File size: 10,011 Bytes
765bd33
 
 
 
 
 
a01b0e0
765bd33
 
 
 
 
 
a01b0e0
765bd33
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0f13924
765bd33
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
419cfa8
765bd33
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
f6f39d8
765bd33
1e4fc14
765bd33
 
 
 
 
 
 
 
 
 
 
 
 
 
c56b9f1
765bd33
 
 
 
 
 
 
 
a01b0e0
7ff4bb1
765bd33
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
675c01e
765bd33
 
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
183
184
185
186
187
188
189
190
191
192
import os
import cv2
import numpy as np
import json
import random
from PIL import Image, ImageDraw, ImageFont
import asyncio

import requests
import base64
import gradio as gr
# from IPython import embed

machine_number = 0
model = os.path.join(os.path.dirname(__file__), "models/eva/Eva_0.png")

MODEL_MAP = {
    "AI Model Rouyan_0": 'models/rouyan_new/Rouyan_0.png',
    "AI Model Rouyan_1": 'models/rouyan_new/Rouyan_1.png',
    "AI Model Rouyan_2": 'models/rouyan_new/Rouyan_2.png',
    "AI Model Eva_0": 'models/eva/Eva_0.png',
    "AI Model Eva_1": 'models/eva/Eva_1.png',
    "AI Model Simon_0": 'models/simon_online/Simon_0.png',
    "AI Model Simon_1": 'models/simon_online/Simon_1.png',
    "AI Model Xuanxuan_0": 'models/xiaoxuan_online/Xuanxuan_0.png',
    "AI Model Xuanxuan_1": 'models/xiaoxuan_online/Xuanxuan_1.png',
    "AI Model Xuanxuan_2": 'models/xiaoxuan_online/Xuanxuan_2.png',
    "AI Model Yaqi_0": 'models/yaqi/Yaqi_0.png',
    "AI Model Yaqi_1": 'models/yaqi/Yaqi_1.png',
    "AI Model Yaqi_2": 'models/yaqi/Yaqi_2.png',
    "AI Model Yaqi_3": 'models/yaqi/Yaqi_3.png',
    "AI Model Yifeng_0": 'models/yifeng_online/Yifeng_0.png',
    "AI Model Yifeng_1": 'models/yifeng_online/Yifeng_1.png',
    "AI Model Yifeng_2": 'models/yifeng_online/Yifeng_2.png',
    "AI Model Yifeng_3": 'models/yifeng_online/Yifeng_3.png',
}

def add_waterprint(img):

    h, w, _ = img.shape
    img = cv2.putText(img, 'Powered by OutfitAnyone', (int(0.3*w), h-20), cv2.FONT_HERSHEY_PLAIN, 2, (128, 128, 128), 2, cv2.LINE_AA)

    return img


def get_tryon_result(model_name, garment1, garment2, seed=1234):

    # model_name = "AI Model " + model_name.split("\\")[-1].split(".")[0] # windows
    model_name = "AI Model " + model_name.split("/")[-1].split(".")[0] # linux
    print(model_name)

    encoded_garment1 = cv2.imencode('.jpg', garment1)[1].tobytes()
    encoded_garment1 = base64.b64encode(encoded_garment1).decode('utf-8')

    if garment2 is not None:
        encoded_garment2 = cv2.imencode('.jpg', garment2)[1].tobytes()
        encoded_garment2 = base64.b64encode(encoded_garment2).decode('utf-8')
    else:
        encoded_garment2 = ''

    url = os.environ['OA_IP_ADDRESS']
    headers = {'Content-Type': 'application/json'}
    seed = random.randint(0, 1222222222)
    data = {
        "garment1": encoded_garment1,
        "garment2": encoded_garment2,
        "model_name": model_name,
        "seed": seed
    }
    response = requests.post(url, headers=headers, data=json.dumps(data))
    print("response code", response.status_code)
    if response.status_code == 200:
        result = response.json()
        result = base64.b64decode(result['images'][0])
        result_np = np.frombuffer(result, np.uint8)
        result_img = cv2.imdecode(result_np, cv2.IMREAD_UNCHANGED)
    else:
        print('server error!')

