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import os
import cv2
import gradio as gr
import numpy as np
import random
import base64
import requests
import json
import time
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)
# print("post response code", response.status_code)
if response.status_code == 200:
result = response.json()['result']
status = result['status']
if status == "success":
uuid = result['result']
# print(uuid)
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)
# print("get 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"
break
elif status == "error":
err_log = f"Status is Error"
info = "Error"
break
else:
# print(response.text)
err_log = "URL error, pleace contact the admin"
info = "URL error, pleace 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 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"
raise gr.Error("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; font-size: 20px;">
<div>
Step 1. Upload a person image ⬇️
</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>
Step 2. Upload a garment image ⬇️
</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>
Step 3. Press “Run” to get try-on results
</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")
test_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)
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)
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;">
<div> </div>
<br>
<div>
Virtual try-on examples in pairs of person and garment images
</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
)
Tryon.queue(api_open=False).launch(show_api=False)
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