import gradio as gr
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing import image
from keras.applications.imagenet_utils import preprocess_input
import numpy as np

# Load the model
model = load_model('dementia.h5')

def classify_image(inp):
    inp = inp.reshape((-1, 224, 224, 3))
    inp = preprocess_input(inp)
    prediction = model.predict(inp).flatten()
    return {"Dementia not Detected": float(prediction[0]), "Dementia Detected": float(prediction[1])}

# Use 'image_mode' to specify the shape
image_input = gr.Image(image_mode="RGB", source="upload", shape=(224, 224))

interface = gr.Interface(
    fn=classify_image,
    inputs=image_input,
    outputs="label",
    title="DementAI",
)

interface.launch()