Gecko [ www.leshallesdegournay.geraud-market.com ]

Name	Size	Permission	Date
ArgImagePlugin.py	12.17 KB	-rw-r--r--	2024-02-22 08:02
ArgImagePlugin.pyc	12.79 KB	-rw-r--r--	2024-02-22 08:02
ArgImagePlugin.pyo	12.79 KB	-rw-r--r--	2024-02-22 08:02
BdfFontFile.py	3.27 KB	-rw-r--r--	2024-02-22 08:02
BdfFontFile.pyc	2.97 KB	-rw-r--r--	2024-02-22 08:02
BdfFontFile.pyo	2.97 KB	-rw-r--r--	2024-02-22 08:02
BmpImagePlugin.py	6.52 KB	-rw-r--r--	2024-02-22 08:02
BmpImagePlugin.pyc	5.34 KB	-rw-r--r--	2024-02-22 08:02
BmpImagePlugin.pyo	5.34 KB	-rw-r--r--	2024-02-22 08:02
BufrStubImagePlugin.py	1.46 KB	-rw-r--r--	2024-02-22 08:02
BufrStubImagePlugin.pyc	2 KB	-rw-r--r--	2024-02-22 08:02
BufrStubImagePlugin.pyo	2 KB	-rw-r--r--	2024-02-22 08:02
ContainerIO.py	2.54 KB	-rw-r--r--	2024-02-22 08:02
ContainerIO.pyc	2.09 KB	-rw-r--r--	2024-02-22 08:02
ContainerIO.pyo	2.09 KB	-rw-r--r--	2024-02-22 08:02
CurImagePlugin.py	1.89 KB	-rw-r--r--	2024-02-22 08:02
CurImagePlugin.pyc	1.64 KB	-rw-r--r--	2024-02-22 08:02
CurImagePlugin.pyo	1.64 KB	-rw-r--r--	2024-02-22 08:02
DcxImagePlugin.py	1.76 KB	-rw-r--r--	2024-02-22 08:02
DcxImagePlugin.pyc	1.9 KB	-rw-r--r--	2024-02-22 08:02
DcxImagePlugin.pyo	1.9 KB	-rw-r--r--	2024-02-22 08:02
EpsImagePlugin.py	10.64 KB	-rw-r--r--	2024-02-22 08:02
EpsImagePlugin.pyc	9.44 KB	-rw-r--r--	2024-02-22 08:02
EpsImagePlugin.pyo	9.44 KB	-rw-r--r--	2024-02-22 08:02
ExifTags.py	4.69 KB	-rw-r--r--	2024-02-22 08:02
ExifTags.pyc	4.81 KB	-rw-r--r--	2024-02-22 08:02
ExifTags.pyo	4.81 KB	-rw-r--r--	2024-02-22 08:02
FitsStubImagePlugin.py	1.61 KB	-rw-r--r--	2024-02-22 08:02
FitsStubImagePlugin.pyc	2.01 KB	-rw-r--r--	2024-02-22 08:02
FitsStubImagePlugin.pyo	2.01 KB	-rw-r--r--	2024-02-22 08:02
FliImagePlugin.py	3.37 KB	-rw-r--r--	2024-02-22 08:02
FliImagePlugin.pyc	3.5 KB	-rw-r--r--	2024-02-22 08:02
FliImagePlugin.pyo	3.5 KB	-rw-r--r--	2024-02-22 08:02
FontFile.py	3.32 KB	-rw-r--r--	2024-02-22 08:02
FontFile.pyc	3.5 KB	-rw-r--r--	2024-02-22 08:02
FontFile.pyo	3.5 KB	-rw-r--r--	2024-02-22 08:02
FpxImagePlugin.py	6.04 KB	-rw-r--r--	2024-02-22 08:02
FpxImagePlugin.pyc	4.55 KB	-rw-r--r--	2024-02-22 08:02
FpxImagePlugin.pyo	4.55 KB	-rw-r--r--	2024-02-22 08:02
GbrImagePlugin.py	1.54 KB	-rw-r--r--	2024-02-22 08:02
GbrImagePlugin.pyc	1.81 KB	-rw-r--r--	2024-02-22 08:02
GbrImagePlugin.pyo	1.81 KB	-rw-r--r--	2024-02-22 08:02
GdImageFile.py	2.11 KB	-rw-r--r--	2024-02-22 08:02
GdImageFile.pyc	1.68 KB	-rw-r--r--	2024-02-22 08:02
GdImageFile.pyo	1.68 KB	-rw-r--r--	2024-02-22 08:02
GifImagePlugin.py	11.09 KB	-rw-r--r--	2024-02-22 08:02
