Spaces:
Running
on
CPU Upgrade
Running
on
CPU Upgrade
File size: 18,323 Bytes
f69cd15 eaa8689 1ecb321 eaa8689 5cbc9b1 6af3026 f8801dc d1c501f 18f423a 4caf25d 18f423a 4e460bd 18f423a 5d19a11 18f423a 5b58307 18f423a 4e460bd 8947405 a079d6c 5b58307 4e460bd 5b58307 4e460bd d1c501f 24f237b e4c119e d25f2a3 a079d6c 8d83455 4e460bd 232eb9c f24d75a 4e460bd b470d34 8d83455 2231fef 5d19a11 18f423a d1c501f 5d19a11 4e460bd 8d83455 5d19a11 b6434bc 8d83455 4284d10 4e460bd 5b58307 a079d6c 22a00a3 8d83455 a079d6c 8d83455 5d19a11 18f423a 1ecb321 d1c501f eaa8689 f8801dc dbe8337 0805db6 eaa8689 8c2fca3 eaa8689 8c2fca3 eaa8689 8654223 f26d335 8654223 49eabb6 6803e6c 49eabb6 6803e6c 6af3026 b453f9d 0c1a8d3 4ad0645 0c1a8d3 d1c501f b453f9d 0c1a8d3 d1c501f 0c1a8d3 64d0526 0c1a8d3 d1c501f f8801dc 6af3026 b453f9d 1ecb321 d1c501f 534e5bb d1c501f f69cd15 d1c501f f69cd15 d1c501f 01db67e d1c501f f69cd15 1ecb321 d1c501f f69cd15 4db4e89 a9ba2aa 4db4e89 f69cd15 1ecb321 d1c501f 1ecb321 f69cd15 d1c501f 1ecb321 fc8d8be f69cd15 d1c501f f69cd15 d1c501f bd8fedc 070a1ae bd8fedc d1c501f bd8fedc d1c501f bd8fedc 070a1ae bd8fedc d1c501f bd8fedc d1c501f bd8fedc 070a1ae bd8fedc d1c501f bd8fedc d1c501f ad30fcb d1c501f b453f9d 7de6d0d 534e5bb 7de6d0d d1c501f 7de6d0d fa6131f d1c501f 537454a d1c501f 537454a d1c501f 537454a d1c501f |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 |
import os
import cv2
import gradio as gr
import numpy as np
import random
import base64
import requests
import json
import time
from PIL import Image
def tryon(person_img, garment_img, seed, randomize_seed):
post_start_time = time.time()
if person_img is None or garment_img is None:
gr.Warning("Empty image")
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'] + "Submit"
token = os.environ['token']
cookie = os.environ['Cookie']
referer = os.environ['referer']
headers = {'Content-Type': 'application/json', 'token': token, 'Cookie': cookie, 'referer': referer}
data = {
"clothImage": encoded_garment_img,
"humanImage": encoded_person_img,
"seed": seed
}
try:
response = requests.post(url, headers=headers, data=json.dumps(data), timeout=50)
if response.status_code == 200:
result = response.json()['result']
status = result['status']
if status == "success":
uuid = result['result']
except Exception as err:
print(f"Post Exception Error: {err}")
raise gr.Error("Too many users, please try again later")
post_end_time = time.time()
print(f"post time used: {post_end_time-post_start_time}")
get_start_time = time.time()
time.sleep(9)
Max_Retry = 12
result_img = None
info = ""
err_log = ""
for i in range(Max_Retry):
try:
url = "http://" + os.environ['tryon_url'] + "Query?taskId=" + uuid
response = requests.get(url, headers=headers, timeout=20)
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"
break
elif status == "error":
err_log = f"Status is Error"
info = "Error"
break
else:
err_log = "URL error, please contact the admin"
info = "URL error, please contact the admin"
break
except requests.exceptions.ReadTimeout:
err_log = "Http Timeout"
info = "Http Timeout, please try again later"
except Exception as err:
err_log = f"Get Exception Error: {err}"
time.sleep(1)
get_end_time = time.time()
print(f"get time used: {get_end_time-get_start_time}")
print(f"all time used: {get_end_time-get_start_time+post_end_time-post_start_time}")
if info == "":
err_log = f"No image after {Max_Retry} retries"
info = "Too many users, please try again later"
if info != "Success":
print(f"Error Log: {err_log}")
gr.Warning("Too many users, please try again later")
return result_img, seed, info
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']
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()
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 later"
else:
print(response.text)
info = "URL error, please contact the admin"
except requests.exceptions.ReadTimeout:
print("timeout")
info = "Too many users, please try again later"
raise gr.Error("Too many users, please try again later")
except Exception as err:
print(f"Other error: {err}")
info = "Error, please contact the admin"
end_time = time.time()
print(f"time used: {end_time-start_time}")
return result_img, seed, info
def capture_person_photo(webcam_image):
"""Process captured person photo from webcam"""
