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+#
+# The Python Imaging Library.
+# $Id$
+#
+# standard image operations
+#
+# History:
+# 2001-10-20 fl   Created
+# 2001-10-23 fl   Added autocontrast operator
+# 2001-12-18 fl   Added Kevin's fit operator
+# 2004-03-14 fl   Fixed potential division by zero in equalize
+# 2005-05-05 fl   Fixed equalize for low number of values
+#
+# Copyright (c) 2001-2004 by Secret Labs AB
+# Copyright (c) 2001-2004 by Fredrik Lundh
+#
+# See the README file for information on usage and redistribution.
+#
+from __future__ import annotations
+
+import functools
+import operator
+import re
+from collections.abc import Sequence
+from typing import Protocol, cast
+
+from . import ExifTags, Image, ImagePalette
+
+#
+# helpers
+
+
+def _border(border: int | tuple[int, ...]) -> tuple[int, int, int, int]:
+    if isinstance(border, tuple):
+        if len(border) == 2:
+            left, top = right, bottom = border
+        elif len(border) == 4:
+            left, top, right, bottom = border
+    else:
+        left = top = right = bottom = border
+    return left, top, right, bottom
+
+
+def _color(color: str | int | tuple[int, ...], mode: str) -> int | tuple[int, ...]:
+    if isinstance(color, str):
+        from . import ImageColor
+
+        color = ImageColor.getcolor(color, mode)
+    return color
+
+
+def _lut(image: Image.Image, lut: list[int]) -> Image.Image:
+    if image.mode == "P":
+        # FIXME: apply to lookup table, not image data
+        msg = "mode P support coming soon"
+        raise NotImplementedError(msg)
+    elif image.mode in ("L", "RGB"):
+        if image.mode == "RGB" and len(lut) == 256:
+            lut = lut + lut + lut
+        return image.point(lut)
+    else:
+        msg = f"not supported for mode {image.mode}"
+        raise OSError(msg)
+
+
+#
+# actions
+
+
+def autocontrast(
+    image: Image.Image,
+    cutoff: float | tuple[float, float] = 0,
+    ignore: int | Sequence[int] | None = None,
+    mask: Image.Image | None = None,
+    preserve_tone: bool = False,
+) -> Image.Image:
+    """
+    Maximize (normalize) image contrast. This function calculates a
+    histogram of the input image (or mask region), removes ``cutoff`` percent of the
+    lightest and darkest pixels from the histogram, and remaps the image
+    so that the darkest pixel becomes black (0), and the lightest
+    becomes white (255).
+
+    :param image: The image to process.
+    :param cutoff: The percent to cut off from the histogram on the low and
+                   high ends. Either a tuple of (low, high), or a single
+                   number for both.
+    :param ignore: The background pixel value (use None for no background).
+    :param mask: Histogram used in contrast operation is computed using pixels
+                 within the mask. If no mask is given the entire image is used
+                 for histogram computation.
+    :param preserve_tone: Preserve image tone in Photoshop-like style autocontrast.
+
+                          .. versionadded:: 8.2.0
+
+    :return: An image.
