Machine Learning Prerequisites (Numpy)

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Numpy - Arrays - Example - Extracting a portion of an image using array slicing

Let us extract a portion of an image using NumPy array slicing.

We can represent an image by arranging its pixel values in the form of a NumPy array.

Then, by slicing this NumPy array in desired dimensions of the pixel locations of the image, we can extract the desired portion of this image.


we can extract a portion of china image by specifying the pixel locations (in NumPy array) of this image portion.

Let us say dimensions of china image (china.shape) is 427 x 640 x 3. And we want to extract the portion of this image, and dimensions of this portion are - row numbers from 150 to 220 and column numbers from 130 to 250 in the 'china' NumPy array.

To extract this portion, we can simply use the below code statement

image = china[150:220, 130:250]

Here, china is the NumPy array representing the image of china, and image is the desired portion of this image, that we wanted to extract.

Numpy - Arrays - Example


Please follow the below steps:

(1) Please import load_sample_image from sklearn.datasets

(2) Please load china.jpg file using load_sample_image() function

china = load_sample_image("<<your code comes here>>")

(3) Please extract a portion of china image by extracting row numbers from 120 to 250 and column numbers from 110 to 230, and store this image portion in a variable called 'portion'

portion = china[<<your code comes here>>]

(4) Check the dimensions of the portion image by printing the shape of the portion array

print(<<your code comes here>>)
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