GifImagePlugin.pyc	7.95 KB	-rw-r--r--	2024-02-22 08:02
GifImagePlugin.pyo	7.95 KB	-rw-r--r--	2024-02-22 08:02
GimpGradientFile.py	3.1 KB	-rw-r--r--	2024-02-22 08:02
GimpGradientFile.pyc	3.61 KB	-rw-r--r--	2024-02-22 08:02
GimpGradientFile.pyo	3.61 KB	-rw-r--r--	2024-02-22 08:02
GimpPaletteFile.py	1.3 KB	-rw-r--r--	2024-02-22 08:02
GimpPaletteFile.pyc	1.47 KB	-rw-r--r--	2024-02-22 08:02
GimpPaletteFile.pyo	1.47 KB	-rw-r--r--	2024-02-22 08:02
GribStubImagePlugin.py	1.47 KB	-rw-r--r--	2024-02-22 08:02
GribStubImagePlugin.pyc	2.01 KB	-rw-r--r--	2024-02-22 08:02
GribStubImagePlugin.pyo	2.01 KB	-rw-r--r--	2024-02-22 08:02
Hdf5StubImagePlugin.py	1.51 KB	-rw-r--r--	2024-02-22 08:02
Hdf5StubImagePlugin.pyc	2.01 KB	-rw-r--r--	2024-02-22 08:02
Hdf5StubImagePlugin.pyo	2.01 KB	-rw-r--r--	2024-02-22 08:02
IcnsImagePlugin.py	6.09 KB	-rw-r--r--	2024-02-22 08:02
IcnsImagePlugin.pyc	6.56 KB	-rw-r--r--	2024-02-22 08:02
IcnsImagePlugin.pyo	6.56 KB	-rw-r--r--	2024-02-22 08:02
IcoImagePlugin.py	1.84 KB	-rw-r--r--	2024-02-22 08:02
IcoImagePlugin.pyc	1.59 KB	-rw-r--r--	2024-02-22 08:02
IcoImagePlugin.pyo	1.59 KB	-rw-r--r--	2024-02-22 08:02
ImImagePlugin.py	9.8 KB	-rw-r--r--	2024-02-22 08:02
ImImagePlugin.pyc	8.04 KB	-rw-r--r--	2024-02-22 08:02
ImImagePlugin.pyo	8.04 KB	-rw-r--r--	2024-02-22 08:02
Image.py	67.81 KB	-rw-r--r--	2024-02-22 08:02
Image.pyc	39.15 KB	-rw-r--r--	2024-02-22 08:02
Image.pyo	39.15 KB	-rw-r--r--	2024-02-22 08:02
ImageChops.py	7.25 KB	-rw-r--r--	2024-02-22 08:02
ImageChops.pyc	4.97 KB	-rw-r--r--	2024-02-22 08:02
ImageChops.pyo	4.97 KB	-rw-r--r--	2024-02-22 08:02
ImageCms.py	29.63 KB	-rw-r--r--	2024-02-22 08:02
ImageCms.pyc	12.13 KB	-rw-r--r--	2024-02-22 08:02
ImageCms.pyo	12.13 KB	-rw-r--r--	2024-02-22 08:02
ImageColor.py	7.04 KB	-rw-r--r--	2024-02-22 08:02
ImageColor.pyc	6.92 KB	-rw-r--r--	2024-02-22 08:02
ImageColor.pyo	6.92 KB	-rw-r--r--	2024-02-22 08:02
ImageDraw.py	11.36 KB	-rw-r--r--	2024-02-22 08:02
ImageDraw.pyc	8.63 KB	-rw-r--r--	2024-02-22 08:02
ImageDraw.pyo	8.63 KB	-rw-r--r--	2024-02-22 08:02
ImageDraw2.py	3.11 KB	-rw-r--r--	2024-02-22 08:02
ImageDraw2.pyc	5.1 KB	-rw-r--r--	2024-02-22 08:02
ImageDraw2.pyo	5.1 KB	-rw-r--r--	2024-02-22 08:02
ImageEnhance.py	2.71 KB	-rw-r--r--	2024-02-22 08:02
ImageEnhance.pyc	2.54 KB	-rw-r--r--	2024-02-22 08:02
ImageEnhance.pyo	2.54 KB	-rw-r--r--	2024-02-22 08:02
ImageFile.py	14.72 KB	-rw-r--r--	2024-02-22 08:02
ImageFile.pyc	9.74 KB	-rw-r--r--	2024-02-22 08:02
ImageFile.pyo	9.64 KB	-rw-r--r--	2024-02-22 08:02
ImageFileIO.py	968 B	-rw-r--r--	2024-02-22 08:02
