IdentifiantMot de passe
Loading...
Mot de passe oublié ?Je m'inscris ! (gratuit)
The ImageOps Module
Python Imaging Library Handbook

Prev   Next

The ImageOps Module

(New in 1.1.3) The ImageOps module contains a number of 'ready-made' image processing operations. This module is somewhat experimental, and most operators only work on L and RGB images.

Functions

autocontrast

ImageOps.autocontrast(image, cutoff=0) => image

Maximize (normalize) image contrast. This function calculates a histogram of the input image, removes cutoff percent of the lightest and darkest pixels from the histogram, and remaps the image so that the darkest remaining pixel becomes black (0), and the lightest becomes white (255).

colorize

ImageOps.colorize(image, black, white) => image

Colorize grayscale image. The black and white arguments should be RGB tuples or color names; this function calculates a colour wedge mapping all black pixels in the source image to the first colour, and all white pixels to the second colour.

crop

ImageOps.crop(image, border=0) => image

Remove border pixels from all four edges. This function works on all image modes.

deform

ImageOps.deform(image, deformer, filter=Image.BILINEAR) => image

Deform the image using the given deformer object. The deformer should provide a getmesh method, which returns a MESH list suitable for the Image transform method. See the transform method for details.

equalize

ImageOps.equalize(image) => image

Equalize the image histogram. This function applies a non-linear mapping to the input image, in order to create a uniform distribution of grayscale values in the output image.

expand

ImageOps.expand(image, border=0, fill=0) => image

Add border pixels of border to the image, at all four edges.

fit

ImageOps.fit(image, size, method, bleed, centering) => image

Returns a sized and cropped version of the image, cropped to the requested aspect ratio and size. The size argument is the requested output size in pixels, given as a (width, height) tuple.

The method argument is what resampling method to use. The default is Image.NEAREST (nearest neighbour).

The bleed argument allows you to remove a border around the outside the image (from all four edges). The value is a decimal percentage (use 0.01 for one percent). The default value is 0 (no border).

The centering argument is used to control the cropping position. (0.5, 0.5) is center cropping (i.e. if cropping the width, take 50% off of the left side (and therefore 50% off the right side), and same with top/bottom).

(0.0, 0.0) will crop from the top left corner (i.e. if cropping the width, take all of the crop off of the right side, and if cropping the height, take all of it off the bottom).

(1.0, 0.0) will crop from the bottom left corner, etc. (i.e. if cropping the width, take all of the crop off the left side, and if cropping the height take none from the top (and therefore all off the bottom)).

The fit function was contributed by Kevin Cazabon.

flip

ImageOps.flip(image) => image

Flip the image vertically (top to bottom).

grayscale

ImageOps.grayscale(image) => image

Convert the image to grayscale.

invert

ImageOps.invert(image) => image

Invert (negate) the image.

mirror

ImageOps.mirror(image) => image

Flip image horizontally (left to right).

posterize

ImageOps.posterize(image, bits) => image

Reduce the number of bits for each colour channel.

solarize

ImageOps.solarize(image, threshold=128) => image

Invert all pixel values above the given threshold.