+    """
+    if preserve_tone:
+        histogram = image.convert("L").histogram(mask)
+    else:
+        histogram = image.histogram(mask)
+
+    lut = []
+    for layer in range(0, len(histogram), 256):
+        h = histogram[layer : layer + 256]
+        if ignore is not None:
+            # get rid of outliers
+            if isinstance(ignore, int):
+                h[ignore] = 0
+            else:
+                for ix in ignore:
+                    h[ix] = 0
+        if cutoff:
+            # cut off pixels from both ends of the histogram
+            if not isinstance(cutoff, tuple):
+                cutoff = (cutoff, cutoff)
+            # get number of pixels
+            n = 0
+            for ix in range(256):
+                n = n + h[ix]
+            # remove cutoff% pixels from the low end
+            cut = int(n * cutoff[0] // 100)
+            for lo in range(256):
+                if cut > h[lo]:
+                    cut = cut - h[lo]
+                    h[lo] = 0
+                else:
+                    h[lo] -= cut
+                    cut = 0
+                if cut <= 0:
+                    break
+            # remove cutoff% samples from the high end
+            cut = int(n * cutoff[1] // 100)
+            for hi in range(255, -1, -1):
+                if cut > h[hi]:
+                    cut = cut - h[hi]
+                    h[hi] = 0
+                else:
+                    h[hi] -= cut
+                    cut = 0
+                if cut <= 0:
+                    break
+        # find lowest/highest samples after preprocessing
+        for lo in range(256):
+            if h[lo]:
+                break
+        for hi in range(255, -1, -1):
+            if h[hi]:
+                break
+        if hi <= lo:
+            # don't bother
+            lut.extend(list(range(256)))
+        else:
+            scale = 255.0 / (hi - lo)
+            offset = -lo * scale
+            for ix in range(256):
+                ix = int(ix * scale + offset)
+                if ix < 0:
+                    ix = 0
+                elif ix > 255:
+                    ix = 255
+                lut.append(ix)
+    return _lut(image, lut)
+
+
+def colorize(
+    image: Image.Image,
+    black: str | tuple[int, ...],
+    white: str | tuple[int, ...],
+    mid: str | int | tuple[int, ...] | None = None,
+    blackpoint: int = 0,
+    whitepoint: int = 255,
+    midpoint: int = 127,
+) -> Image.Image:
+    """
+    Colorize grayscale image.
+    This function calculates a color wedge which maps all black pixels in
+    the source image to the first color and all white pixels to the
+    second color. If ``mid`` is specified, it uses three-color mapping.
+    The ``black`` and ``white`` arguments should be RGB tuples or color names;
+    optionally you can use three-color mapping by also specifying ``mid``.
+    Mapping positions for any of the colors can be specified
+    (e.g. ``blackpoint``), where these parameters are the integer
+    value corresponding to where the corresponding color should be mapped.
+    These parameters must have logical order, such that
+    ``blackpoint <= midpoint <= whitepoint`` (if ``mid`` is specified).
+
+    :param image: The image to colorize.
+    :param black: The color to use for black input pixels.
+    :param white: The color to use for white input pixels.
+    :param mid: The color to use for midtone input pixels.
+    :param blackpoint: an int value [0, 255] for the black mapping.
+    :param whitepoint: an int value [0, 255] for the white mapping.
+    :param midpoint: an int value [0, 255] for the midtone mapping.
+    :return: An image.
+    """
+
+    # Initial asserts
+    assert image.mode == "L"
+    if mid is None:
+        assert 0 <= blackpoint <= whitepoint <= 255
+    else:
+        assert 0 <= blackpoint <= midpoint <= whitepoint <= 255
+
+    # Define colors from arguments
+    rgb_black = cast(Sequence[int], _color(black, "RGB"))
+    rgb_white = cast(Sequence[int], _color(white, "RGB"))
+    rgb_mid = cast(Sequence[int], _color(mid, "RGB")) if mid is not None else None
+
+    # Empty lists for the mapping
+    red = []
+    green = []
+    blue = []
+
+    # Create the low-end values
+    for i in range(0, blackpoint):
+        red.append(rgb_black[0])
+        green.append(rgb_black[1])
+        blue.append(rgb_black[2])
+
+    # Create the mapping (2-color)
+    if rgb_mid is None:
+        range_map = range(0, whitepoint - blackpoint)
+
+        for i in range_map:
+            red.append(
+                rgb_black[0] + i * (rgb_white[0] - rgb_black[0]) // len(range_map)
+            )
+            green.append(
+                rgb_black[1] + i * (rgb_white[1] - rgb_black[1]) // len(range_map)
