Numpy- How to create ROI iteratively in OpenCV python?

Question

I am trying to split an image in a grid of smaller images so that I can process each small image separately. For that I realized that I'll have to define each small image as an ROI and I can use it easily from there.

Now, my grid size is not fixed. I.e, if user inputs 5, I have to make a grid of 5x5.

Iterating over the image pixel by pixel would be slow, so I decided to use Numpy to create ROI by using this construct :

#Assuming user entered grid size =5
roiwidth=w/5
roiheight=h/5   
roi0=img[0:roiheight,0:roiwidth]

This would be my first slice. h and w are height and width of the image respectively. For the next slice I'd have to do:

roi1=img[0:roiheight,roiwidth+1:2*roiwidth]   

While my last roi will be:

roi25=img[4*roiheight+1:5*roiheight, 4*roiwidth+1:5*roiwidth]

But I need to do it iteratively, and cannot figure out the correct way to do that. I don't want to iterate over the image pixel by pixel and need it to be dynamic

EDIT: I am iterating like this now:

import cv2
import numpy

img=cv2.imread('01.jpg')
h,w,chan=img.shape
rh=h/5
rw=w/5
z={}
count=0
for i in range (0,5):
    for j in range (0,5):
        yl=i*rh
        yh=(i+1)*rh
        xl=j*rw
        xh=(j+1)*rw
        z[count]=img[yl:yh,xl:xh]
        count=count+1

But I don't know whether this is the most efficient way of doing this.

Answer 1

If you want to split your image using Numpy functions, take a look at numpy.array_split.

In your case you would write something like this:

z = {}
count = 0
split1 = np.array_split(img, rh)
for sub in split1:
    split2 = np.array_split(sub, rw, 1)
    for sub2 in split2:
        z[count] = sub2
        count++