tfserve_vision8.py

import cv2

def resize_image_array(img, img_size_dims):
    img = cv2.resize(img, dsize=img_size_dims, 
                     interpolation=cv2.INTER_CUBIC)
    img = np.array(img, dtype=np.float32)
    return img

# convert single channel images to 3-channel images    
train_images_3ch = np.stack([train_images]*3, axis=-1)
test_images_3ch = np.stack([test_images]*3, axis=-1)

# resizing images
IMG_DIMS = (32, 32)
train_images_3ch = np.array([resize_image_array(img, img_size_dims=IMG_DIMS) for img in train_images_3ch])
test_images_3ch = np.array([resize_image_array(img, img_size_dims=IMG_DIMS) for img in test_images_3ch])

print('\nTrain_images.shape: {}, of {}'.format(train_images_3ch.shape, train_images_3ch.dtype))
print('Test_images.shape: {}, of {}'.format(test_images_3ch.shape, test_images_3ch.dtype))