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.
out = ((image1 + image2) / scale + offset)
Return type: Image
-
PIL.ImageChops.add_modulo(image1, image2)¶ Add two images, without clipping the result.
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.darker(image1, image2)¶ 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)¶ 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)¶ Copy a channel. Alias for
PIL.Image.Image.copy().Return type: Image
-
PIL.ImageChops.lighter(image1, image2)¶ 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)¶ Logical AND between two images.
out = ((image1 and image2) % MAX)
Return type: Image
-
PIL.ImageChops.logical_or(image1, image2)¶ Logical OR between two images.
out = ((image1 or 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.
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.
Parameters: - xoffset – The horizontal distance.
- yoffset – The vertical distance. If omitted, both distances are set to the same value.
Return type:
-
PIL.ImageChops.screen(image1, image2)¶ Superimposes two inverted images on top of each other.
out = MAX - ((MAX - image1) * (MAX - image2) / MAX)
Return type: Image