Reading 3D numpy array

Question

I have a dataset which comprises of the binary data of pixelated 50x50 images. The array shape is (50, 50, 90245). I want to reach 50x50 pixels of each of the 90245 images. How can I slice the array?

So basically you have 90245 images that are each 50x50, and you want to get them all into a list? So maybe you want to change the shape to (90245, 50, 50) — user17242583
– user17242583, Commented Mar 19, 2022 at 20:55
Actually, the proposed solution in the answer worked for me. When I tried your way, it gave me different data — sonido
– sonido, Commented Mar 19, 2022 at 21:03

BrokenBenchmark · Accepted Answer · 2022-03-19 20:53:06Z

1

If data is the variable storing the image data, and i is the index of the image you want to access, then you can do:

data[:,:,i]

to get the desired image data.

answered Mar 19, 2022 at 20:53

BrokenBenchmark

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Anirudh Ramesh · Accepted Answer · 2022-03-20 05:53:08Z

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If data is the variable storing the image data, and i is the index of the image you want to access, then you can do as @BrokenBenchmark suggested. In case you want a (50,50,1) 3D array as the output, you could do:

data[:,:,i:i+1]

to get the image as a 3D array.

Edit1: If you reshaped your data matrix to be of shape (90245,50,50), you can get the ith image by doing data[i,:,:] or just data[i] to get a (50,50) image. Similarly, to get a (1,50,50) image, you could do data[i:i+1,:,:] or just data[i:i+1].

Edit2: To reshape the array, you could use the swapaxes() function in numpy.

edited Mar 20, 2022 at 5:53

answered Mar 20, 2022 at 5:22

Anirudh Ramesh

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