main.py

import streamlit as st
import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt
from PIL import Image

def main():
    st.title('Cifar10 Web Classifier')
    st.write('Upload an image that you think fits into one of the classes and see if the prediction is correct')

    file = st.file_uploader('Please upload an image', type=['jpg','png'])
    if file:
        image = Image.open(file)
        st.image(image, use_column_width=True)

        resized_image = image.resize((32,32))
        img_array = np.array(resized_image)/255
        img_array = img_array.reshape((1,32,32,3))

        model = tf.keras.models.load_model('cifar10_model.h5')

        predictions = model.predict(img_array)

        cifar10_classes = ['airplane','automobile','bird','cat','deer','dog','people','horse', 'ship','truck']

        fig, ax = plt.subplots()
        y_pos = np.arange(len(cifar10_classes))
        ax.barh(y_pos, predictions[0], align='center')
        ax.set_yticks(y_pos)
        ax.set_yticklabels(cifar10_classes)

        ax.invert_yaxis()
        ax.set_xlabel('Probability')
        ax.set_title("CIFAR10 Predictions")

        st.pyplot(fig)
    else:
        st.text("You have not uploaded an image yet")



if __name__ =='__main__':
    main()