uploading app with TensorFlow filter to Heroku cause memory exceeded

Recently I’ve uploaded an application to Heroku with TensorFlow,

the problem is the basic memory that you get from Heroku is 512MB,

which causes the server to crash after loading images into the TensorFlow model when the images are high quality.

Process running mem=934M(182.5%)

Error R14 (Memory quota exceeded)

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Process running mem=1108M(216.5%)

Error R15 (Memory quota vastly exceeded)

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Then, a few times I exceeded over 1.2GB when using this model, so I bought 1GB.And then it used over 2.2GB

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CODE:

import tensorflow_hub

import tensorflow

import numpy

import cv2

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model = hub.load(‘https://tfhub.dev/google/magenta/arbitrary-image-stylization-v1-256/2‘)

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def load_image(img_path):

img = tensorflow.io.read_file(img_path)

img = tensorflow.image.decode_image(img, channels=3)

img = tensorflow.image.convert_image_dtype(img, tf.tensorflow)

img = img[tensorflow.newaxis, :]

return img

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def stylize_img(content_image_path,style_image_path):

content_image = load_image(content_image_path)

style_image = load_image(style_image_path)

cv2.imwrite(‘styled_img.jpg’, cv2.cvtColor(np.squeeze(stylized_image)*255, cv2.COLOR_BGR2RGB))

img = tensorflow.io.read_file(‘styled_img.jpg’)

remove(‘styled_img.jpg’)

return img

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how can I solve the memory issue?