#
# The Python Imaging Library
# $Id$
#
# 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 builtins
from . import Image, _imagingmath
def _isconstant(v):
return isinstance(v, (int, float))
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(f"unsupported mode: {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 as e:
raise TypeError(f"bad operand type for '{op}'") from e
_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.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, im1.size, None)
im1.load()
im2.load()
try:
op = getattr(_imagingmath, op + "_" + im1.mode)
except AttributeError as e:
raise TypeError(f"bad operand type for '{op}'") from e
_imagingmath.binop(op, out.im.id, im1.im.id, im2.im.id)
return _Operand(out)
# unary operators
def __bool__(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 __truediv__(self, other):
return self.apply("div", self, other)
def __rtruediv__(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 list(globals().items()):
if k[:10] == "imagemath_":
ops[k[10:]] = v
def eval(expression, _dict={}, **kw):
"""
Evaluates an image expression.
:param expression: A string containing a Python-style expression.
:param 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.
"""
# build execution namespace
args = ops.copy()
args.update(_dict)
args.update(kw)
for k, v in list(args.items()):
if hasattr(v, "im"):
args[k] = _Operand(v)
compiled_code = compile(expression, "<string>", "eval")
def scan(code):
for const in code.co_consts:
if type(const) == type(compiled_code):
scan(const)
for name in code.co_names:
if name not in args and name != "abs":
raise ValueError(f"'{name}' not allowed")
scan(compiled_code)
out = builtins.eval(expression, {"__builtins": {"abs": abs}}, args)
try:
return out.im
except AttributeError:
return out