ImageFileIO.pyc	614 B	-rw-r--r--	2024-02-22 08:02
ImageFileIO.pyo	614 B	-rw-r--r--	2024-02-22 08:02
ImageFilter.py	6.51 KB	-rw-r--r--	2024-02-22 08:02
ImageFilter.pyc	8.7 KB	-rw-r--r--	2024-02-22 08:02
ImageFilter.pyo	8.7 KB	-rw-r--r--	2024-02-22 08:02
ImageFont.py	17.38 KB	-rw-r--r--	2024-02-22 08:02
ImageFont.pyc	15.96 KB	-rw-r--r--	2024-02-22 08:02
ImageFont.pyo	15.96 KB	-rw-r--r--	2024-02-22 08:02
ImageGL.py	483 B	-rw-r--r--	2024-02-22 08:02
ImageGL.pyc	394 B	-rw-r--r--	2024-02-22 08:02
ImageGL.pyo	394 B	-rw-r--r--	2024-02-22 08:02
ImageGrab.py	1.85 KB	-rw-r--r--	2024-02-22 08:02
ImageGrab.pyc	1.07 KB	-rw-r--r--	2024-02-22 08:02
ImageGrab.pyo	1.07 KB	-rw-r--r--	2024-02-22 08:02
ImageMath.py	7.66 KB	-rw-r--r--	2024-02-22 08:02
ImageMath.pyc	10.94 KB	-rw-r--r--	2024-02-22 08:02
ImageMath.pyo	10.94 KB	-rw-r--r--	2024-02-22 08:02
ImageMode.py	1.27 KB	-rw-r--r--	2024-02-22 08:02
ImageMode.pyc	1.34 KB	-rw-r--r--	2024-02-22 08:02
ImageMode.pyo	1.34 KB	-rw-r--r--	2024-02-22 08:02
ImageOps.py	13 KB	-rw-r--r--	2024-02-22 08:02
ImageOps.pyc	8.43 KB	-rw-r--r--	2024-02-22 08:02
ImageOps.pyo	8.38 KB	-rw-r--r--	2024-02-22 08:02
ImagePalette.py	5.4 KB	-rw-r--r--	2024-02-22 08:02
ImagePalette.pyc	5.7 KB	-rw-r--r--	2024-02-22 08:02
ImagePalette.pyo	5.7 KB	-rw-r--r--	2024-02-22 08:02
ImagePath.py	1.32 KB	-rw-r--r--	2024-02-22 08:02
ImagePath.pyc	1.36 KB	-rw-r--r--	2024-02-22 08:02
ImagePath.pyo	1.36 KB	-rw-r--r--	2024-02-22 08:02
ImageSequence.py	792 B	-rw-r--r--	2024-02-22 08:02
ImageSequence.pyc	903 B	-rw-r--r--	2024-02-22 08:02
ImageSequence.pyo	903 B	-rw-r--r--	2024-02-22 08:02
ImageShow.py	4.45 KB	-rw-r--r--	2024-02-22 08:02
ImageShow.pyc	5.22 KB	-rw-r--r--	2024-02-22 08:02
ImageShow.pyo	5.22 KB	-rw-r--r--	2024-02-22 08:02
ImageStat.py	4.22 KB	-rw-r--r--	2024-02-22 08:02
ImageStat.pyc	4.66 KB	-rw-r--r--	2024-02-22 08:02
ImageStat.pyo	4.66 KB	-rw-r--r--	2024-02-22 08:02
ImageTransform.py	2.8 KB	-rw-r--r--	2024-02-22 08:02
ImageTransform.pyc	1.87 KB	-rw-r--r--	2024-02-22 08:02
ImageTransform.pyo	1.87 KB	-rw-r--r--	2024-02-22 08:02
ImageWin.py	6.73 KB	-rw-r--r--	2024-02-22 08:02
ImageWin.pyc	6.55 KB	-rw-r--r--	2024-02-22 08:02
ImageWin.pyo	6.55 KB	-rw-r--r--	2024-02-22 08:02
ImtImagePlugin.py	2.17 KB	-rw-r--r--	2024-02-22 08:02
ImtImagePlugin.pyc	1.56 KB	-rw-r--r--	2024-02-22 08:02
ImtImagePlugin.pyo	1.56 KB	-rw-r--r--	2024-02-22 08:02
IptcImagePlugin.py	7.52 KB	-rw-r--r--	2024-02-22 08:02
IptcImagePlugin.pyc	6.29 KB	-rw-r--r--	2024-02-22 08:02
IptcImagePlugin.pyo	6.29 KB	-rw-r--r--	2024-02-22 08:02
