id card generator

1 files changed, 259 insertions, 0 deletions

diff --git a/env/lib/python3.10/site-packages/PIL/ImageMath.py b/env/lib/python3.10/site-packages/PIL/ImageMath.py
new file mode 100644
index 0000000..09d9898
--- /dev/null
+++ b/env/lib/python3.10/site-packages/PIL/ImageMath.py
@@ -0,0 +1,259 @@
+#
+# 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