import gradio as gr
from transformers import pipeline

# Load the breast cancer image classification model
model = pipeline("image-classification", model="OverDriveLee/Breast_Cancer")

# Define the prediction function
def classify_image(image):
    results = model(image)
    return {"prediction": results[0]["label"], "confidence": results[0]["score"]}

# Define the Gradio interface
iface = gr.Interface(
    fn=classify_image,
    inputs=gr.inputs.Image(),
    outputs="json",
    title="Breast Cancer Image Classification",
    description="This application classifies breast cancer images into different classes."
)

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