JpegImagePlugin.py	19.42 KB	-rw-r--r--	2024-02-22 08:02
JpegImagePlugin.pyc	16.24 KB	-rw-r--r--	2024-02-22 08:02
JpegImagePlugin.pyo	16.24 KB	-rw-r--r--	2024-02-22 08:02
JpegPresets.py	12.05 KB	-rw-r--r--	2024-02-22 08:02
JpegPresets.pyc	6.3 KB	-rw-r--r--	2024-02-22 08:02
JpegPresets.pyo	6.3 KB	-rw-r--r--	2024-02-22 08:02
McIdasImagePlugin.py	1.69 KB	-rw-r--r--	2024-02-22 08:02
McIdasImagePlugin.pyc	1.67 KB	-rw-r--r--	2024-02-22 08:02
McIdasImagePlugin.pyo	1.67 KB	-rw-r--r--	2024-02-22 08:02
MicImagePlugin.py	2.12 KB	-rw-r--r--	2024-02-22 08:02
MicImagePlugin.pyc	2.09 KB	-rw-r--r--	2024-02-22 08:02
MicImagePlugin.pyo	2.09 KB	-rw-r--r--	2024-02-22 08:02
MpegImagePlugin.py	1.79 KB	-rw-r--r--	2024-02-22 08:02
MpegImagePlugin.pyc	2.49 KB	-rw-r--r--	2024-02-22 08:02
MpegImagePlugin.pyo	2.49 KB	-rw-r--r--	2024-02-22 08:02
MspImagePlugin.py	2.12 KB	-rw-r--r--	2024-02-22 08:02
MspImagePlugin.pyc	2.39 KB	-rw-r--r--	2024-02-22 08:02
MspImagePlugin.pyo	2.39 KB	-rw-r--r--	2024-02-22 08:02
OleFileIO.py	15.92 KB	-rw-r--r--	2024-02-22 08:02
OleFileIO.pyc	12.62 KB	-rw-r--r--	2024-02-22 08:02
OleFileIO.pyo	12.62 KB	-rw-r--r--	2024-02-22 08:02
PSDraw.py	5.57 KB	-rw-r--r--	2024-02-22 08:02
PSDraw.pyc	5.5 KB	-rw-r--r--	2024-02-22 08:02
PSDraw.pyo	5.5 KB	-rw-r--r--	2024-02-22 08:02
PaletteFile.py	1.08 KB	-rw-r--r--	2024-02-22 08:02
PaletteFile.pyc	1.31 KB	-rw-r--r--	2024-02-22 08:02
PaletteFile.pyo	1.31 KB	-rw-r--r--	2024-02-22 08:02
PalmImagePlugin.py	9.33 KB	-rw-r--r--	2024-02-22 08:02
PalmImagePlugin.pyc	9.39 KB	-rw-r--r--	2024-02-22 08:02
PalmImagePlugin.pyo	9.39 KB	-rw-r--r--	2024-02-22 08:02
PcdImagePlugin.py	1.77 KB	-rw-r--r--	2024-02-22 08:02
PcdImagePlugin.pyc	1.73 KB	-rw-r--r--	2024-02-22 08:02
PcdImagePlugin.pyo	1.73 KB	-rw-r--r--	2024-02-22 08:02
PcfFontFile.py	6.03 KB	-rw-r--r--	2024-02-22 08:02
PcfFontFile.pyc	6.2 KB	-rw-r--r--	2024-02-22 08:02
PcfFontFile.pyo	6.2 KB	-rw-r--r--	2024-02-22 08:02
PcxImagePlugin.py	4.53 KB	-rw-r--r--	2024-02-22 08:02
PcxImagePlugin.pyc	3.84 KB	-rw-r--r--	2024-02-22 08:02
PcxImagePlugin.pyo	3.78 KB	-rw-r--r--	2024-02-22 08:02
PdfImagePlugin.py	5.73 KB	-rw-r--r--	2024-02-22 08:02
PdfImagePlugin.pyc	5.04 KB	-rw-r--r--	2024-02-22 08:02
PdfImagePlugin.pyo	5.04 KB	-rw-r--r--	2024-02-22 08:02
PixarImagePlugin.py	1.57 KB	-rw-r--r--	2024-02-22 08:02
PixarImagePlugin.pyc	1.24 KB	-rw-r--r--	2024-02-22 08:02
PixarImagePlugin.pyo	1.24 KB	-rw-r--r--	2024-02-22 08:02
PngImagePlugin.py	18.19 KB	-rw-r--r--	2024-02-22 08:02
PngImagePlugin.pyc	17.9 KB	-rw-r--r--	2024-02-22 08:02
PngImagePlugin.pyo	17.9 KB	-rw-r--r--	2024-02-22 08:02
