Convert an image to 2D array in python

I want to convert an image to 2D array with 5 columns where each row is of the form [r, g, b, x, y]. x, y is the position of the pixel and r,g,b are the pixel values. (I will be using this array as input to a machine learning model). Is there a more efficient implementation than this in python?

import Image import numpy as np im = Image.open("farm.jpg") col,row = im.size data = np.zeros((row*col, 5)) pixels = im.load() for i in range(row): for j in range(col): r,g,b = pixels[i,j] data[i*col + j,:] = r,g,b,i,j 

4 Answers

I had to write this recently and ended up with

indices = np.dstack(np.indices(im.shape[:2])) data = np.concatenate((im, indices), axis=-1) 

Where im is a numpy array. You are probably better off reading the images straight into numpy arrays with

from scipy.misc import imread im = imread("farm.jpg") 

Or, better still if you have Scikit Image installed

from skimage.io import imread im = imread("farm.jpg") 

I am not sure if this is the very efficient. But here you go, say arr = np.array(im); then you can do something like this.

>>> arr = np.arange(150).reshape(5, 10, 3) >>> x, y, z = arr.shape >>> indices = np.vstack(np.unravel_index(np.arange(x*y), (y, x))).T #or indices = np.hstack((np.repeat(np.arange(y), x)[:,np.newaxis], np.tile(np.arange(x), y)[:,np.newaxis])) >>> np.hstack((arr.reshape(x*y, z), indices)) array([[ 0, 1, 2, 0, 0], [ 3, 4, 5, 0, 1], [ 6, 7, 8, 0, 2], [ 9, 10, 11, 0, 3], [ 12, 13, 14, 0, 4], [ 15, 16, 17, 1, 0], [ 18, 19, 20, 1, 1], [ 21, 22, 23, 1, 2], [ 24, 25, 26, 1, 3], [ 27, 28, 29, 1, 4], [ 30, 31, 32, 2, 0], [ 33, 34, 35, 2, 1], [ 36, 37, 38, 2, 2], ... [129, 130, 131, 8, 3], [132, 133, 134, 8, 4], [135, 136, 137, 9, 0], [138, 139, 140, 9, 1], [141, 142, 143, 9, 2], [144, 145, 146, 9, 3], [147, 148, 149, 9, 4]]) 

I used "+" to combine two tuple, and use .append() to make "data" list.No need to use Numpy here.

row,col = im.size data=[] #r,g,b,i,j pixels=im.load() for i in range(row): for j in range(col): data.append(pixels[i,j]+(i,j)) 

steps are :

1. convert images to grayscale (opencv)

2. convert grayscale to binary image (opencv)

3. convert to binary 2D matrix (scipy , pillow, numpy)

from scipy.ndimage import zoom from PIL import Image import numpy as np srcImage = Image.open("image_in_binary_color.jpg") grayImage = srcImage.convert('L') array = np.array(grayImage) array = zoom(array, 310/174) np.savetxt("binarized.txt", array<128, fmt="%d") print("\n\n Output Stored to binarized.txt.......#") 

4. store it in a file named binarized.txt

This is how i did it :