    
    final_img = add_waterprint(result_img)

    return final_img



with gr.Blocks(css = ".output-image, .input-image, .image-preview {height: 400px !important} ") as demo:
    # gr.Markdown("# Outfit Anyone v0.9")
    gr.HTML(
        """
        <div style="display: flex; justify-content: center; align-items: center; text-align: center;">
        <a href="https://github.com/HumanAIGC/OutfitAnyone" style="margin-right: 20px; text-decoration: none; display: flex; align-items: center;">
        </a>
        <div>
            <h1 >Outfit Anyone: Ultra-high quality virtual try-on for Any Clothing and Any Person</h1>
            <h4 >v0.9</h4>
            <h5 style="margin: 0;">If you like our project, please give us a star  on Github to stay updated with the latest developments.</h5>
            <div style="display: flex; justify-content: center; align-items: center; text-align: center;>
                <a href="https://github.com/HumanAIGC/OutfitAnyone"><img src="https://img.shields.io/badge/Arxiv-0000.00000-red"></a>
                <a href='https://humanaigc.github.io/outfit-anyone/'><img src='https://img.shields.io/badge/Project_Page-OutfitAnyone-green' alt='Project Page'></a>
                <a href='https://github.com/HumanAIGC/OutfitAnyone'><img src='https://img.shields.io/badge/Github-Repo-blue'></a>
            </div>
        </div>
        </div>
        """)
    with gr.Row():
        with gr.Column():
            init_image = gr.Image(sources='clipboard', type="filepath", label="model", value=model)
            example = gr.Examples(inputs=init_image,
                                  examples_per_page=4,
                                  examples=[os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Rouyan_0')),
                                            os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Rouyan_2')),
                                            os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Eva_0')),
                                            os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Simon_1')),
                                            os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Eva_1')),
                                            os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Simon_0')),
                                            os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Xuanxuan_0')),
                                            os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Xuanxuan_2')),
                                            os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Yaqi_1')),
                                            os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Yifeng_0')),
                                            os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Yifeng_3')),
                                            os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Rouyan_1')),
                                            os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Yifeng_2')),
                                            os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Yaqi_0')),
                                            ])
        with gr.Column():
            gr.HTML(
                """
                <div style="display: flex; justify-content: center; align-items: center; text-align: center;">
                <div>
                    <h3>Models are fixed and cannot be uploaded or modified; we only support users uploading their own garments.</h3>
                    <h4 style="margin: 0;">For a one-piece dress or coat, you only need to upload the image to the 'top garment' section and leave the 'lower garment' section empty.</h4>
                </div>
                </div>
                """)
            with gr.Row():
                garment_top = gr.Image(sources='upload', type="numpy", label="top garment")
                example_top = gr.Examples(inputs=garment_top,
                                          examples_per_page=5,
                                          examples=[os.path.join(os.path.dirname(__file__), "garments/top222.JPG"),
                                                    os.path.join(os.path.dirname(__file__), "garments/top5.png"),
                                                    os.path.join(os.path.dirname(__file__), "garments/top333.png"),
                                                    os.path.join(os.path.dirname(__file__), "garments/dress1.png"),
                                                    os.path.join(os.path.dirname(__file__), "garments/dress2.png"),
                                                            ])
                garment_down = gr.Image(sources='upload', type="numpy", label="lower garment")
                example_down = gr.Examples(inputs=garment_down,
                                           examples_per_page=5,
                                           examples=[os.path.join(os.path.dirname(__file__), "garments/bottom1.png"),
                                                     os.path.join(os.path.dirname(__file__), "garments/bottom2.PNG"),
                                                     os.path.join(os.path.dirname(__file__), "garments/bottom3.JPG"),
                                                     os.path.join(os.path.dirname(__file__), "garments/bottom4.PNG"),
                                                     os.path.join(os.path.dirname(__file__), "garments/bottom5.png"),
                                                            ])

            run_button = gr.Button(value="Run")
        with gr.Column():
            gallery = gr.Image()

            run_button.click(fn=get_tryon_result, 
                             inputs=[
                                    init_image,
                                    garment_top,
                                    garment_down,
                                    ], 
                             outputs=[gallery],
                             concurrency_limit=4)
        

    # Examples
    gr.Markdown("## Examples")
    with gr.Row():
        reference_image1  = gr.Image(label="model", scale=1, value="examples/basemodel.png")
        reference_image2  = gr.Image(label="garment", scale=1, value="examples/garment1.jpg")
        reference_image3  = gr.Image(label="result", scale=1, value="examples/result1.png")
    gr.Examples(
        examples=[
            ["examples/basemodel.png", "examples/garment1.png", "examples/result1.png"],
            ["examples/basemodel.png", "examples/garment2.png", "examples/result2.png"],
            ["examples/basemodel.png", "examples/garment3.png", "examples/result3.png"],
        ],
        inputs=[reference_image1, reference_image2, reference_image3],
        label=None,
    )

if __name__ == "__main__":
    ip = requests.get('http://ifconfig.me/ip', timeout=1).text.strip()
    print("ip address alibaba", ip)
    demo.queue(max_size=10)
    demo.launch()