PpmImagePlugin.py	3.23 KB	-rw-r--r--	2024-02-22 08:02
PpmImagePlugin.pyc	2.94 KB	-rw-r--r--	2024-02-22 08:02
PpmImagePlugin.pyo	2.94 KB	-rw-r--r--	2024-02-22 08:02
PsdImagePlugin.py	7.28 KB	-rw-r--r--	2024-02-22 08:02
PsdImagePlugin.pyc	6.17 KB	-rw-r--r--	2024-02-22 08:02
PsdImagePlugin.pyo	6.17 KB	-rw-r--r--	2024-02-22 08:02
SgiImagePlugin.py	2.05 KB	-rw-r--r--	2024-02-22 08:02
SgiImagePlugin.pyc	2 KB	-rw-r--r--	2024-02-22 08:02
SgiImagePlugin.pyo	2 KB	-rw-r--r--	2024-02-22 08:02
SunImagePlugin.py	1.9 KB	-rw-r--r--	2024-02-22 08:02
SunImagePlugin.pyc	1.99 KB	-rw-r--r--	2024-02-22 08:02
SunImagePlugin.pyo	1.99 KB	-rw-r--r--	2024-02-22 08:02
TarIO.py	1.19 KB	-rw-r--r--	2024-02-22 08:02
TarIO.pyc	1.08 KB	-rw-r--r--	2024-02-22 08:02
TarIO.pyo	1.08 KB	-rw-r--r--	2024-02-22 08:02
TgaImagePlugin.py	4.83 KB	-rw-r--r--	2024-02-22 08:02
TgaImagePlugin.pyc	4.14 KB	-rw-r--r--	2024-02-22 08:02
TgaImagePlugin.pyo	4.14 KB	-rw-r--r--	2024-02-22 08:02
TiffImagePlugin.py	34.05 KB	-rw-r--r--	2024-02-22 08:02
TiffImagePlugin.pyc	26.2 KB	-rw-r--r--	2024-02-22 08:02
TiffImagePlugin.pyo	26.07 KB	-rw-r--r--	2024-02-22 08:02
TiffTags.py	4.53 KB	-rw-r--r--	2024-02-22 08:02
TiffTags.pyc	4.9 KB	-rw-r--r--	2024-02-22 08:02
TiffTags.pyo	4.9 KB	-rw-r--r--	2024-02-22 08:02
WalImageFile.py	5.39 KB	-rw-r--r--	2024-02-22 08:02
WalImageFile.pyc	2.13 KB	-rw-r--r--	2024-02-22 08:02
WalImageFile.pyo	2.13 KB	-rw-r--r--	2024-02-22 08:02
WebPImagePlugin.py	978 B	-rw-r--r--	2024-02-22 08:02
WebPImagePlugin.pyc	1.86 KB	-rw-r--r--	2024-02-22 08:02
WebPImagePlugin.pyo	1.86 KB	-rw-r--r--	2024-02-22 08:02
WmfImagePlugin.py	4 KB	-rw-r--r--	2024-02-22 08:02
WmfImagePlugin.pyc	3.97 KB	-rw-r--r--	2024-02-22 08:02
WmfImagePlugin.pyo	3.97 KB	-rw-r--r--	2024-02-22 08:02
XVThumbImagePlugin.py	1.8 KB	-rw-r--r--	2024-02-22 08:02
XVThumbImagePlugin.pyc	1.6 KB	-rw-r--r--	2024-02-22 08:02
XVThumbImagePlugin.pyo	1.6 KB	-rw-r--r--	2024-02-22 08:02
XbmImagePlugin.py	2.39 KB	-rw-r--r--	2024-02-22 08:02
XbmImagePlugin.pyc	2.52 KB	-rw-r--r--	2024-02-22 08:02
XbmImagePlugin.pyo	2.52 KB	-rw-r--r--	2024-02-22 08:02
XpmImagePlugin.py	3.01 KB	-rw-r--r--	2024-02-22 08:02
XpmImagePlugin.pyc	2.8 KB	-rw-r--r--	2024-02-22 08:02
XpmImagePlugin.pyo	2.8 KB	-rw-r--r--	2024-02-22 08:02
__init__.py	183 B	-rw-r--r--	2024-02-22 08:02
__init__.pyc	137 B	-rw-r--r--	2024-02-22 08:02
__init__.pyo	137 B	-rw-r--r--	2024-02-22 08:02
_binary.py	1.09 KB	-rw-r--r--	2024-02-22 08:02
_binary.pyc	2.52 KB	-rw-r--r--	2024-02-22 08:02
_binary.pyo	2.52 KB	-rw-r--r--	2024-02-22 08:02