+            )
+            blue.append(
+                rgb_black[2] + i * (rgb_white[2] - rgb_black[2]) // len(range_map)
+            )
+
+    # Create the mapping (3-color)
+    else:
+        range_map1 = range(0, midpoint - blackpoint)
+        range_map2 = range(0, whitepoint - midpoint)
+
+        for i in range_map1:
+            red.append(
+                rgb_black[0] + i * (rgb_mid[0] - rgb_black[0]) // len(range_map1)
+            )
+            green.append(
+                rgb_black[1] + i * (rgb_mid[1] - rgb_black[1]) // len(range_map1)
+            )
+            blue.append(
+                rgb_black[2] + i * (rgb_mid[2] - rgb_black[2]) // len(range_map1)
+            )
+        for i in range_map2:
+            red.append(rgb_mid[0] + i * (rgb_white[0] - rgb_mid[0]) // len(range_map2))
+            green.append(
+                rgb_mid[1] + i * (rgb_white[1] - rgb_mid[1]) // len(range_map2)
+            )
+            blue.append(rgb_mid[2] + i * (rgb_white[2] - rgb_mid[2]) // len(range_map2))
+
+    # Create the high-end values
+    for i in range(0, 256 - whitepoint):
+        red.append(rgb_white[0])
+        green.append(rgb_white[1])
+        blue.append(rgb_white[2])
+
+    # Return converted image
+    image = image.convert("RGB")
+    return _lut(image, red + green + blue)
+
+
+def contain(
+    image: Image.Image, size: tuple[int, int], method: int = Image.Resampling.BICUBIC
+) -> Image.Image:
+    """
+    Returns a resized version of the image, set to the maximum width and height
+    within the requested size, while maintaining the original aspect ratio.
+
+    :param image: The image to resize.
+    :param size: The requested output size in pixels, given as a
+                 (width, height) tuple.
+    :param method: Resampling method to use. Default is
+                   :py:attr:`~PIL.Image.Resampling.BICUBIC`.
+                   See :ref:`concept-filters`.
+    :return: An image.
+    """
+
+    im_ratio = image.width / image.height
+    dest_ratio = size[0] / size[1]
+
+    if im_ratio != dest_ratio:
+        if im_ratio > dest_ratio:
+            new_height = round(image.height / image.width * size[0])
+            if new_height != size[1]:
+                size = (size[0], new_height)
+        else:
+            new_width = round(image.width / image.height * size[1])
+            if new_width != size[0]:
+                size = (new_width, size[1])
+    return image.resize(size, resample=method)
+
+
+def cover(
+    image: Image.Image, size: tuple[int, int], method: int = Image.Resampling.BICUBIC
+) -> Image.Image:
+    """
+    Returns a resized version of the image, so that the requested size is
+    covered, while maintaining the original aspect ratio.
+
+    :param image: The image to resize.
+    :param size: The requested output size in pixels, given as a
+                 (width, height) tuple.
+    :param method: Resampling method to use. Default is
+                   :py:attr:`~PIL.Image.Resampling.BICUBIC`.
+                   See :ref:`concept-filters`.
+    :return: An image.
+    """
+
+    im_ratio = image.width / image.height
+    dest_ratio = size[0] / size[1]
+
+    if im_ratio != dest_ratio:
+        if im_ratio < dest_ratio:
+            new_height = round(image.height / image.width * size[0])
+            if new_height != size[1]:
+                size = (size[0], new_height)
+        else:
+            new_width = round(image.width / image.height * size[1])
+            if new_width != size[0]:
+                size = (new_width, size[1])
+    return image.resize(size, resample=method)
+
+
+def pad(
+    image: Image.Image,
+    size: tuple[int, int],
+    method: int = Image.Resampling.BICUBIC,
+    color: str | int | tuple[int, ...] | None = None,
+    centering: tuple[float, float] = (0.5, 0.5),
+) -> Image.Image:
+    """
+    Returns a resized and padded version of the image, expanded to fill the
+    requested aspect ratio and size.
+
+    :param image: The image to resize and crop.
+    :param size: The requested output size in pixels, given as a
+                 (width, height) tuple.
+    :param method: Resampling method to use. Default is
+                   :py:attr:`~PIL.Image.Resampling.BICUBIC`.
+                   See :ref:`concept-filters`.
+    :param color: The background color of the padded image.
+    :param centering: Control the position of the original image within the
+                      padded version.
+
+                          (0.5, 0.5) will keep the image centered
+                          (0, 0) will keep the image aligned to the top left
+                          (1, 1) will keep the image aligned to the bottom
+                          right
+    :return: An image.
