app.py

import gradio as gr
from transformers import pipeline
from PIL import Image

# Load a pre-trained model suitable for general plant disease classification
# Replace with an appropriate model from Hugging Face's hub trained on PlantVillage or similar
model = pipeline("image-classification", model="PlantVillage/plant-disease-model")  # Replace with actual general plant disease model name if available

def classify_leaf_disease(image):
    # Run the model on the image
    results = model(image)
    
    # Get the top prediction
    disease_name = results[0]['label']
    confidence_score = results[0]['score']
    
    # Format the output
    return disease_name, f"{confidence_score:.2f}", image

# Create Gradio Interface
interface = gr.Interface(
    fn=classify_leaf_disease,
    inputs=gr.Image(type="pil"),
    outputs=[
        gr.Textbox(label="Disease Name"),
        gr.Textbox(label="Confidence Score"),
        gr.Image(type="pil", label="Uploaded Image")
    ],
    title="Leaf Disease Identification",
    description="Upload an image of any plant leaf, and this model will identify the disease and show the confidence score."
)

# Launch the app
if __name__ == "__main__":
    interface.launch()