Rename

#
# The Python Imaging Library.
# $Id$
#
# standard image operations
#
# History:
# 2001-10-20 fl   Created
# 2001-10-23 fl   Added autocontrast operator
# 2001-12-18 fl   Added Kevin's fit operator
# 2004-03-14 fl   Fixed potential division by zero in equalize
# 2005-05-05 fl   Fixed equalize for low number of values
#
# Copyright (c) 2001-2004 by Secret Labs AB
# Copyright (c) 2001-2004 by Fredrik Lundh
#
# See the README file for information on usage and redistribution.
#

from PIL import Image
import operator
from functools import reduce

##
# (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.
#
# @since 1.1.3
##

#
# helpers

def _border(border):
    if isinstance(border, tuple):
        if len(border) == 2:
            left, top = right, bottom = border
        elif len(border) == 4:
            left, top, right, bottom = border
    else:
        left = top = right = bottom = border
    return left, top, right, bottom

def _color(color, mode):
    if Image.isStringType(color):
        from PIL import ImageColor
        color = ImageColor.getcolor(color, mode)
    return color

def _lut(image, lut):
    if image.mode == "P":
        # FIXME: apply to lookup table, not image data
        raise NotImplementedError("mode P support coming soon")
    elif image.mode in ("L", "RGB"):
        if image.mode == "RGB" and len(lut) == 256:
            lut = lut + lut + lut
        return image.point(lut)
    else:
        raise IOError("not supported for this image mode")

#
# actions

##
# 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 pixel becomes black (0), and the lightest
# becomes white (255).
#
# @param image The image to process.
# @param cutoff How many percent to cut off from the histogram.
# @param ignore The background pixel value (use None for no background).
# @return An image.

def autocontrast(image, cutoff=0, ignore=None):
 "Maximize image contrast, based on histogram"
 histogram = image.histogram()
 lut = []
 for layer in range(0, len(histogram), 256):
 h = histogram[layer:layer+256]
 if ignore is not None:
 # get rid of outliers
 try:
 h[ignore] = 0
 except TypeError:
 # assume sequence
 for ix in ignore:
 h[ix] = 0
 if cutoff:
 # cut off pixels from both ends of the histogram
 # get number of pixels
 n = 0
 for ix in range(256):
 n = n + h[ix]
 # remove cutoff% pixels from the low end
 cut = n * cutoff // 100
 for lo in range(256):
 if cut > h[lo]:
 cut = cut - h[lo]
 h[lo] = 0
 else:
 h[lo] = h[lo] - cut
 cut = 0
 if cut <= 0:
 break
 # remove cutoff% samples from the hi end
 cut = n * cutoff // 100
 for hi in range(255, -1, -1):
 if cut > h[hi]:
 cut = cut - h[hi]
 h[hi] = 0
 else:
 h[hi] = h[hi] - cut
 cut = 0
 if cut <= 0:
 break
 # find lowest/highest samples after preprocessing
 for lo in range(256):
 if h[lo]:
 break
 for hi in range(255, -1, -1):
 if h[hi]:
 break
 if hi <= lo:
 # don't bother
 lut.extend(list(range(256)))
 else:
 scale = 255.0 / (hi - lo)
 offset = -lo * scale
 for ix in range(256):
 ix = int(ix * scale + offset)
 if ix < 0:
 ix = 0
 elif ix > 255:
 ix = 255
 lut.append(ix)
 return _lut(image, lut)

