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