The np_pixels[] array contains the values for all the pixels in the image.


example picture for np_pixels[]

def setup():
    tower = py5.load_image("tower.jpg")
    tower.np_pixels[:, ::2, 1:] = [0, 0, 0]
    py5.image(tower, 0, 0)


The np_pixels[] array contains the values for all the pixels in the image. Unlike the one dimensional array Py5Image.pixels[], the np_pixels[] array organizes the color data in a 3 dimensional numpy array. The size of the array’s dimensions are defined by the size of the image. The first dimension is the height, the second is the width, and the third represents the color channels. The color channels are ordered alpha, red, green, blue (ARGB). Every value in np_pixels[] is an integer between 0 and 255.

This numpy array is very similar to the image arrays used by other popular Python image libraries, but note that some of them like opencv will by default order the color channels as RGBA.

Much like the Py5Image.pixels[] array, there are load and update methods that must be called before and after making changes to the data in np_pixels[]. Before accessing np_pixels[], the data must be loaded with the Py5Image.load_np_pixels() method. If this is not done, np_pixels will be equal to None and your code will likely result in Python exceptions. After np_pixels[] has been modified, the Py5Image.update_np_pixels() method must be called to update the content of the display window.

To set the entire contents of np_pixels[] to the contents of another equally sized numpy array, consider using Py5Image.set_np_pixels().

Look at the online “Numpy, Arrays, and Images” Python Ecosystem Integration tutorial for more information about how to make best use of np_pixels[].

Updated on December 25, 2023 17:02:43pm UTC