+    """
+
+    resized = contain(image, size, method)
+    if resized.size == size:
+        out = resized
+    else:
+        out = Image.new(image.mode, size, color)
+        if resized.palette:
+            palette = resized.getpalette()
+            if palette is not None:
+                out.putpalette(palette)
+        if resized.width != size[0]:
+            x = round((size[0] - resized.width) * max(0, min(centering[0], 1)))
+            out.paste(resized, (x, 0))
+        else:
+            y = round((size[1] - resized.height) * max(0, min(centering[1], 1)))
+            out.paste(resized, (0, y))
+    return out
+
+
+def crop(image: Image.Image, border: int = 0) -> Image.Image:
+    """
+    Remove border from image.  The same amount of pixels are removed
+    from all four sides.  This function works on all image modes.
+
+    .. seealso:: :py:meth:`~PIL.Image.Image.crop`
+
+    :param image: The image to crop.
+    :param border: The number of pixels to remove.
+    :return: An image.
+    """
+    left, top, right, bottom = _border(border)
+    return image.crop((left, top, image.size[0] - right, image.size[1] - bottom))
+
+
+def scale(
+    image: Image.Image, factor: float, resample: int = Image.Resampling.BICUBIC
+) -> Image.Image:
+    """
+    Returns a rescaled image by a specific factor given in parameter.
+    A factor greater than 1 expands the image, between 0 and 1 contracts the
+    image.
+
+    :param image: The image to rescale.
+    :param factor: The expansion factor, as a float.
+    :param resample: Resampling method to use. Default is
+                     :py:attr:`~PIL.Image.Resampling.BICUBIC`.
+                     See :ref:`concept-filters`.
+    :returns: An :py:class:`~PIL.Image.Image` object.
+    """
+    if factor == 1:
+        return image.copy()
+    elif factor <= 0:
+        msg = "the factor must be greater than 0"
+        raise ValueError(msg)
+    else:
+        size = (round(factor * image.width), round(factor * image.height))
+        return image.resize(size, resample)
+
+
+class SupportsGetMesh(Protocol):
+    """
+    An object that supports the ``getmesh`` method, taking an image as an
+    argument, and returning a list of tuples. Each tuple contains two tuples,
+    the source box as a tuple of 4 integers, and a tuple of 8 integers for the
+    final quadrilateral, in order of top left, bottom left, bottom right, top
+    right.
+    """
+
+    def getmesh(
+        self, image: Image.Image
+    ) -> list[
+        tuple[tuple[int, int, int, int], tuple[int, int, int, int, int, int, int, int]]
+    ]: ...
+
+
+def deform(
+    image: Image.Image,
+    deformer: SupportsGetMesh,
+    resample: int = Image.Resampling.BILINEAR,
+) -> Image.Image:
+    """
+    Deform the image.
+
+    :param image: The image to deform.
+    :param deformer: A deformer object.  Any object that implements a
+                    ``getmesh`` method can be used.
+    :param resample: An optional resampling filter. Same values possible as
+       in the PIL.Image.transform function.
+    :return: An image.
+    """
+    return image.transform(
+        image.size, Image.Transform.MESH, deformer.getmesh(image), resample
+    )
+
+
+def equalize(image: Image.Image, mask: Image.Image | None = None) -> Image.Image:
+    """
+    Equalize the image histogram. This function applies a non-linear
+    mapping to the input image, in order to create a uniform
+    distribution of grayscale values in the output image.
+
+    :param image: The image to equalize.
+    :param mask: An optional mask.  If given, only the pixels selected by
+                 the mask are included in the analysis.
+    :return: An image.
