Construct image with numpy.ndarray manually instead of cv2.imread()

Question

I'm trying to understand how image is stored as RGB value

I just realized image that has been read by cv2.imread() method is just bunch of numbers especially RGB number stored in numpy.ndarray for every pixel when I check with builtin function type()

import cv2
im = cv2.imread('./rgb.png', cv2.IMREAD_UNCHANGED)
print(type(im)) # Output: numpy.ndarray

But I still don't know what representation of each index in that array

To understand it, I want make 3col * 4row image manually with numpy.ndarray

I expect image where:

first column filled with red (255,0,0)
second column filled with green (0,255,0)
third column filled with blue (0,0,255)

for all rows!

Using numpy.ndarray declaration that stored in a variable for example im and successfully saved according what I expect

im = np.ndarray('What should I fill in here?')
cv2.imwrite('success.jpg',im)

Do print(im.shape). You should see something like (480,640,3), which tells you there are 480 rows of 640 columns, where each column is an RGB triple. — Tim Roberts
– Tim Roberts, Commented Apr 3, 2022 at 5:23

Tim Roberts · Accepted Answer · 2022-04-03 05:28:48Z

1

See if this helps. I create an empty numpy array, then I fill each quadrant with a solid color:

import numpy as np
from PIL import Image

im = np.zeros( (480,640,3), dtype=np.uint8 )

im[:240,:320,:] = (255,0,0)
im[:240,320:,:] = (0,255,0)
im[240:,:320,:] = (0,0,255)
im[240:,320:,:] = (255,255,255)
print(im.shape)

p = Image.fromarray(im)
p.save('x.jpg')

Output:

answered Apr 3, 2022 at 5:28

Tim Roberts

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