It returns a NumPy array with the dimension passed as n_blocks.Įach element of the array is a block, so to access each block and save it as an image you should write something like the following: result = divide_img_blocks(my_image)Ĭv2.imwrite(f'my_block_) Return np.asarray(splitted_img, dtype=np.ndarray).reshape(n_blocks) Splitted_img =, axis=1) for block in horizontal]

Horizontal = np.array_split(img, n_blocks) Here is another solution, just using NumPy built-in np.array_split : def divide_img_blocks(img, n_blocks=(5, 5)):

Has a function to stitch the image tiles back together (which I haven't yet tested) files apparently must be named after the convention which you will see in the split files after testing the image_slicer.slice function.

Takes that parameter and automagically splits the given image into so many slices, and auto-saves the resultant numbered tiles in the same directory, and finally.

Accepts any even number as an image slice parameter (e.g.

Can invoke an image split with two lines of code.

Image_slicer.slice('huge_test_image.png', 14) Then get and install the image_slicer module via pip, by entering the following command at the console: python -m pip install image_slicerĬopy the image you want to slice into the Python root directory, open a python shell (not the 'command line'), and enter these commands: import image_slicer Open a console and type (if I recall correctly): python get-pip.py install

These instructions are for Windows 7 they may need to be adapted for other OSs.ĭownload the install archive, and extract it to your root Python installation directory. Simpler than all these is to use a wheel someone else invented :) It may be more involved to set up, but then it's a snap to use. It looks like other answers cut in columns and rows. Edit: I believe this answer missed the intent to cut an image into rectangles in columns and rows.

Split picture into grid