mirror of
https://github.com/python-pillow/Pillow.git
synced 2024-11-11 04:07:21 +03:00
110 lines
3.9 KiB
ReStructuredText
110 lines
3.9 KiB
ReStructuredText
Concepts
|
||
========
|
||
|
||
The Python Imaging Library handles *raster images*; that is, rectangles of
|
||
pixel data.
|
||
|
||
Bands
|
||
-----
|
||
|
||
An image can consist of one or more bands of data. The Python Imaging Library
|
||
allows you to store several bands in a single image, provided they all have the
|
||
same dimensions and depth.
|
||
|
||
To get the number and names of bands in an image, use the
|
||
:py:meth:`~PIL.Image.Image.getbands` method.
|
||
|
||
.. _concept-modes:
|
||
|
||
Modes
|
||
-----
|
||
|
||
The :term:`mode` of an image defines the type and depth of a pixel in the
|
||
image. The current release supports the following standard modes:
|
||
|
||
* ``1`` (1-bit pixels, black and white, stored with one pixel per byte)
|
||
* ``L`` (8-bit pixels, black and white)
|
||
* ``P`` (8-bit pixels, mapped to any other mode using a color palette)
|
||
* ``RGB`` (3x8-bit pixels, true color)
|
||
* ``RGBA`` (4x8-bit pixels, true color with transparency mask)
|
||
* ``CMYK`` (4x8-bit pixels, color separation)
|
||
* ``YCbCr`` (3x8-bit pixels, color video format)
|
||
* ``LAB`` (3x8-bit pixels, the L*a*b color space)
|
||
* ``HSV`` (3x8-bit pixels, Hue, Saturation, Value color space)
|
||
* ``I`` (32-bit signed integer pixels)
|
||
* ``F`` (32-bit floating point pixels)
|
||
|
||
PIL also provides limited support for a few special modes, including ``LA`` (L
|
||
with alpha), ``RGBX`` (true color with padding) and ``RGBa`` (true color with
|
||
premultiplied alpha). However, PIL doesn’t support user-defined modes; if you
|
||
to handle band combinations that are not listed above, use a sequence of Image
|
||
objects.
|
||
|
||
You can read the mode of an image through the :py:attr:`~PIL.Image.Image.mode`
|
||
attribute. This is a string containing one of the above values.
|
||
|
||
Size
|
||
----
|
||
|
||
You can read the image size through the :py:attr:`~PIL.Image.Image.size`
|
||
attribute. This is a 2-tuple, containing the horizontal and vertical size in
|
||
pixels.
|
||
|
||
Coordinate System
|
||
-----------------
|
||
|
||
The Python Imaging Library uses a Cartesian pixel coordinate system, with (0,0)
|
||
in the upper left corner. Note that the coordinates refer to the implied pixel
|
||
corners; the centre of a pixel addressed as (0, 0) actually lies at (0.5, 0.5).
|
||
|
||
Coordinates are usually passed to the library as 2-tuples (x, y). Rectangles
|
||
are represented as 4-tuples, with the upper left corner given first. For
|
||
example, a rectangle covering all of an 800x600 pixel image is written as (0,
|
||
0, 800, 600).
|
||
|
||
Palette
|
||
-------
|
||
|
||
The palette mode (``P``) uses a color palette to define the actual color for
|
||
each pixel.
|
||
|
||
Info
|
||
----
|
||
|
||
You can attach auxiliary information to an image using the
|
||
:py:attr:`~PIL.Image.Image.info` attribute. This is a dictionary object.
|
||
|
||
How such information is handled when loading and saving image files is up to
|
||
the file format handler (see the chapter on :ref:`image-file-formats`). Most
|
||
handlers add properties to the :py:attr:`~PIL.Image.Image.info` attribute when
|
||
loading an image, but ignore it when saving images.
|
||
|
||
Filters
|
||
-------
|
||
|
||
For geometry operations that may map multiple input pixels to a single output
|
||
pixel, the Python Imaging Library provides four different resampling *filters*.
|
||
|
||
``NEAREST``
|
||
Pick the nearest pixel from the input image. Ignore all other input pixels.
|
||
|
||
``BILINEAR``
|
||
For resize calculate the output pixel value using linear interpolation
|
||
on all pixels that may contribute to the output value.
|
||
For other transformations linear interpolation over a 2x2 environment
|
||
in the input image is used.
|
||
|
||
``BICUBIC``
|
||
For resize calculate the output pixel value using cubic interpolation
|
||
on all pixels that may contribute to the output value.
|
||
For other transformations cubic interpolation over a 4x4 environment
|
||
in the input image is used.
|
||
|
||
``LANCZOS``
|
||
Calculate the output pixel value using a high-quality Lanczos filter (a
|
||
truncated sinc) on all pixels that may contribute to the output value. In
|
||
the current version of PIL, this filter can only be used with the resize
|
||
and thumbnail methods.
|
||
|
||
.. versionadded:: 1.1.3
|