app.py

import streamlit as st
import torch
from PIL import Image
import os

from read import classify

st.title("Pizza & Not Pizza")

device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
checkpoint = torch.load(os.path.join(os.getcwd(), "best.pth.tar"))
model = checkpoint["model"]
classes = checkpoint["classes"]
tran = checkpoint["transform"]

# upload image
while True:
    uploaded_file = st.file_uploader("Choose an image...", type="jpg")
    taking_picture = st.camera_input("Take a picture...")
    
    if uploaded_file is not None:
        img = Image.open(uploaded_file)
        st.image(img, caption="Uploaded Image.", use_column_width=True)
        label = classify(model, img, tran, classes, device)
        st.write(label)
        
    elif taking_picture is not None:
        img = Image.open(taking_picture)
        st.image(img, caption="Uploaded Image.", use_column_width=True)
        label = classify(model, img, tran, classes, device)
        st.write(label)
    
    else:
        pass