# -*- coding: utf-8 -*-
"""interface.ipynb

Automatically generated by Colab.

Original file is located at
    https://colab.research.google.com/drive/1GvHbtJDns2rWyk-OdqSP-90yAbWY4ctR
"""


import gradio as gr
import tensorflow as tf
import numpy as np
from tensorflow.keras.preprocessing import image

# Load your trained model
model = tf.keras.models.load_model('cat_dog_classifier.h5')

# Define prediction functiond
def predict(img):
    img = img.resize((160, 160))
    img_array = image.img_to_array(img) / 255.0
    img_array = np.expand_dims(img_array, axis=0)
    prediction = model.predict(img_array)[0][0]
    return "🐶 It's a Dog!" if prediction > 0.5 else "🐱 It's a Cat!"

# Create Gradio interface
interface = gr.Interface(
    fn=predict,
    inputs=gr.Image(type="pil", label="Upload an Image"),
    outputs=gr.Textbox(label="Prediction"),
    title="Cat vs Dog Classifier 🐾",
    description="Upload an image to find out if it's a cat or a dog!"
)

# Launch interface
interface.launch()