How do i make a function that iterate over all the pixels in an image to find a specified colour using numpy

Question

I am trying to make a function that uses a double for loop to traverse all pixels in an image (png) to find all the red pixels. The function should return a 2D array in numpy representing the output binary image and writes the 2D array into a new jpg file. I can only use numpy, matplotlib and skimage.

import numpy as np
from matplotlib import pyplot as mat_plot


def find_red_pixels(map_filename, upper_threshold=100, lower_threshold=50):
    """
    Returns a 2D array in numpy representing the output binary image and writes the 2D array into a file 

    """
    map_filename = 
    mat_plot.imread('./data/map.png')
    map_filename = map_filename * 255 # Scale the color values from [0 – 1] range to [0 – 255] range
    rgb = np.array(map_filename)
    row, col = rgb.shape
    for i in range(0, row):
        for j in range(0, col):
            color = rgb[i,j]  
            if(color[0] > upper_threshold):
                if(color[1] < lower_threshold):
                    if(color[2] < lower_threshold):
                        rgb[i,j] = [0,0,0]
    mat_plot.imsave('map-red-pixels.jpg', map_filename.astype(np.uint8))

This is what i have so far but i am stuck. A pixel is red if r > upper_threshold, g < lower_threshold and b < lower_threshold

Answer 1

The only problem with your code is the syntax:

• Replace '.data/map.png' by map_filename , which is the input of your function.
• Delete the empty line between map_filename= and mat_plot.imread('./data/map.png') .
• Replace map_filename.astype(np.uint8) by rgb.astype(np.uint8) .

That being said...

The point of using NumPy is that you can replace loops by matrix operations, which makes the code faster and easier to read. This is an alternative solution for your problem using NumPy and Matplotlib.

def find_red_pixels(_image: str, up_threshold: float, low_threshold: float) -> None:

    image = plt.imread(_image) * 255

    rgb = image * np.array([[[-1.0, 1.0, 1.0]]])
    threshold = np.array([[[-up_threshold, low_threshold, low_threshold]]])

    new_image = image - image * np.all(rgb - threshold < 0.0, axis=2)[:, :, None]

    plt.imsave("no_red_image.jpg", new_image.astype(np.uint8))

    return None