# 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)[source]

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)

Return type: Image
PIL.ImageChops.add_modulo(image1, image2)[source]

Add two images, without clipping the result.

out = ((image1 + image2) % MAX)

Return type: Image
PIL.ImageChops.blend(image1, image2, alpha)[source]

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

Return type: Image
PIL.ImageChops.composite(image1, image2, mask)[source]

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

Return type: Image
PIL.ImageChops.constant(image, value)[source]

Fill a channel with a given grey level.

Return type: Image
PIL.ImageChops.darker(image1, image2)[source]

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

out = min(image1, image2)

Return type: Image
PIL.ImageChops.difference(image1, image2)[source]

Returns the absolute value of the pixel-by-pixel difference between the two images.

out = abs(image1 - image2)

Return type: Image
PIL.ImageChops.duplicate(image)[source]

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

Return type: Image
PIL.ImageChops.invert(image)[source]

Invert an image (channel).

out = MAX - image

Return type: Image
PIL.ImageChops.lighter(image1, image2)[source]

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

out = max(image1, image2)

Return type: Image
PIL.ImageChops.logical_and(image1, image2)[source]

Logical AND between two images.

out = ((image1 and image2) % MAX)

Return type: Image
PIL.ImageChops.logical_or(image1, image2)[source]

Logical OR between two images.

out = ((image1 or image2) % MAX)

Return type: Image
PIL.ImageChops.multiply(image1, image2)[source]

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

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)[source]

Superimposes two inverted images on top of each other.

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

Return type: Image
PIL.ImageChops.subtract(image1, image2, scale=1.0, offset=0)[source]

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)

Return type: Image
PIL.ImageChops.subtract_modulo(image1, image2)[source]

Subtract two images, without clipping the result.

out = ((image1 - image2) % MAX)

Return type: Image