image classification web app using stramlit code example

Example: image classification web app using stramlit

import cv2from PIL import Image, ImageOpsimport numpy as npdef import_and_predict(image_data, model):            size = (150,150)            image = ImageOps.fit(image_data, size, Image.ANTIALIAS)        image = np.asarray(image)        img = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)        img_resize = (cv2.resize(img, dsize=(75, 75),    interpolation=cv2.INTER_CUBIC))/255.                img_reshape = img_resize[np.newaxis,...]            prediction = model.predict(img_reshape)                return predictionif file is None:    st.text("Please upload an image file")else:    image = Image.open(file)    st.image(image, use_column_width=True)    prediction = import_and_predict(image, model)        if np.argmax(prediction) == 0:        st.write("It is a paper!")    elif np.argmax(prediction) == 1:        st.write("It is a rock!")    else:        st.write("It is a scissor!")        st.text("Probability (0: Paper, 1: Rock, 2: Scissor")    st.write(prediction)