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| import numpy as np | |
| import matplotlib.pyplot as plt | |
| import cv2 as cv | |
| import tensorflow as tf | |
| import tensorflow_hub as hub | |
| model = hub.load('https://www.kaggle.com/models/google/arbitrary-image-stylization-v1/tensorFlow1/256/2') | |
| def load_image(img_bytes): | |
| img = tf.image.decode_image(img_bytes, channels=3) | |
| img = tf.image.resize(img, [256, 256]) | |
| img = tf.image.convert_image_dtype(img, tf.float32) | |
| img = tf.expand_dims(img/255.0, axis=0) | |
| return img | |
| def generate_img(org_img, style_img): | |
| org_img = load_image(org_img) | |
| style_img = load_image(style_img) | |
| gen_img = model(tf.constant(org_img), tf.constant(style_img))[0] | |
| img_arr = (np.array(gen_img)*255).astype(np.uint8)[0] | |
| return img_arr |