##
# Colorize grayscale image. The black and white
# arguments should be RGB tuples; 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.
#
# @param image The image to colourize.
# @param black The colour to use for black input pixels.
# @param white The colour to use for white input pixels.
# @return An image.

def colorize(image, black, white):
    "Colorize a grayscale image"
    assert image.mode == "L"
    black = _color(black, "RGB")
    white = _color(white, "RGB")
    red = []; green = []; blue = []
    for i in range(256):
        red.append(black[0]+i*(white[0]-black[0])//255)
        green.append(black[1]+i*(white[1]-black[1])//255)
        blue.append(black[2]+i*(white[2]-black[2])//255)
    image = image.convert("RGB")
    return _lut(image, red + green + blue)

##
# Remove border from image.  The same amount of pixels are removed
# from all four sides.  This function works on all image modes.
#
# @param image The image to crop.
# @param border The number of pixels to remove.
# @return An image.
# @see Image#Image.crop

def crop(image, border=0):
    "Crop border off image"
    left, top, right, bottom = _border(border)
    return image.crop(
        (left, top, image.size[0]-right, image.size[1]-bottom)
        )

##
# Deform the image.
#
# @param image The image to deform.
# @param deformer A deformer object. Any object that implements a
# getmesh method can be used.
# @param resample What resampling filter to use.
# @return An image.

def deform(image, deformer, resample=Image.BILINEAR):
    "Deform image using the given deformer"
    return image.transform(
        image.size, Image.MESH, deformer.getmesh(image), resample
        )

##
# 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.
#
# @param image The image to equalize.
# @param mask An optional mask.  If given, only the pixels selected by
#     the mask are included in the analysis.
# @return An image.

def equalize(image, mask=None):
 "Equalize image histogram"
 if image.mode == "P":
 image = image.convert("RGB")
 h = image.histogram(mask)
 lut = []
 for b in range(0, len(h), 256):
 histo = [_f for _f in h[b:b+256] if _f]
 if len(histo) <= 1:
 lut.extend(list(range(256)))
 else:
 step = (reduce(operator.add, histo) - histo[-1]) // 255
 if not step:
 lut.extend(list(range(256)))
 else:
 n = step // 2
 for i in range(256):
 lut.append(n // step)
 n = n + h[i+b]
 return _lut(image, lut)

##
# Add border to the image
#
# @param image The image to expand.
# @param border Border width, in pixels.
# @param fill Pixel fill value (a colour value).  Default is 0 (black).
# @return An image.

def expand(image, border=0, fill=0):
    "Add border to image"
    left, top, right, bottom = _border(border)
    width = left + image.size[0] + right
    height = top + image.size[1] + bottom
    out = Image.new(image.mode, (width, height), _color(fill, image.mode))
    out.paste(image, (left, top))
    return out

##
# Returns a sized and cropped version of the image, cropped to the
# requested aspect ratio and size.
# 
# The fit function was contributed by Kevin Cazabon.
#
# @param size The requested output size in pixels, given as a
# (width, height) tuple.
# @param method What resampling method to use. Default is Image.NEAREST.
# @param bleed Remove a border around the outside of 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).
# @param centering Control the cropping position. Use (0.5, 0.5) for
# center cropping (e.g. if cropping the width, take 50% off of the
# left side, and therefore 50% off the right side). (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).
# @return An image.

def fit(image, size, method=Image.NEAREST, bleed=0.0, centering=(0.5, 0.5)):
    """
    This method returns a sized and cropped version of the image,
    cropped to the aspect ratio and size that you request.
    """

