In [1]:

    

import numpy as np
from PIL import Image


    

In [2]:

    

src = np.array(Image.open('data/src/lena.jpg'))
mask = np.array(Image.open('data/src/horse_r.png').resize(src.shape[1::-1], Image.BILINEAR))


    

In [3]:

    

print(mask.dtype, mask.min(), mask.max())


    

    




uint8 0 255

In [4]:

    

mask = mask / 255


    

In [5]:

    

print(mask.dtype, mask.min(), mask.max())


    

    




float64 0.0 1.0

In [6]:

    

dst = src * mask


    

In [7]:

    

Image.fromarray(dst.astype(np.uint8)).save('data/dst/numpy_image_mask.jpg')


    

In [8]:

    

mask = np.array(Image.open('data/src/horse_r.png').convert('L').resize(src.shape[1::-1], Image.BILINEAR))


    

In [9]:

    

print(mask.shape)


    

    




(225, 400)

In [10]:

    

mask = mask / 255


    

In [11]:

    

# dst = src * mask
# ValueError: operands could not be broadcast together with shapes (225,400,3) (225,400)


    

In [12]:

    

# mask = mask[:, :, np.newaxis]


    

In [13]:

    

mask = mask.reshape(*mask.shape, 1)


    

In [14]:

    

print(mask.shape)


    

    




(225, 400, 1)

In [15]:

    

dst = src * mask


    

In [16]:

    

Image.fromarray(dst.astype(np.uint8)).save('data/dst/numpy_image_mask_l.jpg')