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import gradio as gr
import requests
import os
# Load API Key from Environment Variable
HUGGING_FACE_API_KEY = os.getenv("HUGGING_FACE_API_KEY")
# Hugging Face Model API URL
MODEL_URL = "https://api-inference.huggingface.co/models/ramim36/Kolors-Virtual-Try-On"
def virtual_tryon(user_image, cloth_image):
"""Send images to Hugging Face model and return result."""
if user_image is None or cloth_image is None:
return "Please upload both user and cloth images."
headers = {"Authorization": f"Bearer {HUGGING_FACE_API_KEY}"}
files = {
"user_image": user_image,
"cloth_image": cloth_image,
}
response = requests.post(MODEL_URL, headers=headers, files=files)
if response.status_code == 200:
return response.json() # Return model output
else:
return {"error": "Failed to process request", "details": response.text}
# Gradio Interface
iface = gr.Interface(
fn=virtual_tryon,
inputs=[
gr.Image(type="file", label="Upload User Image"),
gr.Image(type="file", label="Upload Cloth Image"),
],
outputs="json",
title="Virtual Try-On",
description="Upload a user image and a clothing image to try them on virtually.",
)
# Launch Gradio app
if __name__ == "__main__":
iface.launch()