src/app.py

import streamlit as st
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing import image
import numpy as np

# Load model
model = load_model("src/cat_dog_tl_model.keras")

st.title("🐱🐶 Cat vs Dog Predictor")

uploaded_file = st.file_uploader("Upload an image", type=["jpg", "png"])
if uploaded_file:
    img = image.load_img(uploaded_file, target_size=(224,224))
    x = image.img_to_array(img) / 255.0
    x = np.expand_dims(x, axis=0)

    pred = model.predict(x)[0][0]
    st.write("Prediction:", "Dog 🐶" if pred > 0.5 else "Cat 🐱")