from scipy import misc
import numpy as np
from seam_carver import intelligent_resize

rgb_weights = [-3, 1, -3]
mask_weight = 10
cat_img = misc.imread('./demo/cat.png')
mask = np.zeros(cat_img.shape)

resized_img = intelligent_resize(cat_img, 0, -20, rgb_weights, mask, mask_weight)
misc.imsave('./demo/cat_shrunk.png', resized_img)

def intelligent_resize(img, d_rows, d_columns, rgb_weights, mask, mask_weight):
    """
    Changes the size of the provided image in either the vertical or horizontal direction,
    by increasing or decreasing or some combination of the two.

    Args:
        img (n,m,3 numpy matrix): RGB image to be resized.
        d_rows (int): The change (delta) in rows. Positive number indicated insertions, negative is removal.
        d_columns (int): The change (delta) in columns. Positive number indicated insertions, negative is removal.
        rgb_weights (1,3 numpy matrix): Additional weight paramater to be applied to pixels.
        mask (n,m,3 numpy matrix): Mask matrix indicating areas to make more or less likely for removal.
        mask_weight (int): Scalar multiple to be applied to mask.

    Returns:
        n,m,3 numpy matrix: Resized RGB image.
    """