File size: 7,766 Bytes
6a6227f
 
 
 
 
 
 
 
 
6eb1d7d
6a6227f
 
 
7627f49
6a6227f
 
7627f49
 
 
 
21c6c10
7627f49
32b0bc1
6a6227f
 
7627f49
6a6227f
7627f49
6a6227f
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7627f49
6a6227f
 
7627f49
6a6227f
 
 
 
 
 
 
 
 
 
 
 
7627f49
6a6227f
 
56c2873
6a6227f
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7627f49
6a6227f
 
 
 
 
 
 
7627f49
6a6227f
7627f49
6a6227f
 
 
7627f49
6a6227f
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7627f49
6a6227f
 
7627f49
 
 
 
6a6227f
7627f49
 
 
 
 
 
 
 
 
 
 
 
 
 
6a6227f
7627f49
6a6227f
 
 
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
import argparse
import os
from datetime import datetime
import gradio as gr
import numpy as np
import torch
from diffusers.image_processor import VaeImageProcessor
from huggingface_hub import snapshot_download
from PIL import Image
from model.cloth_masker import AutoMasker, vis_mask
from model.pipeline import CatVTONPipeline
from utils import init_weight_dtype, resize_and_crop, resize_and_padding

# ... (rest of your imports and function definitions remain unchanged)

HEADER = """
<p style="text-align: center;">
    <img src="resource/DeXFIT.png" alt="DeX Logo" style="height: 100px;">
</p>
<h1 style="text-align: center; color: #101820;"> DEX FIT Virtual Try-On with Diffusion Models </h1>
<br>
<p style="color: #101820;">· SafetyChecker is set to filter NSFW content, but it may block normal results too. Please adjust the <span style="color: #00685E;">seed</span> for normal outcomes.</p>
"""

def app_gradio():
    with gr.Blocks(title="CatVTON", css="#main {background-color: #F4F4F1;}") as demo:
        gr.Markdown(HEADER)
        
        with gr.Row():
            with gr.Column(scale=1, min_width=350):
                with gr.Row():
                    person_image = gr.ImageEditor(
                        interactive=True, label="Person Image", type="filepath"
                    )

                with gr.Row():
                    with gr.Column(scale=1, min_width=230):
                        cloth_image = gr.Image(
                            interactive=True, label="Condition Image", type="filepath"
                        )
                    with gr.Column(scale=1, min_width=120):
                        gr.Markdown(
                            '<span style="color: #808080; font-size: small;">Two ways to provide Mask:<br>1. Upload the person image and use the `🖌️` above to draw the Mask (higher priority)<br>2. Select the `Try-On Cloth Type` to generate automatically </span>'
                        )
                        cloth_type = gr.Radio(
                            label="Try-On Cloth Type",
                            choices=["upper", "lower", "overall"],
                            value="upper",
                            label_style={"color": "#101820"}
                        )

                submit = gr.Button("Submit", elem_id="submit-button", style={"background-color": "#00685E", "color": "#FFFFFF"})
                gr.Markdown(
                    '<center><span style="color: #FF0000">!!! Click only Once, Wait for Delay !!!</span></center>'
                )
                
                gr.Markdown(
                    '<span style="color: #808080; font-size: small;">Advanced options can adjust details:<br>1. `Inference Step` may enhance details;<br>2. `CFG` is highly correlated with saturation;<br>3. `Random seed` may improve pseudo-shadow.</span>'
                )
                with gr.Accordion("Advanced Options", open=False):
                    num_inference_steps = gr.Slider(
                        label="Inference Step", minimum=10, maximum=100, step=5, value=50
                    )
                    guidance_scale = gr.Slider(
                        label="CFG Strength", minimum=0.0, maximum=7.5, step=0.5, value=2.5
                    )
                    seed = gr.Slider(
                        label="Seed", minimum=-1, maximum=10000, step=1, value=1000
                    )
                    show_type = gr.Radio(
                        label="Show Type",
                        choices=["result only", "input & result", "input & mask & result"],
                        value="input & mask & result",
                    )

            with gr.Column(scale=2, min_width=500):
                result_image = gr.Image(interactive=False, label="Result")
                with gr.Row():
                    root_path = "resource/demo/example"
                    with gr.Column():
                        men_exm = gr.Examples(
                            examples=[
                                os.path.join(root_path, "person", "men", _)
                                for _ in os.listdir(os.path.join(root_path, "person", "men"))
                            ],
                            examples_per_page=4,
                            inputs=person_image,
                            label="Person Examples ①",
                        )
                        women_exm = gr.Examples(
                            examples=[
                                os.path.join(root_path, "person", "women", _)
                                for _ in os.listdir(os.path.join(root_path, "person", "women"))
                            ],
                            examples
                            examples_per_page=4,
                            inputs=person_image,
                            label="Person Examples ②",
                        )
                        gr.Markdown(
                            '<span style="color: #808080; font-size: small;">*Person examples come from the demos of <a href="https://huggingface.co/spaces/levihsu/OOTDiffusion" style="color: #00685E;">OOTDiffusion</a> and <a href="https://www.outfitanyone.org" style="color: #00685E;">OutfitAnyone</a>.</span>'
                        )
                    with gr.Column():
                        condition_upper_exm = gr.Examples(
                            examples=[
                                os.path.join(root_path, "condition", "upper", _)
                                for _ in os.listdir(os.path.join(root_path, "condition", "upper"))
                            ],
                            examples_per_page=4,
                            inputs=cloth_image,
                            label="Condition Upper Examples",
                        )
                        condition_overall_exm = gr.Examples(
                            examples=[
                                os.path.join(root_path, "condition", "overall", _)
                                for _ in os.listdir(os.path.join(root_path, "condition", "overall"))
                            ],
                            examples_per_page=4,
                            inputs=cloth_image,
                            label="Condition Overall Examples",
                        )
                        condition_person_exm = gr.Examples(
                            examples=[
                                os.path.join(root_path, "condition", "person", _)
                                for _ in os.listdir(os.path.join(root_path, "condition", "person"))
                            ],
                            examples_per_page=4,
                            inputs=cloth_image,
                            label="Condition Reference Person Examples",
                        )
                        gr.Markdown(
                            '<span style="color: #808080; font-size: small;">*Condition examples come from the Internet.</span>'
                        )

                # Update the image path change function
                image_path.change(
                    person_example_fn, inputs=image_path, outputs=person_image
                )

                # Connect the submit button to the function
                submit.click(
                    submit_function,
                    [
                        person_image,
                        cloth_image,
                        cloth_type,
                        num_inference_steps,
                        guidance_scale,
                        seed,
                        show_type,
                    ],
                    result_image,
                )

    demo.queue().launch(share=True, show_error=True)

if __name__ == "__main__":
    app_gradio()