Created
August 16, 2021 16:21
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import tensorflow as tf | |
import tensorflow_hub as hub | |
import matplotlib.pyplot as plt | |
import numpy as np | |
import PIL.Image | |
def load_img(path_to_img): | |
max_dim = 512 | |
img = tf.io.read_file(path_to_img) | |
img = tf.image.decode_image(img, channels=3) | |
img = tf.image.convert_image_dtype(img, tf.float32) | |
shape = tf.cast(tf.shape(img)[:-1], tf.float32) | |
long_dim = max(shape) | |
scale = max_dim / long_dim | |
new_shape = tf.cast(shape * scale, tf.int32) | |
img = tf.image.resize(img, new_shape) | |
img = img[tf.newaxis, :] | |
return img | |
def imshow(image, title=None): | |
if len(image.shape) > 3: | |
image = tf.squeeze(image, axis=0) | |
plt.imshow(image) | |
if title: | |
plt.title(title) | |
def tensor_to_image(tensor): | |
tensor = tensor*255 | |
tensor = np.array(tensor, dtype=np.uint8) | |
if np.ndim(tensor)>3: | |
assert tensor.shape[0] == 1 | |
tensor = tensor[0] | |
return PIL.Image.fromarray(tensor) |
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