File size: 4,314 Bytes
f69cd15
eaa8689
f69cd15
1ecb321
 
 
eaa8689
5cbc9b1
6af3026
1ecb321
 
eaa8689
 
 
5479e73
eaa8689
5479e73
eaa8689
8654223
3ea9ed2
8654223
82b1749
5e35140
82b1749
6af3026
 
 
 
 
 
5699bf9
 
b453f9d
5699bf9
5e35140
f6e997e
5e35140
 
 
 
5479e73
b453f9d
 
 
 
 
6af3026
b453f9d
1ecb321
534e5bb
 
 
 
f69cd15
 
 
 
 
1ecb321
 
f69cd15
 
5e35140
01db67e
 
 
5e35140
f69cd15
 
1ecb321
e08a1e8
f69cd15
 
 
1ecb321
 
 
f69cd15
 
 
 
1ecb321
f69cd15
 
 
01db67e
4311e2a
f69cd15
 
 
 
 
1ecb321
01db67e
4311e2a
f69cd15
 
fe775c6
f69cd15
01db67e
fe775c6
b453f9d
 
 
fe775c6
1ecb321
f69cd15
 
 
534e5bb
 
 
 
 
 
 
 
1ecb321
b453f9d
1ecb321
efa1709
 
 
 
 
5cbc9b1
8654223
f69cd15
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
import os
import cv2
from PIL import Image
import gradio as gr
import numpy as np
import random
import base64
import requests
import json


def start_tryon(person_img, garment_img, seed, randomize_seed):
    if randomize_seed:
        seed = random.randint(0, MAX_SEED)
    encoded_person_img = cv2.imencode('.jpg', cv2.cvtColors(person_img, cv2.COLOR_RGB2BGR))[1].tobytes()
    encoded_person_img = base64.b64encode(encoded_person_img).decode('utf-8')
    encoded_garment_img = cv2.imencode('.jpg', cv2.cvtColors(garment_img, cv2.COLOR_RGB2BGR))[1].tobytes()
    encoded_garment_img = base64.b64encode(encoded_garment_img).decode('utf-8')

    url = "https://" + os.environ['tryon_url']
    token = os.environ['token']
    cookie = os.environ['Cookie']
    
    headers = {'Content-Type': 'application/json', 'token': token, 'Cookie': cookie}
    data = {
        "clothImage": encoded_garment_img,
        "humanImage": encoded_person_img,
        "seed": seed
    }

    response = requests.post(url, headers=headers, data=json.dumps(data))
    print("response code", response.status_code)
    result_img = None
    if response.status_code == 200:
        result = response.json()['result']
        status = result['status']
        if status == "success":
            result = base64.b64decode(result['result'])
            result_np = np.frombuffer(result, np.uint8)
            result_img = cv2.imdecode(result_np, cv2.IMREAD_UNCHANGED)
            result_img = cv2.cvtColors(result_img, cv2.COLOR_RGB2BGR)
            info = "Success"
        else:
            info = "Try again latter"
    else:
        info = "URL error"

    return result_img, seed, info

MAX_SEED = 999999

example_path = os.path.join(os.path.dirname(__file__), 'assets')

garm_list = os.listdir(os.path.join(example_path,"cloth"))
garm_list_path = [os.path.join(example_path,"cloth",garm) for garm in garm_list]

human_list = os.listdir(os.path.join(example_path,"human"))
human_list_path = [os.path.join(example_path,"human",human) for human in human_list]

css="""
#col-left {
    margin: 0 auto;
    max-width: 380px;
}
#col-mid {
    margin: 0 auto;
    max-width: 380px;
}
#col-right {
    margin: 0 auto;
    max-width: 520px;
}
#button {
    color: blue;
}
"""

def load_description(fp):
    with open(fp, 'r', encoding='utf-8') as f:
        content = f.read()
    return content

with gr.Blocks(css=css) as Tryon:
    gr.HTML(load_description("assets/title.md"))
    with gr.Row():
        with gr.Column(elem_id = "col-left"):
            imgs = gr.Image(label="Person image", sources='upload', type="numpy")
            # category = gr.Dropdown(label="Garment category", choices=['upper_body', 'lower_body', 'dresses'],  value="upper_body")
            example = gr.Examples(
                inputs=imgs,
                examples_per_page=10,
                examples=human_list_path
            )
        with gr.Column(elem_id = "col-mid"):
            garm_img = gr.Image(label="Garment image", sources='upload', type="numpy")
            example = gr.Examples(
                inputs=garm_img,
                examples_per_page=10,
                examples=garm_list_path)
        with gr.Column(elem_id = "col-right"):
            image_out = gr.Image(label="Output", show_share_button=False)
            with gr.Row():
                seed_used = gr.Number(label="Seed Used")
                result_info = gr.Text(label="Info")
            try_button = gr.Button(value="Try-on", elem_id="button")


    with gr.Column():
        with gr.Accordion(label="Advanced Settings", open=False):
            seed = gr.Slider(
                    label="Seed",
                    minimum=0,
                    maximum=MAX_SEED,
                    step=1,
                    value=0,
                )
            randomize_seed = gr.Checkbox(label="Randomize seed", value=True)

    try_button.click(fn=start_tryon, inputs=[imgs, garm_img, seed, randomize_seed], outputs=[image_out, seed_used, result_info], api_name='tryon')

    # with gr.Row(label="Examples"):
    #     with gr.Column(elem_id = "col-left"):
    #         imgs = gr.Image(label="Person image", sources='upload', type="numpy")


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