ImageChops (“Channel Operations”) 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).

PIL.ImageChops.add(image1, image2, scale=1.0, offset=0)

Adds two images, dividing the result by scale and adding the offset. If omitted, scale defaults to 1.0, and offset to 0.0. At least one of the images must have mode “1”.

out = ((image1 + image2) / scale + offset)

Return type:Image

PIL.ImageChops.add_modulo(image1, image2)

Add two images, without clipping the result. At least one of the images must have mode “1”.

out = ((image1 + image2) % MAX)

Return type:Image

PIL.ImageChops.blend(image1, image2, alpha)

Blend images using constant transparency weight. Alias for PIL.Image.Image.blend().

Return type:Image

PIL.ImageChops.composite(image1, image2, mask)

Create composite using transparency mask. Alias for PIL.Image.Image.composite().

Return type:Image

PIL.ImageChops.constant(image, value)

Fill a channel with a given grey level.

Return type:Image

PIL.ImageChops.darker(image1, image2)

Compares the two images, pixel by pixel, and returns a new image containing the darker values. At least one of the images must have mode “1”.

out = min(image1, image2)

Return type:Image

PIL.ImageChops.difference(image1, image2)

Returns the absolute value of the pixel-by-pixel difference between the two images. At least one of the images must have mode “1”.

out = abs(image1 - image2)

Return type:Image

PIL.ImageChops.duplicate(image)

Copy a channel. Alias for PIL.Image.Image.copy().

Return type:Image

PIL.ImageChops.invert(image)

Invert an image (channel).

out = MAX - image

Return type:Image

PIL.ImageChops.lighter(image1, image2)

Compares the two images, pixel by pixel, and returns a new image containing the lighter values. At least one of the images must have mode “1”.

out = max(image1, image2)

Return type:Image

PIL.ImageChops.logical_and(image1, image2)

Logical AND between two images. At least one of the images must have mode “1”.

out = ((image1 and image2) % MAX)

Return type:Image

PIL.ImageChops.logical_or(image1, image2)

Logical OR between two images. At least one of the images must have mode “1”.

out = ((image1 or image2) % MAX)

Return type:Image

PIL.ImageChops.logical_xor(image1, image2)

Logical XOR between two images. At least one of the images must have mode “1”.

out = ((bool(image1) != bool(image2)) % MAX)

Return type:Image

PIL.ImageChops.multiply(image1, image2)

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. At least one of the images must have mode “1”.

out = image1 * image2 / MAX

Return type:Image

PIL.ImageChops.offset(image, xoffset, yoffset=None)

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.

PIL.ImageChops.screen(image1, image2)

Superimposes two inverted images on top of each other. At least one of the images must have mode “1”.

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

Return type:Image

PIL.ImageChops.subtract(image1, image2, scale=1.0, offset=0)

Subtracts two images, dividing the result by scale and adding the offset. If omitted, scale defaults to 1.0, and offset to 0.0. At least one of the images must have mode “1”.

out = ((image1 - image2) / scale + offset)

Return type:Image

PIL.ImageChops.subtract_modulo(image1, image2)

Subtract two images, without clipping the result. At least one of the images must have mode “1”.

out = ((image1 - image2) % MAX)

Return type:Image