Spaces:
Runtime error
Runtime error
My-AI-Projects
commited on
Commit
•
1d5e328
1
Parent(s):
b060b0d
Upload app.py
Browse files
app.py
ADDED
@@ -0,0 +1,275 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import os
|
2 |
+
import cv2
|
3 |
+
import gradio as gr
|
4 |
+
import numpy as np
|
5 |
+
import random
|
6 |
+
import base64
|
7 |
+
import requests
|
8 |
+
import json
|
9 |
+
import time
|
10 |
+
|
11 |
+
|
12 |
+
def tryon(person_img, garment_img, seed, randomize_seed):
|
13 |
+
post_start_time = time.time()
|
14 |
+
if person_img is None or garment_img is None:
|
15 |
+
gr.Warning("Empty image")
|
16 |
+
return None, None, "Empty image"
|
17 |
+
if randomize_seed:
|
18 |
+
seed = random.randint(0, MAX_SEED)
|
19 |
+
encoded_person_img = cv2.imencode('.jpg', cv2.cvtColor(person_img, cv2.COLOR_RGB2BGR))[1].tobytes()
|
20 |
+
encoded_person_img = base64.b64encode(encoded_person_img).decode('utf-8')
|
21 |
+
encoded_garment_img = cv2.imencode('.jpg', cv2.cvtColor(garment_img, cv2.COLOR_RGB2BGR))[1].tobytes()
|
22 |
+
encoded_garment_img = base64.b64encode(encoded_garment_img).decode('utf-8')
|
23 |
+
|
24 |
+
url = "http://" + os.environ['tryon_url'] + "Submit"
|
25 |
+
token = os.environ['token']
|
26 |
+
cookie = os.environ['Cookie']
|
27 |
+
referer = os.environ['referer']
|
28 |
+
headers = {'Content-Type': 'application/json', 'token': token, 'Cookie': cookie, 'referer': referer}
|
29 |
+
data = {
|
30 |
+
"clothImage": encoded_garment_img,
|
31 |
+
"humanImage": encoded_person_img,
|
32 |
+
"seed": seed
|
33 |
+
}
|
34 |
+
try:
|
35 |
+
response = requests.post(url, headers=headers, data=json.dumps(data), timeout=50)
|
36 |
+
# print("post response code", response.status_code)
|
37 |
+
if response.status_code == 200:
|
38 |
+
result = response.json()['result']
|
39 |
+
status = result['status']
|
40 |
+
if status == "success":
|
41 |
+
uuid = result['result']
|
42 |
+
# print(uuid)
|
43 |
+
except Exception as err:
|
44 |
+
print(f"Post Exception Error: {err}")
|
45 |
+
raise gr.Error("Too many users, please try again later")
|
46 |
+
post_end_time = time.time()
|
47 |
+
print(f"post time used: {post_end_time-post_start_time}")
|
48 |
+
|
49 |
+
get_start_time =time.time()
|
50 |
+
time.sleep(9)
|
51 |
+
Max_Retry = 12
|
52 |
+
result_img = None
|
53 |
+
info = ""
|
54 |
+
err_log = ""
|
55 |
+
for i in range(Max_Retry):
|
56 |
+
try:
|
57 |
+
url = "http://" + os.environ['tryon_url'] + "Query?taskId=" + uuid
|
58 |
+
response = requests.get(url, headers=headers, timeout=20)
|
59 |
+
# print("get response code", response.status_code)
|
60 |
+
if response.status_code == 200:
|
61 |
+
result = response.json()['result']
|
62 |
+
status = result['status']
|
63 |
+
if status == "success":
|
64 |
+
result = base64.b64decode(result['result'])
|
65 |
+
result_np = np.frombuffer(result, np.uint8)
|
66 |
+
result_img = cv2.imdecode(result_np, cv2.IMREAD_UNCHANGED)
|
67 |
+
result_img = cv2.cvtColor(result_img, cv2.COLOR_RGB2BGR)
|
68 |
+
info = "Success"
|
69 |
+
break
|
70 |
+
elif status == "error":
|
71 |
+
err_log = f"Status is Error"
|
72 |
+
info = "Error"
|
73 |
+
break
|
74 |
+
else:
|
75 |
+
# print(response.text)
|
76 |
+
err_log = "URL error, pleace contact the admin"
|
77 |
+
info = "URL error, pleace contact the admin"
|
78 |
+
break
|
79 |
+
except requests.exceptions.ReadTimeout:
|
80 |
+
err_log = "Http Timeout"
|
81 |
+
info = "Http Timeout, please try again later"
|
82 |
+
except Exception as err:
|
83 |
+
err_log = f"Get Exception Error: {err}"
|
84 |
+
time.sleep(1)
|
85 |
+
get_end_time = time.time()
|
86 |
+
print(f"get time used: {get_end_time-get_start_time}")
|
87 |
+
print(f"all time used: {get_end_time-get_start_time+post_end_time-post_start_time}")
