src/app.py

import streamlit as st
import numpy as np
import tensorflow as tf
from PIL import Image

# Load model
model = tf.keras.models.load_model("src/street_food_model.keras")

class_names = [
    'burger','churros','crepes','falafel',
    'hot_dog','pad_thai','pani_puri',
    'pretzel','shawarma','tacos'
]

st.title("🍔 Street Food Classifier")

uploaded_file = st.file_uploader("Upload an image", type=["jpg","png","jpeg"])

if uploaded_file is not None:
    image = Image.open(uploaded_file).resize((224,224))
    st.image(image, caption="Uploaded Image", use_column_width=True)

    img_array = np.array(image) / 255.0
    img_array = np.expand_dims(img_array, axis=0)

    prediction = model.predict(img_array)
    predicted_class = class_names[np.argmax(prediction)]

    st.success(f"Prediction: {predicted_class}")