Detection of certain pixels of a grayscale image

Question

I have this code that allows you to detect pixels of a vertain value. Right now I\'m detecting pixels over a certain value (27). My idea would be to still detect them but to det

Answer 1

A few ideas:

• if, as you say, your images are greyscale, then you should process them as single-channel greyscale images, rather than needlessly tripling their memory footprint and tripling the number of comparisons you need to make by promoting them to RGB

• rather than use nested for loops which are miserably slow in Python, either use Numpy or OpenCV to gain 10x to 1000x speedup. Similar example here.

• if you have many images to process, they are all independent, and you have a decent CPU and RAM, consider using multiprocessing to get all your lovely cores processing images in parallel. Simple example here.

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The second suggestion is most likely to yield the best dividend, so I'll expand that:

from PIL import Image
import Numpy as np

# Open an image and ensure greyscale
im = Image.open('image.png').convert('L')

# Make into Numpy array
na = np.array(im)

# Make a new array that is True where pixels between 65..75 and False elsewhere
x = np.logical_and(na>65,na<75)

# Now count the True pixels
result = np.count_nonzero(x)

That yields 2,200 for this 400x100 image: