Upload app_gradio.py

app_gradio.py

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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()