# by Kevin Cazabon, Feb 17/2000
    # kevin@cazabon.com
    # http://www.cazabon.com

# ensure inputs are valid
    if not isinstance(centering, list):
        centering = [centering[0], centering[1]]

if centering[0] > 1.0 or centering[0] < 0.0:
 centering [0] = 0.50
 if centering[1] > 1.0 or centering[1] < 0.0:
 centering[1] = 0.50

if bleed > 0.49999 or bleed < 0.0:
 bleed = 0.0

# calculate the area to use for resizing and cropping, subtracting
    # the 'bleed' around the edges

# number of pixels to trim off on Top and Bottom, Left and Right
    bleedPixels = (
        int((float(bleed) * float(image.size[0])) + 0.5),
        int((float(bleed) * float(image.size[1])) + 0.5)
        )

liveArea = (
        bleedPixels[0], bleedPixels[1], image.size[0] - bleedPixels[0] - 1,
        image.size[1] - bleedPixels[1] - 1
        )

liveSize = (liveArea[2] - liveArea[0], liveArea[3] - liveArea[1])

# calculate the aspect ratio of the liveArea
    liveAreaAspectRatio = float(liveSize[0])/float(liveSize[1])

# calculate the aspect ratio of the output image
    aspectRatio = float(size[0]) / float(size[1])

# figure out if the sides or top/bottom will be cropped off
    if liveAreaAspectRatio >= aspectRatio:
        # liveArea is wider than what's needed, crop the sides
        cropWidth = int((aspectRatio * float(liveSize[1])) + 0.5)
        cropHeight = liveSize[1]
    else:
        # liveArea is taller than what's needed, crop the top and bottom
        cropWidth = liveSize[0]
        cropHeight = int((float(liveSize[0])/aspectRatio) + 0.5)

# make the crop
 leftSide = int(liveArea[0] + (float(liveSize[0]-cropWidth) * centering[0]))
 if leftSide < 0:
 leftSide = 0
 topSide = int(liveArea[1] + (float(liveSize[1]-cropHeight) * centering[1]))
 if topSide < 0:
 topSide = 0

out = image.crop(
        (leftSide, topSide, leftSide + cropWidth, topSide + cropHeight)
        )

# resize the image and return it
    return out.resize(size, method)

##
# Flip the image vertically (top to bottom).
#
# @param image The image to flip.
# @return An image.

def flip(image):
    "Flip image vertically"
    return image.transpose(Image.FLIP_TOP_BOTTOM)

##
# Convert the image to grayscale.
#
# @param image The image to convert.
# @return An image.

def grayscale(image):
    "Convert to grayscale"
    return image.convert("L")

##
# Invert (negate) the image.
#
# @param image The image to invert.
# @return An image.

def invert(image):
    "Invert image (negate)"
    lut = []
    for i in range(256):
        lut.append(255-i)
    return _lut(image, lut)

##
# Flip image horizontally (left to right).
#
# @param image The image to mirror.
# @return An image.

def mirror(image):
    "Flip image horizontally"
    return image.transpose(Image.FLIP_LEFT_RIGHT)

##
# Reduce the number of bits for each colour channel.
#
# @param image The image to posterize.
# @param bits The number of bits to keep for each channel (1-8).
# @return An image.

def posterize(image, bits):
    "Reduce the number of bits per color channel"
    lut = []
    mask = ~(2**(8-bits)-1)
    for i in range(256):
        lut.append(i & mask)
    return _lut(image, lut)

##
# Invert all pixel values above a threshold.
#
# @param image The image to posterize.
# @param threshold All pixels above this greyscale level are inverted.
# @return An image.

def solarize(image, threshold=128):
 "Invert all values above threshold"
 lut = []
 for i in range(256):
 if i < threshold:
 lut.append(i)
 else:
 lut.append(255-i)
 return _lut(image, lut)

# --------------------------------------------------------------------
# PIL USM components, from Kevin Cazabon.

def gaussian_blur(im, radius=None):
    """ PIL_usm.gblur(im, [radius])"""

if radius is None:
        radius = 5.0

im.load()

return im.im.gaussian_blur(radius)

gblur = gaussian_blur

def unsharp_mask(im, radius=None, percent=None, threshold=None):
    """ PIL_usm.usm(im, [radius, percent, threshold])"""

if radius is None:
        radius = 5.0
    if percent is None:
        percent = 150
    if threshold is None:
        threshold = 3

im.load()

return im.im.unsharp_mask(radius, percent, threshold)

usm = unsharp_mask