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Diffstat (limited to 'PIL/ImageMath.py')
| -rw-r--r-- | PIL/ImageMath.py | 207 |
1 files changed, 0 insertions, 207 deletions
diff --git a/PIL/ImageMath.py b/PIL/ImageMath.py deleted file mode 100644 index 117a5ae..0000000 --- a/PIL/ImageMath.py +++ /dev/null @@ -1,207 +0,0 @@ -# -# The Python Imaging Library -# $Id: ImageMath.py 2508 2005-09-12 19:01:03Z fredrik $ -# -# a simple math add-on for the Python Imaging Library -# -# History: -# 1999-02-15 fl Original PIL Plus release -# 2005-05-05 fl Simplified and cleaned up for PIL 1.1.6 -# 2005-09-12 fl Fixed int() and float() for Python 2.4.1 -# -# Copyright (c) 1999-2005 by Secret Labs AB -# Copyright (c) 2005 by Fredrik Lundh -# -# See the README file for information on usage and redistribution. -# - -import Image -import _imagingmath - -VERBOSE = 0 - -def _isconstant(v): - return isinstance(v, type(0)) or isinstance(v, type(0.0)) - -class _Operand: - # wraps an image operand, providing standard operators - - def __init__(self, im): - self.im = im - - def __fixup(self, im1): - # convert image to suitable mode - if isinstance(im1, _Operand): - # argument was an image. - if im1.im.mode in ("1", "L"): - return im1.im.convert("I") - elif im1.im.mode in ("I", "F"): - return im1.im - else: - raise ValueError, "unsupported mode: %s" % im1.im.mode - else: - # argument was a constant - if _isconstant(im1) and self.im.mode in ("1", "L", "I"): - return Image.new("I", self.im.size, im1) - else: - return Image.new("F", self.im.size, im1) - - def apply(self, op, im1, im2=None, mode=None): - im1 = self.__fixup(im1) - if im2 is None: - # unary operation - out = Image.new(mode or im1.mode, im1.size, None) - im1.load() - try: - op = getattr(_imagingmath, op+"_"+im1.mode) - except AttributeError: - raise TypeError, "bad operand type for '%s'" % op - _imagingmath.unop(op, out.im.id, im1.im.id) - else: - # binary operation - im2 = self.__fixup(im2) - if im1.mode != im2.mode: - # convert both arguments to floating point - if im1.mode != "F": im1 = im1.convert("F") - if im2.mode != "F": im2 = im2.convert("F") - if im1.mode != im2.mode: - raise ValueError, "mode mismatch" - if im1.size != im2.size: - # crop both arguments to a common size - size = (min(im1.size[0], im2.size[0]), - min(im1.size[1], im2.size[1])) - if im1.size != size: im1 = im1.crop((0, 0) + size) - if im2.size != size: im2 = im2.crop((0, 0) + size) - out = Image.new(mode or im1.mode, size, None) - else: - out = Image.new(mode or im1.mode, im1.size, None) - im1.load(); im2.load() - try: - op = getattr(_imagingmath, op+"_"+im1.mode) - except AttributeError: - raise TypeError, "bad operand type for '%s'" % op - _imagingmath.binop(op, out.im.id, im1.im.id, im2.im.id) - return _Operand(out) - - # unary operators - def __nonzero__(self): - # an image is "true" if it contains at least one non-zero pixel - return self.im.getbbox() is not None - def __abs__(self): - return self.apply("abs", self) - def __pos__(self): - return self - def __neg__(self): - return self.apply("neg", self) - - # binary operators - def __add__(self, other): - return self.apply("add", self, other) - def __radd__(self, other): - return self.apply("add", other, self) - def __sub__(self, other): - return self.apply("sub", self, other) - def __rsub__(self, other): - return self.apply("sub", other, self) - def __mul__(self, other): - return self.apply("mul", self, other) - def __rmul__(self, other): - return self.apply("mul", other, self) - def __div__(self, other): - return self.apply("div", self, other) - def __rdiv__(self, other): - return self.apply("div", other, self) - def __mod__(self, other): - return self.apply("mod", self, other) - def __rmod__(self, other): - return self.apply("mod", other, self) - def __pow__(self, other): - return self.apply("pow", self, other) - def __rpow__(self, other): - return self.apply("pow", other, self) - - # bitwise - def __invert__(self): - return self.apply("invert", self) - def __and__(self, other): - return self.apply("and", self, other) - def __rand__(self, other): - return self.apply("and", other, self) - def __or__(self, other): - return self.apply("or", self, other) - def __ror__(self, other): - return self.apply("or", other, self) - def __xor__(self, other): - return self.apply("xor", self, other) - def __rxor__(self, other): - return self.apply("xor", other, self) - def __lshift__(self, other): - return self.apply("lshift", self, other) - def __rshift__(self, other): - return self.apply("rshift", self, other) - - # logical - def __eq__(self, other): - return self.apply("eq", self, other) - def __ne__(self, other): - return self.apply("ne", self, other) - def __lt__(self, other): - return self.apply("lt", self, other) - def __le__(self, other): - return self.apply("le", self, other) - def __gt__(self, other): - return self.apply("gt", self, other) - def __ge__(self, other): - return self.apply("ge", self, other) - -# conversions -def imagemath_int(self): - return _Operand(self.im.convert("I")) -def imagemath_float(self): - return _Operand(self.im.convert("F")) - -# logical -def imagemath_equal(self, other): - return self.apply("eq", self, other, mode="I") -def imagemath_notequal(self, other): - return self.apply("ne", self, other, mode="I") - -def imagemath_min(self, other): - return self.apply("min", self, other) -def imagemath_max(self, other): - return self.apply("max", self, other) - -def imagemath_convert(self, mode): - return _Operand(self.im.convert(mode)) - -ops = {} -for k, v in globals().items(): - if k[:10] == "imagemath_": - ops[k[10:]] = v - -## -# Evaluates an image expression. -# -# @param expression A string containing a Python-style expression. -# @keyparam options Values to add to the evaluation context. You -# can either use a dictionary, or one or more keyword arguments. -# @return The evaluated expression. This is usually an image object, -# but can also be an integer, a floating point value, or a pixel -# tuple, depending on the expression. - -def eval(expression, _dict={}, **kw): - - # build execution namespace - args = ops.copy() - args.update(_dict) - args.update(kw) - for k, v in args.items(): - if hasattr(v, "im"): - args[k] = _Operand(v) - - import __builtin__ - out =__builtin__.eval(expression, args) - try: - return out.im - except AttributeError: - return out |