|
88 |
+
if info == "":
|
89 |
+
err_log = f"No image after {Max_Retry} retries"
|
90 |
+
info = "Too many users, please try again later"
|
91 |
+
if info != "Success":
|
92 |
+
print(f"Error Log: {err_log}")
|
93 |
+
gr.Warning("Too many users, please try again later")
|
94 |
+
|
95 |
+
return result_img, seed, info
|
96 |
+
|
97 |
+
def start_tryon(person_img, garment_img, seed, randomize_seed):
|
98 |
+
start_time = time.time()
|
99 |
+
if person_img is None or garment_img is None:
|
100 |
+
return None, None, "Empty image"
|
101 |
+
if randomize_seed:
|
102 |
+
seed = random.randint(0, MAX_SEED)
|
103 |
+
encoded_person_img = cv2.imencode('.jpg', cv2.cvtColor(person_img, cv2.COLOR_RGB2BGR))[1].tobytes()
|
104 |
+
encoded_person_img = base64.b64encode(encoded_person_img).decode('utf-8')
|
105 |
+
encoded_garment_img = cv2.imencode('.jpg', cv2.cvtColor(garment_img, cv2.COLOR_RGB2BGR))[1].tobytes()
|
106 |
+
encoded_garment_img = base64.b64encode(encoded_garment_img).decode('utf-8')
|
107 |
+
|
108 |
+
url = "http://" + os.environ['tryon_url']
|
109 |
+
token = os.environ['token']
|
110 |
+
cookie = os.environ['Cookie']
|
111 |
+
referer = os.environ['referer']
|
112 |
+
|
113 |
+
headers = {'Content-Type': 'application/json', 'token': token, 'Cookie': cookie, 'referer': referer}
|
114 |
+
data = {
|
115 |
+
"clothImage": encoded_garment_img,
|
116 |
+
"humanImage": encoded_person_img,
|
117 |
+
"seed": seed
|
118 |
+
}
|
119 |
+
|
120 |
+
result_img = None
|
121 |
+
try:
|
122 |
+
session = requests.Session()
|
123 |
+
response = session.post(url, headers=headers, data=json.dumps(data), timeout=60)
|
124 |
+
print("response code", response.status_code)
|
125 |
+
if response.status_code == 200:
|
126 |
+
result = response.json()['result']
|
127 |
+
status = result['status']
|
128 |
+
if status == "success":
|
129 |
+
result = base64.b64decode(result['result'])
|
130 |
+
result_np = np.frombuffer(result, np.uint8)
|
131 |
+
result_img = cv2.imdecode(result_np, cv2.IMREAD_UNCHANGED)
|
132 |
+
result_img = cv2.cvtColor(result_img, cv2.COLOR_RGB2BGR)
|
133 |
+
info = "Success"
|
134 |
+
else:
|
135 |
+
info = "Try again latter"
|
136 |
+
else:
|
137 |
+
print(response.text)
|
138 |
+
info = "URL error, pleace contact the admin"
|
139 |
+
except requests.exceptions.ReadTimeout:
|
140 |
+
print("timeout")
|
141 |
+
info = "Too many users, please try again later"
|
142 |
+
raise gr.Error("Too many users, please try again later")
|
143 |
+
except Exception as err:
|
144 |
+
print(f"其他错误: {err}")
|
145 |
+
info = "Error, pleace contact the admin"
|
146 |
+
end_time = time.time()
|
147 |
+
print(f"time used: {end_time-start_time}")
|
148 |
+
|
149 |
+
return result_img, seed, info
|
150 |
+
|
151 |
+
MAX_SEED = 999999
|
152 |
+
|
153 |
+
example_path = os.path.join(os.path.dirname(__file__), 'assets')
|
154 |
+
|
155 |
+
garm_list = os.listdir(os.path.join(example_path,"cloth"))
|
156 |
+
garm_list_path = [os.path.join(example_path,"cloth",garm) for garm in garm_list]
|
157 |
+
|
158 |
+
human_list = os.listdir(os.path.join(example_path,"human"))
|
159 |
+
human_list_path = [os.path.join(example_path,"human",human) for human in human_list]
|
160 |
+
|
161 |
+
css="""
|
162 |
+
#col-left {
|
163 |
+
margin: 0 auto;
|
164 |
+
max-width: 430px;
|
165 |
+
}
|
166 |
+
#col-mid {
|
167 |
+
margin: 0 auto;
|
168 |
+
max-width: 430px;
|
169 |
+
}
|
170 |
+
#col-right {
|
171 |
+
margin: 0 auto;
|
172 |
+
max-width: 430px;
|
173 |
+
}
|
174 |
+
#col-showcase {
|
175 |
+
margin: 0 auto;
|
176 |
+
max-width: 1100px;
|
177 |
+
}
|
178 |
+
#button {
|
179 |
+
color: blue;
|
180 |
+
}
|
181 |
+
"""
|
182 |
+
|
183 |
+
def load_description(fp):
