app.py

import streamlit as st
from PIL import Image
from transformers import pipeline

st.set_page_config(page_title="Emotion AI", page_icon="🧠", layout="centered")

st.title("🧠 Emotion Recognition AI")
st.write("Upload a face image and detect emotion")

# современная модель (работает без .h5 и TensorFlow)
@st.cache_resource
def load_model():
    return pipeline(
        "image-classification",
        model="trpakov/vit-face-expression"
    )

model = load_model()

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

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

    result = model(img)

    st.markdown("## Prediction")

    for r in result:
        st.write(f"**{r['label']}** : {round(r['score'], 3)}")