Tryonn / app.py
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import os
import requests
import json
import time
import cv2
import base64
import random
import numpy as np
import gradio as gr
MAX_SEED = 999999
# βœ… Pixelcut API Key
pixelcut_api_key = "YOUR_PIXELCUT_API_KEY"
# βœ… ImgBB API Key (for uploading images to get valid URLs)
imgbb_api_key = "YOUR_IMGBB_API_KEY"
# 🎯 Convert image to PNG format
def convert_to_png(image):
return cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
# πŸ”₯ Resize large images to prevent upload failures (ImgBB limit: 32MB)
def resize_image(image, max_size=1024):
height, width = image.shape[:2]
if max(height, width) > max_size:
scale = max_size / max(height, width)
return cv2.resize(image, (int(width * scale), int(height * scale)))
return image
# πŸ› οΈ Upload images to ImgBB (fixed payload!)
def upload_image_to_imgbb(image_data):
url = f"https://api.imgbb.com/1/upload?key={imgbb_api_key}"
files = {"image": image_data}
response = requests.post(url, files=files)
if response.status_code == 200:
return response.json().get("data", {}).get("url")
else:
print("❌ ImgBB upload failed:", response.text)
return None
# πŸš€ Main try-on function using Pixelcut API
def tryon(person_img, garment_img, seed, randomize_seed):
start_time = time.time()
# πŸ›‘ Check if images are provided
if person_img is None or garment_img is None:
return None, None, "Empty image"
# 🎲 Handle seed randomization
if randomize_seed:
seed = random.randint(0, MAX_SEED)
# πŸ”₯ Convert and resize images to base64 PNG
person_img = resize_image(convert_to_png(person_img))
garment_img = resize_image(convert_to_png(garment_img))
_, person_encoded = cv2.imencode('.png', person_img)
_, garment_encoded = cv2.imencode('.png', garment_img)
# βœ… Upload person and garment images to get valid URLs
print("πŸ“€ Uploading person image...")
person_url = upload_image_to_imgbb(person_encoded)
print("πŸ“€ Uploading garment image...")
garment_url = upload_image_to_imgbb(garment_encoded)
if not person_url or not garment_url:
return None, None, "Image upload failed β€” check API keys or connection"
# 🌟 Setup Pixelcut API endpoint and headers
url = "https://api.developer.pixelcut.ai/v1/remove-background"
headers = {
'Content-Type': 'application/json',
'Accept': 'application/json',
'X-API-KEY': pixelcut_api_key
}
# πŸ”§ Use the uploaded URLs in the payload
person_data = {"image_url": person_url, "format": "png"}
garment_data = {"image_url": garment_url, "format": "png"}
result_img = None
max_retries = 5
retry_delay = 3 # Faster retries now!
try:
session = requests.Session()
# πŸ” Retry loop β€” smarter handling of "please try again later"
for attempt in range(max_retries):
response = session.post(url, headers=headers, json=person_data, timeout=60)
print("Response code:", response.status_code)
# βœ… Success β€” process the result
if response.status_code == 200:
result_url = response.json().get('result_url', '')
print("βœ… Success:", result_url)
# Fetch the final image
if result_url:
result_img_data = requests.get(result_url).content
result_np = np.frombuffer(result_img_data, np.uint8)
result_img = cv2.imdecode(result_np, cv2.IMREAD_UNCHANGED)
info = "βœ… Success"
break
else:
# πŸ”₯ Handle "please try again later" or other errors
error_response = response.json().get('error', '')
if "please try again later" in error_response.lower():
print(f"Attempt {attempt + 1}/{max_retries}: API said 'please try again later'. Retrying in {retry_delay} seconds...")
time.sleep(retry_delay)
retry_delay += 2 # Exponential backoff β€” retries longer each time
else:
info = f"❌ Error: {response.status_code} - {response.text}"
break
else:
# ❌ If all retries fail
info = "API still says 'please try again later' β€” waited too long."
# πŸ›‘ Handle timeouts specifically
except requests.exceptions.ReadTimeout:
print("Timeout!")
info = "⚑ Timeout β€” please try again later"
raise gr.Error("Too many users, please try again later")
# ❗ Handle any other unexpected errors
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:.2f} seconds")
return result_img, seed, info
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/new_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 β€œRun” 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)