app.py

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

pipeline = pipeline(task="image-classification", model="Libidrave/CartoonOrNotv2")

st.title("Cartoon Or Not Image Classifiers")
file_name = st.file_uploader("Upload an Image to predict")

if file_name is not None:
    col1, col2 = st.columns(2)

    image = Image.open(file_name)
    col1.image(image, use_column_width=True)
    predictions = pipeline(image)

    col2.header("Probabilities")
    for p in predictions:
        col2.subheader(f"{ p['label'] }: { round(p['score'] * 100, 1)}%")

"""[View the Model Repository](https://github.com/Libidrave/CartoonOrNot/blob/main/TrainingModel.ipynb)"""