|
184 |
+
with open(fp, 'r', encoding='utf-8') as f:
|
185 |
+
content = f.read()
|
186 |
+
return content
|
187 |
+
|
188 |
+
def change_imgs(image1, image2):
|
189 |
+
return image1, image2
|
190 |
+
|
191 |
+
with gr.Blocks(css=css) as Tryon:
|
192 |
+
gr.HTML(load_description("assets/title.md"))
|
193 |
+
with gr.Row():
|
194 |
+
with gr.Column(elem_id = "col-left"):
|
195 |
+
gr.HTML("""
|
196 |
+
<div style="display: flex; justify-content: center; align-items: center; text-align: center; font-size: 20px;">
|
197 |
+
<div>
|
198 |
+
Step 1. Upload a person image ⬇️
|
199 |
+
</div>
|
200 |
+
</div>
|
201 |
+
""")
|
202 |
+
with gr.Column(elem_id = "col-mid"):
|
203 |
+
gr.HTML("""
|
204 |
+
<div style="display: flex; justify-content: center; align-items: center; text-align: center; font-size: 20px;">
|
205 |
+
<div>
|
206 |
+
Step 2. Upload a garment image ⬇️
|
207 |
+
</div>
|
208 |
+
</div>
|
209 |
+
""")
|
210 |
+
with gr.Column(elem_id = "col-right"):
|
211 |
+
gr.HTML("""
|
212 |
+
<div style="display: flex; justify-content: center; align-items: center; text-align: center; font-size: 20px;">
|
213 |
+
<div>
|
214 |
+
Step 3. Press “Run” to get try-on results
|
215 |
+
</div>
|
216 |
+
</div>
|
217 |
+
""")
|
218 |
+
with gr.Row():
|
219 |
+
with gr.Column(elem_id = "col-left"):
|
220 |
+
imgs = gr.Image(label="Person image", sources='upload', type="numpy")
|
221 |
+
# category = gr.Dropdown(label="Garment category", choices=['upper_body', 'lower_body', 'dresses'], value="upper_body")
|
222 |
+
example = gr.Examples(
|
223 |
+
inputs=imgs,
|
224 |
+
examples_per_page=12,
|
225 |
+
examples=human_list_path
|
226 |
+
)
|
227 |
+
with gr.Column(elem_id = "col-mid"):
|
228 |
+
garm_img = gr.Image(label="Garment image", sources='upload', type="numpy")
|
229 |
+
example = gr.Examples(
|
230 |
+
inputs=garm_img,
|
231 |
+
examples_per_page=12,
|
232 |
+
examples=garm_list_path
|
233 |
+
)
|
234 |
+
with gr.Column(elem_id = "col-right"):
|
235 |
+
image_out = gr.Image(label="Result", show_share_button=False)
|
236 |
+
with gr.Row():
|
237 |
+
seed = gr.Slider(
|
238 |
+
label="Seed",
|
239 |
+
minimum=0,
|
240 |
+
maximum=MAX_SEED,
|
241 |
+
step=1,
|
242 |
+
value=0,
|
243 |
+
)
|
244 |
+
randomize_seed = gr.Checkbox(label="Random seed", value=True)
|
245 |
+
with gr.Row():
|
246 |
+
seed_used = gr.Number(label="Seed used")
|
247 |
+
result_info = gr.Text(label="Response")
|
248 |
+
# try_button = gr.Button(value="Run", elem_id="button")
|
249 |
+
test_button = gr.Button(value="Run", elem_id="button")
|
250 |
+
|
251 |
+
|
252 |
+
# 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)
|
253 |
+
test_button.click(fn=tryon, inputs=[imgs, garm_img, seed, randomize_seed], outputs=[image_out, seed_used, result_info], api_name=False, concurrency_limit=45)
|
254 |
+
|
255 |
+
with gr.Column(elem_id = "col-showcase"):
|
256 |
+
gr.HTML("""
|
257 |
+
<div style="display: flex; justify-content: center; align-items: center; text-align: center; font-size: 20px;">
|
258 |
+
<div> </div>
|
259 |
+
<br>
|
260 |
+
<div>
|
261 |
+
Virtual try-on examples in pairs of person and garment images
|
262 |
+
</div>
|
263 |
+
</div>
|
264 |
+
""")
|
265 |
+
show_case = gr.Examples(
|
266 |
+
examples=[
|
267 |
+
["assets/examples/model2.png", "assets/examples/garment2.png", "assets/examples/result2.png"],
|
268 |
+
["assets/examples/model3.png", "assets/examples/garment3.png", "assets/examples/result3.png"],
|
269 |
+
["assets/examples/model1.png", "assets/examples/garment1.png", "assets/examples/result1.png"],
|
270 |
+
],
|
271 |
+
inputs=[imgs, garm_img, image_out],
|
272 |
+
label=None
|
273 |
+
)
|
274 |
+
|
275 |
+
Tryon.queue(api_open=False).launch(show_api=False)
|