Start by getting the height and width of the required patch from the shape of the image. Use loops to crop out a fragment from the image.
One practical application of cropping in OpenCV can be to divide an image into smaller patches. Img(Range(start_row, end_row), Range(start_col, end_col)) Dividing an Image Into Small Patches Using Cropping The following is the C++ syntax to crop an image:
Here too, the image is read in as a 2D matrix, following the same convention described above. In C++, we use the Range() function to crop the image. How to slice a NumPy array? Check out the syntax in this example:Ĭropped = img It goes with the convention that the first dimension of a 2D array represents the rows of the array (where each row represents the y-coordinate of the image). The second dimension is the number of columns or the width of the image. The first dimension is always the number of rows or the height of the image. To slice an array, you need to specify the start and end index of the first as well as the second dimension. 
In Python, you crop the image using the same method as NumPy array slicing.
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