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import os | |
import cv2 | |
import numpy as np | |
import json | |
import random | |
from PIL import Image, ImageDraw, ImageFont | |
import asyncio | |
import requests | |
import base64 | |
import gradio as gr | |
# Set the machine number and model path | |
machine_number = 0 | |
model = os.path.join(os.path.dirname(__file__), "models", "eva", "Eva_0.png") | |
# Define a mapping of model names to file paths | |
MODEL_MAP = { | |
"AI Model Rouyan_0": os.path.join("models", "rouyan_new", "rouyan_new\\Rouyan_0.png"), | |
"AI Model Rouyan_1": os.path.join("models", "rouyan_new", "rouyan_new\\Rouyan_1.png"), | |
"AI Model Rouyan_2": os.path.join("models", "rouyan_new", "rouyan_new\\Rouyan_2.png"), | |
"AI Model Eva_0": os.path.join("models", "eva", "Eva_0.png"), | |
"AI Model Eva_1": os.path.join("models", "eva", "Eva_1.png"), | |
"AI Model Simon_0": os.path.join("models", "simon_online", "Simon_0.png"), | |
"AI Model Simon_1": os.path.join("models", "simon_online", "Simon_1.png"), | |
"AI Model Xuanxuan_0": os.path.join("models", "xiaoxuan_online", "Xuanxuan_0.png"), | |
"AI Model Xuanxuan_1": os.path.join("models", "xiaoxuan_online", "Xuanxuan_1.png"), | |
"AI Model Xuanxuan_2": os.path.join("models", "xiaoxuan_online", "Xuanxuan_2.png"), | |
"AI Model Yaqi_0": os.path.join("models", "yaqi", "Yaqi_0.png"), | |
"AI Model Yaqi_1": os.path.join("models", "yaqi", "Yaqi_1.png"), | |
"AI Model Yaqi_2": os.path.join("models", "yaqi", "Yaqi_2.png"), | |
"AI Model Yaqi_3": os.path.join("models", "yaqi", "Yaqi_3.png"), | |
"AI Model Yifeng_0": os.path.join("models", "yifeng_online", "Yifeng_0.png"), | |
"AI Model Yifeng_1": os.path.join("models", "yifeng_online", "Yifeng_1.png"), | |
"AI Model Yifeng_2": os.path.join("models", "yifeng_online", "Yifeng_2.png"), | |
"AI Model Yifeng_3": os.path.join("models", "yifeng_online", "Yifeng_3.png"), | |
} | |
# Function to add watermark text to image | |
def add_waterprint(img): | |
h, w, _ = img.shape | |
img = cv2.putText(img, 'Powered by OutfitAnyone', (int(0.3*w), h-20), cv2.FONT_HERSHEY_PLAIN, 2, (128, 128, 128), 2, cv2.LINE_AA) | |
return img | |
# Function to process try-on results | |
def get_tryon_result(model_name, garment1, garment2, seed=1234): | |
if isinstance(model_name, np.ndarray): | |
model_name = model_name[0] | |
model_name = "AI Model " + model_name.split("\\")[-1].split(".")[0] # Handle Windows path | |
print(type(model_name)) | |
# Directly load the model image from the disk, no need for Gradio file upload | |
model_image = cv2.imread(MODEL_MAP.get(model_name)) # Load model image from disk | |
if model_image is None: | |
raise ValueError(f"Model image {model_name} could not be loaded.") | |
# Encode garments as base64 | |
encoded_garment1 = cv2.imencode('.jpg', garment1)[1].tobytes() | |
encoded_garment1 = base64.b64encode(encoded_garment1).decode('utf-8') | |
if garment2 is not None: | |
encoded_garment2 = cv2.imencode('.jpg', garment2)[1].tobytes() | |
encoded_garment2 = base64.b64encode(encoded_garment2).decode('utf-8') | |
else: | |
encoded_garment2 = '' | |
# Get the IP address from environment variable or default to localhost | |
url = os.environ.get('OA_IP_ADDRESS', 'http://localhost:5000') | |
headers = {'Content-Type': 'application/json'} | |
seed = random.randint(0, 1222222222) | |
# Prepare data for POST request | |
data = { | |
