app.py

import streamlit as st
import tensorflow as tf
import numpy as np
import cv2
from PIL import Image

model = tf.keras.models.load_model("emotion_model_rafdb.h5", compile=False)

labels = ["angry","disgust","fear","happy","neutral","sad","surprise"]

st.title("Emotion AI")

file = st.file_uploader("Upload image")

if file:
    img = Image.open(file)
    st.image(img)

    img = np.array(img)
    img = cv2.resize(img,(224,224))/255.0
    img = np.expand_dims(img,0)

    pred = model.predict(img)[0]
    idx = np.argmax(pred)

    st.write("Emotion:", labels[idx])