CODEWITHSUNDEEP
numpy
Soheil_r
Soheil_r

Reputation: 66

Create a 3D numpy array with a loop from multiple 2D images

I want to read from many sample images, and make 2D numpy array that row "i" corresponds to i'th sample, and column j correspond to j'th pixel of image(all pixels of a 12*13 image is saved by a list of 156 numbers)

import numpy as np
images = np.array([])
for Letter in "ABCDEFGHIJKLMNO":
    im = Image.open("ABCDEFGHIJKLMNO\\16\\"+Letter+".bmp")
    sampleimage = list(im.getdata())
    images = np.append(images,[sampleimage])

however I struggling making 2D numpy array. above "images" array become an (1800,) array insted of (11,156) . I tried many differend ways but none of them working properly or efficient (making 2D python list and then converting to numpy array is not efficient. although even that solution doesn't work).

so my question is, what is the best way of creating a 2D numpy array on the fly?

Upvotes: 0

Views: 2113

Answers (1)

Framester
Framester

Reputation: 35451

You are treating the numpy array images like an list. Have a look at numpy.stack. But in my memory the fastest way is to convert each image to an numpy array, aggregate them in a list and then turn the list into an array.

import numpy as np
images = list()
for Letter in "ABCDEFGHIJKLMNO":
    im = Image.open("ABCDEFGHIJKLMNO\\16\\"+Letter+".bmp")
    sampleimage = np.array(im.getdata())
    images.append(sampleimage)
images_array = np.array(images)

In your case the resulting array should have the size [1800,11,156] or [11,156,1800]

Upvotes: 1

Related Questions