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.blend().

Return type

Image

PIL.ImageChops.composite(image1, image2, mask)[source]

Create composite using transparency mask. Alias for PIL.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.

Both of the images must have mode “1”. If you would like to perform a logical AND on an image with a mode other than “1”, try multiply() instead, using a black-and-white mask as the second image.

out = ((image1 and image2) % MAX)
Return type

Image

PIL.ImageChops.logical_or(image1, image2)[source]

Logical OR between two images.

Both of the images must have mode “1”.

out = ((image1 or image2) % MAX)
Return type

Image

PIL.ImageChops.logical_xor(image1, image2)[source]

Logical XOR between two images.

Both of the images must have mode “1”.

out = ((bool(image1) != bool(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.soft_light(image1, image2)[source]

Superimposes two images on top of each other using the Soft Light algorithm

Return type

Image

PIL.ImageChops.hard_light(image1, image2)[source]

Superimposes two images on top of each other using the Hard Light algorithm

Return type

Image

PIL.ImageChops.overlay(image1, image2)[source]

Superimposes two images on top of each other using the Overlay algorithm

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