Turning an image uploaded using Streamlit to a numpy array - tensorflow

Question

I'm working on a webapp for a machine learning project using Streamlit.
I've encountered this error at load_img:
TypeError: expected str, bytes or os.PathLike object, not UploadedFile.
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.image import load_img
from tensorflow.keras.preprocessing.image import img_to_array
from tensorflow.keras.applications.vgg16 import preprocess_input
from tensorflow.keras.applications.vgg16 import decode_predictions
from tensorflow.keras.applications.vgg16 import VGG16
from tensorflow.keras.models import model_from_json
import numpy as np
import cv2
import tensorflow as tf
import streamlit as st
st.write("This is a simple image classification web app to identify cars")
file = st.file_uploader("Please upload an image file", type=["jpg", "png"])
def import_and_predict(image_data, model):
image = load_img(image_data,target_size=(64,64))
img = img_to_array(image)
img = np.array(image)
img = img / 255.0
image = img.resize((64,64))
img = img.reshape(1,64,64,3)
label = model.predict_classes(img)
prediction = label[0][0]
return f"Prediction: {prediction}"
if file is None:
st.text("Please upload an image file")
else:
import_and_predict(file, model)

Answer 1

From the Streamlit documentation for file_uploader:
>>> uploaded_file = st.file_uploader("Choose a file")
>>> if uploaded_file is not None:
... # To read file as bytes:
... bytes_data = uploaded_file.getvalue()
... st.write(bytes_data)
The above code will give you a BytesIO object, which can then be converted into an array representing the image.