app.py

import streamlit as st
from PIL import Image
from fastai.vision.all import *

def is_cat(x): 
    return x[0].isupper()

learn = load_learner('model.pkl')
categories = ('Dog', 'Cat')

def classify_image(img):
    img = Image.open(img)
    pred, idx, probs = learn.predict(img)
    return {categories[i]: float(probs[i]) for i in range(len(categories))}

st.title("Image Classifier")
uploaded_file = st.file_uploader("Choose an image...", type="jpg")

if uploaded_file is not None:
    image = Image.open(uploaded_file)
    st.image(image, caption='Uploaded Image', use_column_width=True)
    st.write("")
    st.write("Classifying...")
    result = classify_image(uploaded_file)
    st.write(result)