Scattering a mesh grid over a grayscale image

Question

I'm trying to create a numpy mesh grid according to a grayscale image. For example, considering this image

I want to scatter points to get something similar to

in cartesian coordinates. Is there any library for doing such a task or I need to implement something from scratch? Thanks in advance, I will appreciate any help.

Answer 1

Guessing somewhat as to what you mean, here is an approach:

• load image as greyscale
• threshold to pure black and white
• get coordinates of all black pixels
• randomly subsample 0.5% of the coordinates
• create empty output image
• draw white circles on output image's alpha channel at the subsampled locations which will make the black background become visible at those locations

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#!/usr/bin/env python3

import numpy as np
import cv2 as cv

# Load image as greyscale
im = cv.imread('Gkzaa.png', cv.IMREAD_GRAYSCALE)

# Otsu threshold to pure black and pure white, i.e. 0 or 255
_, thresh = cv.threshold(im, 0, 255, cv.THRESH_BINARY+cv.THRESH_OTSU)

# Get X and Y coordinates of all black pixels
Y, X = np.where(thresh==0)
nBlack = len(Y)

# Get indices of 0.5% of those black pixels
indices = np.random.choice(nBlack, size=int(nBlack*0.005), replace=False)

# Form an empty (black) output image and an alpha channel for it
BGR = np.zeros((*im.shape,3), np.uint8)
A   = np.zeros_like(im)

# Draw circles of opacity into the alpha channel at selected indices
for i in indices:
    cv.circle(A, center=(X[i], Y[i]), radius=4, color=255, thickness=cv.FILLED)

# Stack the alpha channel onto the BGR channel to make BGRA and save
res = np.dstack((BGR,A))
cv.imwrite('result.png', res)

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