The ImageChops Module

The ImageChops module contains a number of arithmetical image operations, called channel operations (“chops”). These can be used for various purposes, including special effects, image compositions, algorithmic painting, and more.

For more pre-made operations, see ImageOps.

At this time, most channel operations are only implemented for 8-bit images (e.g. “L” and “RGB”).

Functions #

Most channel operations take one or two image arguments and returns a new image. Unless otherwise noted, the result of a channel operation is always clipped to the range 0 to MAX (which is 255 for all modes supported by the operations in this module).

constant #

ImageChops.constant(image, value) ⇒ image

Return a layer with the same size as the given image, but filled with the given pixel value.

duplicate #

ImageChops.duplicate(image) ⇒ image

Return a copy of the given image.

invert #

ImageChops.invert(image) ⇒ image

Inverts an image.

    out = MAX - image

lighter #

ImageChops.lighter(image1, image2) ⇒ image

Compares the two images, pixel by pixel, and returns a new image containing the lighter values.

    out = max(image1, image2)

darker #

ImageChops.darker(image1, image2) ⇒ image

Compares the two images, pixel by pixel, and returns a new image containing the darker values.

    out = min(image1, image2)

difference #

ImageChops.difference(image1, image2) ⇒ image

Returns the absolute value of the difference between the two images.

    out = abs(image1 - image2)

multiply #

ImageChops.multiply(image1, image2) ⇒ image

Superimposes two images on top of each other. If you multiply an image with a solid black image, the result is black. If you multiply with a solid white image, the image is unaffected.

    out = image1 * image2 / MAX

screen #

ImageChops.screen(image1, image2) ⇒ image

Superimposes two inverted images on top of each other.

    out = MAX - ((MAX - image1) * (MAX - image2) / MAX)

add #

ImageChops.add(image1, image2, scale, offset) ⇒ image

Adds two images, dividing the result by scale and adding the offset. If omitted, scale defaults to 1.0, and offset to 0.0.

    out = (image1 + image2) / scale + offset

subtract #

ImageChops.subtract(image1, image2, scale, offset) ⇒ image

Subtracts two images, dividing the result by scale and adding the offset. If omitted, scale defaults to 1.0, and offset to 0.0.

    out = (image1 - image2) / scale + offset

blend #

ImageChops.blend(image1, image2, alpha) ⇒ image

Same as the blend function in the Image module.

composite #

ImageChops.composite(image1, image2, mask) ⇒ image

Same as the composite function in the Image module.

offset #

ImageChops.offset(image, xoffset, yoffset) ⇒ image

ImageChops.offset(image, offset) ⇒ image

Returns a copy of the image where data has been offset by the given distances. Data wraps around the edges. If yoffset is omitted, it is assumed to be equal to xoffset.