app.py

import gradio as gr
from solar_fault_model import predict_damage

# Function that integrates with Gradio for inference
def classify_damage(image):
    # Save uploaded image to a temporary file
    image_path = "temp_image.jpg"
    image.save(image_path)
    
    # Predict the damage type using the model
    return predict_damage(image_path)

# Define Gradio interface
demo = gr.Interface(
    fn=classify_damage,
    inputs=gr.Image(type="pil", label="Upload Solar Panel Image"),
    outputs=gr.Textbox(label="Damage Type"),
    title="Solar Panel Damage Detection",
    description="Upload an image of a damaged solar panel to classify the damage type (e.g., cracked, dusted, shaded, overheated)."
)

if __name__ == "__main__":
    demo.launch()