Replace certain pixels by integers in numpy array

Question

I have made myself a numpy array from a picture using

from PIL import Image
import numpy as np

image = Image.open(file)
np.array(image)

its shape is (6000, 6000, 4) and in that array I would like to replace pixel values by one number lets say this green pixel [99,214,104,255] will be 1. I have only 4 such pixels I want to replace with a number and all other pixels will be 0. Is there a fast and efficient way to do so and what is the best way to minimize the size of the data. Is it better to save it as dict(), where keys will be x,y and values, will be integers? Or is it better to save the whole array as it is with the shape it has? I only need the color values the rest is not important for me.

I need to process such a picture as fast as possible because there is one picture every 5 minutes and lets say i would like to store 1 year of data. That is why I'd like to make it as efficient as possible time and space-wise.

What is the issue, exactly?

AMC
– AMC

2020-02-08 22:02:45 +00:00
Commented Feb 8, 2020 at 22:02 — AMC
– AMC, Commented Feb 8, 2020 at 22:02

CDJB · Accepted Answer · 2020-02-06 15:02:59Z

1

If I understand the question correctly, you can use np.where for this:

>>> arr = np.array(image)
>>> COLOR = [99,214,104,255]
>>> np.where(np.all(arr == COLOR, axis=-1), 1, 0)

This will produce a 6000*6000 array with 1 if the pixel is the selected colour, or 0 if not.

edited Feb 6, 2020 at 15:02

answered Feb 6, 2020 at 14:35

CDJB

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Comments

marcos · Accepted Answer · 2020-02-06 14:33:55Z

0

How about just storing in a database: the position and value of the pixels you want to modify, the shape of the image, the dtype of the array and the extension (jpg, etc...). You can use that information to build a new image from an array filled with 0.

answered Feb 6, 2020 at 14:33

marcos

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