if webcam_image is None:
gr.Warning("No image captured from camera")
return None
return webcam_image
def capture_garment_photo(webcam_image):
"""Process captured garment photo from webcam"""
if webcam_image is None:
gr.Warning("No image captured from camera")
return None
return webcam_image
def clear_person_image():
"""Clear the person image"""
return None
def clear_garment_image():
"""Clear the garment image"""
return None
def switch_to_upload_person():
"""Switch to upload mode for person image"""
return gr.update(visible=True), gr.update(visible=False)
def switch_to_camera_person():
"""Switch to camera mode for person image"""
return gr.update(visible=False), gr.update(visible=True)
def switch_to_upload_garment():
"""Switch to upload mode for garment image"""
return gr.update(visible=True), gr.update(visible=False)
def switch_to_camera_garment():
"""Switch to camera mode for garment image"""
return gr.update(visible=False), gr.update(visible=True)
MAX_SEED = 999999
example_path = os.path.join(os.path.dirname(__file__), 'assets')
# Check if assets directory exists, if not create dummy lists
if os.path.exists(example_path):
garm_list = os.listdir(os.path.join(example_path, "cloth")) if os.path.exists(os.path.join(example_path, "cloth")) else []
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")) if os.path.exists(os.path.join(example_path, "human")) else []
human_list_path = [os.path.join(example_path, "human", human) for human in human_list]
else:
garm_list_path = []
human_list_path = []
css = """
#col-left {
margin: 0 auto;
max-width: 450px;
}
#col-mid {
margin: 0 auto;
max-width: 450px;
}
#col-right {
margin: 0 auto;
max-width: 450px;
}
#col-showcase {
margin: 0 auto;
max-width: 1100px;
}
#button {
color: blue;
}
.camera-section {
border: 2px dashed #ccc;
border-radius: 10px;
padding: 10px;
margin: 5px 0;
}
.mode-buttons {
display: flex;
gap: 10px;
margin-bottom: 10px;
}
"""
def load_description(fp):
"""Load description from file if it exists, otherwise return default"""
try:
with open(fp, 'r', encoding='utf-8') as f:
content = f.read()
return content
except FileNotFoundError:
return """
# π― Virtual Try-On Application
**Experience the future of fashion with AI-powered virtual try-on technology!**
Upload or capture photos of yourself and garments to see how they look together.
"""
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; font-size: 20px;">
<div>
πΈ Step 1. Get Person Image β¬οΈ
</div>
</div>
""")
with gr.Column(elem_id="col-mid"):
gr.HTML("""
<div style="display: flex; justify-content: center; align-items: center; text-align: center; font-size: 20px;">
<div>
π Step 2. Get Garment Image β¬οΈ
</div>
</div>
""")
with gr.Column(elem_id="col-right"):
gr.HTML("""
<div style="display: flex; justify-content: center; align-items: center; text-align: center; font-size: 20px;">
<div>
β¨ Step 3. Generate Try-On Result
</div>
</div>
""")
with gr.Row():
# Person Image Column
with gr.Column(elem_id="col-left"):
# Mode selection buttons for person
with gr.Row(elem_classes="mode-buttons"):
upload_person_btn = gr.Button("π Upload Photo", variant="secondary", size="sm")
camera_person_btn = gr.Button("π· Take Photo", variant="secondary", size="sm")
clear_person_btn = gr.Button("ποΈ Clear", variant="secondary", size="sm")
# Upload interface for person (visible by default)
with gr.Group(visible=True) as person_upload_group:
person_img_upload = gr.Image(
label="Person Image (Upload)",
sources=['upload'],
type="numpy",
height=400
)
# Camera interface for person (hidden by default)
with gr.Group(visible=False, elem_classes="camera-section") as person_camera_group:
person_img_camera = gr.Image(
label="Person Image (Camera)",
sources=['webcam'],
type="numpy",
height=400
)
capture_person_btn = gr.Button("πΈ Capture Person Photo", variant="primary")
# Combined person image state
person_img_final = gr.State()
# Examples for person images
if human_list_path:
example_person = gr.Examples(
inputs=person_img_upload,
examples_per_page=8,
examples=human_list_path,
label="Example Person Images"
)
# Garment Image Column
with gr.Column(elem_id="col-mid"):
# Mode selection buttons for garment
with gr.Row(elem_classes="mode-buttons"):
