# # 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. # from __future__ import annotations import builtins from types import CodeType from typing import Any, Callable from . import Image, _imagingmath from ._deprecate import deprecate class _Operand: """Wraps an image operand, providing standard operators""" def __init__(self, im: Image.Image): self.im = im def __fixup(self, im1: _Operand | float) -> Image.Image: # 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: msg = f"unsupported mode: {im1.im.mode}" raise ValueError(msg) else: # argument was a constant if isinstance(im1, (int, float)) 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: str, im1: _Operand | float, im2: _Operand | float | None = None, mode: str | None = None, ) -> _Operand: im_1 = self.__fixup(im1) if im2 is None: # unary operation out = Image.new(mode or im_1.mode, im_1.size, None) im_1.load() try: op = getattr(_imagingmath, op + "_" + im_1.mode) except AttributeError as e: msg = f"bad operand type for '{op}'" raise TypeError(msg) from e _imagingmath.unop(op, out.im.id, im_1.im.id) else: # binary operation im_2 = self.__fixup(im2) if im_1.mode != im_2.mode: # convert both arguments to floating point if im_1.mode != "F": im_1 = im_1.convert("F") if im_2.mode != "F": im_2 = im_2.convert("F") if im_1.size != im_2.size: # crop both arguments to a common size size = ( min(im_1.size[0], im_2.size[0]), min(im_1.size[1], im_2.size[1]), ) if im_1.size != size: im_1 = im_1.crop((0, 0) + size) if im_2.size != size: im_2 = im_2.crop((0, 0) + size) out = Image.new(mode or im_1.mode, im_1.size, None) im_1.load() im_2.load() try: op = getattr(_imagingmath, op + "_" + im_1.mode) except AttributeError as e: msg = f"bad operand type for '{op}'" raise TypeError(msg) from e _imagingmath.binop(op, out.im.id, im_1.im.id, im_2.im.id) return _Operand(out) # unary operators def __bool__(self) -> bool: # an image is "true" if it contains at least one non-zero pixel return self.im.getbbox() is not None def __abs__(self) -> _Operand: return self.apply("abs", self) def __pos__(self) -> _Operand: return self def __neg__(self) -> _Operand: return self.apply("neg", self) # binary operators def __add__(self, other: _Operand | float) -> _Operand: return self.apply("add", self, other) def __radd__(self, other: _Operand | float) -> _Operand: return self.apply("add", other, self) def __sub__(self, other: _Operand | float) -> _Operand: return self.apply("sub", self, other) def __rsub__(self, other: _Operand | float) -> _Operand: return self.apply("sub", other, self) def __mul__(self, other: _Operand | float) -> _Operand: return self.apply("mul", self, other) def __rmul__(self, other: _Operand | float) -> _Operand: return self.apply("mul", other, self) def __truediv__(self, other: _Operand | float) -> _Operand: return self.apply("div", self, other) def __rtruediv__(self, other: _Operand | float) -> _Operand: return self.apply("div", other, self) def __mod__(self, other: _Operand | float) -> _Operand: return self.apply("mod", self, other) def __rmod__(self, other: _Operand | float) -> _Operand: return self.apply("mod", other, self) def __pow__(self, other: _Operand | float) -> _Operand: return self.apply("pow", self, other) def __rpow__(self, other: _Operand | float) -> _Operand: return self.apply("pow", other, self) # bitwise def __invert__(self) -> _Operand: return self.apply("invert", self) def __and__(self, other: _Operand | float) -> _Operand: return self.apply("and", self, other) def __rand__(self, other: _Operand | float) -> _Operand: return self.apply("and", other, self) def __or__(self, other: _Operand | float) -> _Operand: return self.apply("or", self, other) def __ror__(self, other: _Operand | float) -> _Operand: return self.apply("or", other, self) def __xor__(self, other: _Operand | float) -> _Operand: return self.apply("xor", self, other) def __rxor__(self, other: _Operand | float) -> _Operand: return self.apply("xor", other, self) def __lshift__(self, other: _Operand | float) -> _Operand: return self.apply("lshift", self, other) def __rshift__(self, other: _Operand | float) -> _Operand: 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: _Operand | float) -> _Operand: return self.apply("lt", self, other) def __le__(self, other: _Operand | float) -> _Operand: return self.apply("le", self, other) def __gt__(self, other: _Operand | float) -> _Operand: return self.apply("gt", self, other) def __ge__(self, other: _Operand | float) -> _Operand: return self.apply("ge", self, other) # conversions def imagemath_int(self: _Operand) -> _Operand: return _Operand(self.im.convert("I")) def imagemath_float(self: _Operand) -> _Operand: return _Operand(self.im.convert("F")) # logical def imagemath_equal(self: _Operand, other: _Operand | float | None) -> _Operand: return self.apply("eq", self, other, mode="I") def imagemath_notequal(self: _Operand, other: _Operand | float | None) -> _Operand: return self.apply("ne", self, other, mode="I") def imagemath_min(self: _Operand, other: _Operand | float | None) -> _Operand: return self.apply("min", self, other) def imagemath_max(self: _Operand, other: _Operand | float | None) -> _Operand: return self.apply("max", self, other) def imagemath_convert(self: _Operand, mode: str) -> _Operand: return _Operand(self.im.convert(mode)) ops = { "int": imagemath_int, "float": imagemath_float, "equal": imagemath_equal, "notequal": imagemath_notequal, "min": imagemath_min, "max": imagemath_max, "convert": imagemath_convert, } def lambda_eval( expression: Callable[[dict[str, Any]], Any], options: dict[str, Any] = {}, **kw: Any, ) -> Any: """ Returns the result of an image function. :py:mod:`~PIL.ImageMath` only supports single-layer images. To process multi-band images, use the :py:meth:`~PIL.Image.Image.split` method or :py:func:`~PIL.Image.merge` function. :param expression: A function that receives a dictionary. :param options: Values to add to the function's dictionary. You can either use a dictionary, or one or more keyword arguments. :return: The expression result. This is usually an image object, but can also be an integer, a floating point value, or a pixel tuple, depending on the expression. """ args: dict[str, Any] = ops.copy() args.update(options) args.update(kw) for k, v in args.items(): if hasattr(v, "im"): args[k] = _Operand(v) out = expression(args) try: return out.im except AttributeError: return out def unsafe_eval( expression: str, options: dict[str, Any] = {}, **kw: Any, ) -> Any: """ Evaluates an image expression. This uses Python's ``eval()`` function to process the expression string, and carries the security risks of doing so. It is not recommended to process expressions without considering this. :py:meth:`~lambda_eval` is a more secure alternative. :py:mod:`~PIL.ImageMath` only supports single-layer images. To process multi-band images, use the :py:meth:`~PIL.Image.Image.split` method or :py:func:`~PIL.Image.merge` function. :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: dict[str, Any] = ops.copy() for k in list(options.keys()) + list(kw.keys()): if "__" in k or hasattr(builtins, k): msg = f"'{k}' not allowed" raise ValueError(msg) args.update(options) args.update(kw) for k, v in args.items(): if hasattr(v, "im"): args[k] = _Operand(v) compiled_code = compile(expression, "", "eval") def scan(code: CodeType) -> None: for const in code.co_consts: if type(const) is type(compiled_code): scan(const) for name in code.co_names: if name not in args and name != "abs": msg = f"'{name}' not allowed" raise ValueError(msg) scan(compiled_code) out = builtins.eval(expression, {"__builtins": {"abs": abs}}, args) try: return out.im except AttributeError: return out def eval( expression: str, _dict: dict[str, Any] = {}, **kw: Any, ) -> Any: """ Evaluates an image expression. Deprecated. Use lambda_eval() or unsafe_eval() instead. :param expression: A string containing a Python-style expression. :param _dict: 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. .. deprecated:: 10.3.0 """ deprecate( "ImageMath.eval", 12, "ImageMath.lambda_eval or ImageMath.unsafe_eval", ) return unsafe_eval(expression, _dict, **kw)