputs=result_output_component,
            )
            style_transfer_button = gr.Button("style transfer")
            style_transfer_button.click(
                style_transfer,
                inputs=[
                    prompt_input_compoent,
                    blueprint_input_compoent,
                    num_inference_steps_input_component,
                ],
                outputs=result_output_component,
            )
    with gr.Row():
        gr.Examples(
            examples=[
                [
                    os.path.join(
                        os.path.dirname(__file__), "README.assets", "3x9_prompt.png"
                    ),
                    os.path.join(
                        os.path.dirname(__file__), "README.assets", "3x9_blueprint.png"
                    ),
                ],
            ],
            inputs=[prompt_input_compoent, blueprint_input_compoent],
            outputs=result_output_component,
            fn=lambda x, y: None,
            cache_examples=True,
        )


demo.launch()