upload_garment_btn = gr.Button("π Upload Photo", variant="secondary", size="sm")
camera_garment_btn = gr.Button("π· Take Photo", variant="secondary", size="sm")
clear_garment_btn = gr.Button("ποΈ Clear", variant="secondary", size="sm")
# Upload interface for garment (visible by default)
with gr.Group(visible=True) as garment_upload_group:
garment_img_upload = gr.Image(
label="Garment Image (Upload)",
sources=['upload'],
type="numpy",
height=400
)
# Camera interface for garment (hidden by default)
with gr.Group(visible=False, elem_classes="camera-section") as garment_camera_group:
garment_img_camera = gr.Image(
label="Garment Image (Camera)",
sources=['webcam'],
type="numpy",
height=400
)
capture_garment_btn = gr.Button("πΈ Capture Garment Photo", variant="primary")
# Combined garment image state
garment_img_final = gr.State()
# Examples for garment images
if garm_list_path:
example_garment = gr.Examples(
inputs=garment_img_upload,
examples_per_page=8,
examples=garm_list_path,
label="Example Garment Images"
)
# Results Column
with gr.Column(elem_id="col-right"):
image_out = gr.Image(label="π― Try-On Result", show_share_button=False, height=400)
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="Status")
# Main try-on button
tryon_button = gr.Button("π Generate Try-On", variant="primary", size="lg")
# Event handlers for person image mode switching
upload_person_btn.click(
switch_to_upload_person,
outputs=[person_upload_group, person_camera_group]
)
camera_person_btn.click(
switch_to_camera_person,
outputs=[person_upload_group, person_camera_group]
)
clear_person_btn.click(
clear_person_image,
outputs=[person_img_upload]
)
# Event handlers for garment image mode switching
upload_garment_btn.click(
switch_to_upload_garment,
outputs=[garment_upload_group, garment_camera_group]
)
camera_garment_btn.click(
switch_to_camera_garment,
outputs=[garment_upload_group, garment_camera_group]
)
clear_garment_btn.click(
clear_garment_image,
outputs=[garment_img_upload]
)
# Capture button handlers
capture_person_btn.click(
capture_person_photo,
inputs=[person_img_camera],
outputs=[person_img_final]
)
capture_garment_btn.click(
capture_garment_photo,
inputs=[garment_img_camera],
outputs=[garment_img_final]
)
# Function to get the current person image
def get_current_person_image(upload_img, camera_img, final_img):
if final_img is not None:
return final_img
elif upload_img is not None:
return upload_img
elif camera_img is not None:
return camera_img
return None
# Function to get the current garment image
def get_current_garment_image(upload_img, camera_img, final_img):
if final_img is not None:
return final_img
elif upload_img is not None:
return upload_img
elif camera_img is not None:
return camera_img
return None
# Modified try-on function to handle multiple image sources
def run_tryon(person_upload, person_camera, person_final,
garment_upload, garment_camera, garment_final,
seed, randomize_seed):
# Get the current person image
person_img = get_current_person_image(person_upload, person_camera, person_final)
# Get the current garment image
garment_img = get_current_garment_image(garment_upload, garment_camera, garment_final)
# Run the try-on process
return tryon(person_img, garment_img, seed, randomize_seed)
# Main try-on button click handler
tryon_button.click(
fn=run_tryon,
inputs=[
person_img_upload, person_img_camera, person_img_final,
garment_img_upload, garment_img_camera, garment_img_final,
seed, randomize_seed
],
outputs=[image_out, seed_used, result_info],
api_name=False,
concurrency_limit=45
)
# Showcase section
with gr.Column(elem_id="col-showcase"):
gr.HTML("""
<div style="display: flex; justify-content: center; align-items: center; text-align: center; font-size: 20px; margin-top: 30px;">
<div>
π Virtual Try-On Examples
<br><br>
<em>See how different garments look on various models</em>
</div>
</div>
""")
# Only show examples if they exist
if os.path.exists("assets/examples"):
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=[person_img_upload, garment_img_upload, image_out],
label="Example Try-On Results"
)
# Launch the app
if __name__ == "__main__":
Tryon.queue(api_open=False).launch(
show_api=False,
share=False,
server_name="0.0.0.0",
server_port=7860
) |