import gradio as gr
import tensorflow as tf
import numpy as np
from PIL import Image

model = tf.keras.models.load_model("cat_dog_model (1).h5")

def predict(image):
    img = image.resize((100,100))
    img = np.array(img)/255.0
    img = np.expand_dims(img, axis=0)

    pred = model.predict(img)[0][0]

    if pred > 0.5:
        return "Dog 🐶"
    else:
        return "Cat 🐱"

interface = gr.Interface(
    fn=predict,
    inputs=gr.Image(type="pil"),
    outputs="text",
    title="Cat vs Dog Classifier"
)

interface.launch()