preproc_funcs.py

# A function to normalize image pixels.
def norm_img(img):
    '''A function to Normalize Images.
    Input:
        img : Original image as numpy array.
    Output: Normailized Image as numpy array
    '''
    img = (img / 127.5) - 1
    return img
def denorm_img(img):
    '''A function to Denormailze, i.e. recreate image from normalized image
    Input:
        img : Normalized image as numpy array.
    Output: Original Image as numpy array
    '''
    img = (img + 1) * 127.5
    return img.astype(np.uint8) 
def sample_from_dataset(batch_size, image_shape, data_dir=None):
    '''Create a batch of image samples by sampling random images from a data directory.
    Resizes the image using image_shape and normalize the images.
    Input:
        batch_size : Sample size required
        image_size : Size that Image should be resized to
        data_dir : Path of directory where training images are placed.
    Output:
        sample : batch of processed images 
    '''
    sample_dim = (batch_size,) + image_shape
    sample = np.empty(sample_dim, dtype=np.float32)
    all_data_dirlist = list(glob.glob(data_dir))
    sample_imgs_paths = np.random.choice(all_data_dirlist,batch_size)
    for index,img_filename in enumerate(sample_imgs_paths):
        image = Image.open(img_filename)
        image = image.resize(image_shape[:-1])
        image = image.convert('RGB') 
        image = np.asarray(image)
        image = norm_img(image)
        sample[index,...] = image
    return sample