Spaces:
Running
on
CPU Upgrade
Running
on
CPU Upgrade
File size: 6,815 Bytes
f69cd15 eaa8689 f69cd15 1ecb321 eaa8689 5cbc9b1 6af3026 f8801dc 1ecb321 eaa8689 f8801dc dbe8337 0805db6 eaa8689 8c2fca3 eaa8689 8c2fca3 eaa8689 8654223 f26d335 8654223 49eabb6 6803e6c 3976754 49eabb6 6803e6c 6af3026 b453f9d 0c1a8d3 4ad0645 3976754 4ad0645 0c1a8d3 b453f9d 0c1a8d3 f8801dc 6af3026 b453f9d 1ecb321 534e5bb f69cd15 1ecb321 f69cd15 4dd113c 01db67e 4dd113c f69cd15 1ecb321 4dd113c f69cd15 4db4e89 a9ba2aa 4db4e89 f69cd15 1ecb321 f69cd15 1ecb321 fc8d8be f69cd15 01db67e bd8fedc ad30fcb bd8fedc ad30fcb bd8fedc ad30fcb 4311e2a f69cd15 1e19884 f69cd15 1ecb321 01db67e 4311e2a f69cd15 1e19884 cc17840 01db67e fa6131f b453f9d 7de6d0d 534e5bb 7de6d0d fa6131f 7de6d0d 1ecb321 002bcad 1ecb321 4db4e89 537454a d562784 4db4e89 68b15ec e73c140 4db4e89 a9ba2aa 5900e16 4db4e89 d77e663 eace6f5 002bcad |
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 |
import os
import cv2
from PIL import Image
import gradio as gr
import numpy as np
import random
import base64
import requests
import json
import time
def start_tryon(person_img, garment_img, seed, randomize_seed):
start_time = time.time()
if person_img is None or garment_img is None:
return None, None, "Empty image"
if randomize_seed:
seed = random.randint(0, MAX_SEED)
encoded_person_img = cv2.imencode('.jpg', cv2.cvtColor(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.cvtColor(garment_img, cv2.COLOR_RGB2BGR))[1].tobytes()
encoded_garment_img = base64.b64encode(encoded_garment_img).decode('utf-8')
url = "http://" + os.environ['tryon_url']
token = os.environ['token']
cookie = os.environ['Cookie']
referer = os.environ['referer']
http_proxy = os.environ['http_proxy']
headers = {'Content-Type': 'application/json', 'token': token, 'Cookie': cookie, 'referer': referer}
data = {
"clothImage": encoded_garment_img,
"humanImage": encoded_person_img,
"seed": seed
}
result_img = None
try:
session = requests.Session()
session.proxies = {"http": http_proxy}
response = session.post(url, headers=headers, data=json.dumps(data), timeout=60)
print("response code", response.status_code)
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.cvtColor(result_img, cv2.COLOR_RGB2BGR)
info = "Success"
else:
info = "Try again latter"
else:
print(response.text)
info = "URL error, pleace contact the admin"
except requests.exceptions.ReadTimeout:
print("timeout")
info = "Too many users, please try again later"
except Exception as err:
print(f"其他错误: {err}")
info = "Error, pleace contact the admin"
end_time = time.time()
print(f"time used: {end_time-start_time}")
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: 430px;
}
#col-mid {
margin: 0 auto;
max-width: 430px;
}
#col-right {
margin: 0 auto;
max-width: 430px;
}
#col-showcase {
margin: 0 auto;
max-width: 1100px;
}
#button {
color: blue;
}
"""
def load_description(fp):
with open(fp, 'r', encoding='utf-8') as f:
content = f.read()
return content
def change_imgs(image1, image2):
return image1, image2
with gr.Blocks(css=css) as Tryon:
gr.HTML(load_description("assets/title.md"))
with gr.Row():
with gr.Column(elem_id = "col-left"):
gr.HTML("""
<div style="display: flex; justify-content: center; align-items: center; text-align: center;">
<div>
<h2>Step 1. Upload a person image. ⬇️</h2>
</div>
</div>
""")
with gr.Column(elem_id = "col-mid"):
gr.HTML("""
<div style="display: flex; justify-content: center; align-items: center; text-align: center;">
<div>
<h2>Step 2. Upload a garment image. ⬇️</h2>
</div>
</div>
""")
with gr.Column(elem_id = "col-right"):
gr.HTML("""
<div style="display: flex; justify-content: center; align-items: center; text-align: center;">
<div>
<h2>Step 3. Press the “Run” button to get try-on results.</h2>
</div>
</div>
""")
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=12,
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=12,
examples=garm_list_path
)
with gr.Column(elem_id = "col-right"):
image_out = gr.Image(label="Result", show_share_button=False)
with gr.Row():
seed = gr.Slider(
label="Seed",
minimum=0,
maximum=MAX_SEED,
step=1,
value=0,
)
randomize_seed = gr.Checkbox(label="Random seed", value=True)
with gr.Row():
seed_used = gr.Number(label="Seed used")
result_info = gr.Text(label="Response")
try_button = gr.Button(value="Run", elem_id="button")
try_button.click(fn=start_tryon, inputs=[imgs, garm_img, seed, randomize_seed], outputs=[image_out, seed_used, result_info], api_name='tryon',concurrency_limit=10)
with gr.Column(elem_id = "col-showcase"):
gr.HTML("""
<div style="display: flex; justify-content: center; align-items: center; text-align: center;">
<div>
<h2>Virtual try-on examples in pairs of person and garment images.</h2>
</div>
</div>
""")
show_case = gr.Examples(
examples=[
["assets/examples/model2.png", "assets/examples/garment2.png", "assets/examples/result2.png"],
["assets/examples/model3.png", "assets/examples/garment3.png", "assets/examples/result3.png"],
["assets/examples/model1.png", "assets/examples/garment1.png", "assets/examples/result1.png"],
],
inputs=[imgs, garm_img, image_out],
label=None
)
# ip = requests.get('http://ifconfig.me/ip', timeout=1).text.strip()
# print("ip address", ip)
Tryon.queue(max_size = 20).launch(max_threads = 5)
|