"garment1": encoded_garment1, | |
"garment2": encoded_garment2, | |
"model_name": model_name, | |
"seed": seed | |
} | |
# Send POST request to server | |
response = requests.post(url, headers=headers, data=json.dumps(data)) | |
print("response code", response.status_code) | |
if response.status_code == 200: | |
result = response.json() | |
result = base64.b64decode(result['images'][0]) | |
result_np = np.frombuffer(result, np.uint8) | |
result_img = cv2.imdecode(result_np, cv2.IMREAD_UNCHANGED) | |
else: | |
print('Server error!') | |
final_img = add_waterprint(result_img) | |
return final_img | |
with gr.Blocks(css=".output-image, .input-image, .image-preview {height: 400px !important}") as demo: | |
# Header Section | |
gr.HTML( | |
""" | |
<div style="text-align: center; padding: 20px;"> | |
<h1 style="font-size: 2.5rem; color: #2c3e50;">Outfit Anyone</h1> | |
<h2 style="color: #34495e;">Ultra-high quality virtual try-on for any clothing and any person</h2> | |
</div> | |
""" | |
) | |
# UI Layout for Image Inputs and Text Description | |
with gr.Row(): | |
with gr.Column(): | |
gr.Markdown("### Upload Your Model Image") | |
init_image = gr.Image(sources='upload', type="numpy", label="Select a Model Image", value=None) | |
example = gr.Examples(inputs=init_image, | |
examples_per_page=4, | |
examples=[os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Rouyan_0'))]) | |
with gr.Column(): | |
gr.Markdown( | |
""" | |
<h3 style="color: #2c3e50;">Instructions</h3> | |
<p style="font-size: 1.1rem; color: #7f8c8d;">Please upload your model image and garment images (top and bottom). | |
The models are pre-loaded and cannot be modified. | |
For a dress or coat, you only need to upload the image for the 'Top Garment' section and leave the 'Bottom Garment' section empty.</p> | |
""" | |
) | |
with gr.Row(): | |
garment_top = gr.Image(sources='upload', type="numpy", label="Top Garment") | |
example_top = gr.Examples(inputs=garment_top, | |
examples_per_page=5, | |
examples=[os.path.join(os.path.dirname(__file__), "garments", "top222.JPG")]) | |
garment_down = gr.Image(sources='upload', type="numpy", label="Bottom Garment") | |
example_down = gr.Examples(inputs=garment_down, | |
examples_per_page=5, | |
examples=[os.path.join(os.path.dirname(__file__), "garments", "bottom1.png")]) | |
run_button = gr.Button(value="Run Try-On") | |
with gr.Column(): | |
gallery = gr.Image(label="Try-On Result") | |
run_button.click(fn=get_tryon_result, | |
inputs=[init_image, garment_top, garment_down], | |
outputs=[gallery], | |
concurrency_limit=2) | |
# Example Section | |
gr.Markdown("## Example Try-On Results") | |
with gr.Row(): | |
reference_image1 = gr.Image(label="Model Example", scale=1, value="examples\\examples_basemodel.png") | |
reference_image2 = gr.Image(label="Garment Example", scale=1, value="examples\\examples_garment1.jpg") | |
reference_image3 = gr.Image(label="Result Example", scale=1, value="examples\\examples_result1.png") | |
gr.Examples( | |
examples=[["examples\\examples_basemodel.png", "examples\\examples_garment1.png", "examples\\examples_result1.png"]], | |
inputs=[reference_image1, reference_image2, reference_image3], | |
label="Check out our example outfits!", | |
) | |
if __name__ == "__main__": | |
ip = requests.get('http://ifconfig.me/ip', timeout=1).text.strip() | |
print("IP address", ip) | |
demo.queue(max_size=10) | |
demo.launch() | |