+    """
+    if image.mode == "P":
+        image = image.convert("RGB")
+    h = image.histogram(mask)
+    lut = []
+    for b in range(0, len(h), 256):
+        histo = [_f for _f in h[b : b + 256] if _f]
+        if len(histo) <= 1:
+            lut.extend(list(range(256)))
+        else:
+            step = (functools.reduce(operator.add, histo) - histo[-1]) // 255
+            if not step:
+                lut.extend(list(range(256)))
+            else:
+                n = step // 2
+                for i in range(256):
+                    lut.append(n // step)
+                    n = n + h[i + b]
+    return _lut(image, lut)
+
+
+def expand(
+    image: Image.Image,
+    border: int | tuple[int, ...] = 0,
+    fill: str | int | tuple[int, ...] = 0,
+) -> Image.Image:
+    """
+    Add border to the image
+
+    :param image: The image to expand.
+    :param border: Border width, in pixels.
+    :param fill: Pixel fill value (a color value).  Default is 0 (black).
+    :return: An image.
+    """
+    left, top, right, bottom = _border(border)
+    width = left + image.size[0] + right
+    height = top + image.size[1] + bottom
+    color = _color(fill, image.mode)
+    if image.palette:
+        palette = ImagePalette.ImagePalette(palette=image.getpalette())
+        if isinstance(color, tuple) and (len(color) == 3 or len(color) == 4):
+            color = palette.getcolor(color)
+    else:
+        palette = None
+    out = Image.new(image.mode, (width, height), color)
+    if palette:
+        out.putpalette(palette.palette)
+    out.paste(image, (left, top))
+    return out
+
+
+def fit(
+    image: Image.Image,
+    size: tuple[int, int],
+    method: int = Image.Resampling.BICUBIC,
+    bleed: float = 0.0,
+    centering: tuple[float, float] = (0.5, 0.5),
+) -> Image.Image:
+    """
+    Returns a resized and cropped version of the image, cropped to the
+    requested aspect ratio and size.
+
+    This function was contributed by Kevin Cazabon.
+
+    :param image: The image to resize and crop.
+    :param size: The requested output size in pixels, given as a
+                 (width, height) tuple.
+    :param method: Resampling method to use. Default is
+                   :py:attr:`~PIL.Image.Resampling.BICUBIC`.
+                   See :ref:`concept-filters`.
+    :param bleed: Remove a border around the outside of the image from all
+                  four edges. The value is a decimal percentage (use 0.01 for
+                  one percent). The default value is 0 (no border).
+                  Cannot be greater than or equal to 0.5.
+    :param centering: Control the cropping position.  Use (0.5, 0.5) for
+                      center cropping (e.g. if cropping the width, take 50% off
+                      of the left side, and therefore 50% off the right side).
+                      (0.0, 0.0) will crop from the top left corner (i.e. if
+                      cropping the width, take all of the crop off of the right
+                      side, and if cropping the height, take all of it off the
+                      bottom).  (1.0, 0.0) will crop from the bottom left
+                      corner, etc. (i.e. if cropping the width, take all of the
+                      crop off the left side, and if cropping the height take
+                      none from the top, and therefore all off the bottom).
+    :return: An image.
+    """
+
+    # by Kevin Cazabon, Feb 17/2000
+    # kevin@cazabon.com
+    # https://www.cazabon.com
+
+    centering_x, centering_y = centering
+
+    if not 0.0 <= centering_x <= 1.0:
+        centering_x = 0.5
+    if not 0.0 <= centering_y <= 1.0:
+        centering_y = 0.5
+
+    if not 0.0 <= bleed < 0.5:
+        bleed = 0.0
+
+    # calculate the area to use for resizing and cropping, subtracting
+    # the 'bleed' around the edges
+
+    # number of pixels to trim off on Top and Bottom, Left and Right
+    bleed_pixels = (bleed * image.size[0], bleed * image.size[1])
+
+    live_size = (
+        image.size[0] - bleed_pixels[0] * 2,
+        image.size[1] - bleed_pixels[1] * 2,
+    )
+
+    # calculate the aspect ratio of the live_size
+    live_size_ratio = live_size[0] / live_size[1]
+
+    # calculate the aspect ratio of the output image
+    output_ratio = size[0] / size[1]
+
+    # figure out if the sides or top/bottom will be cropped off
+    if live_size_ratio == output_ratio:
+        # live_size is already the needed ratio
+        crop_width = live_size[0]
+        crop_height = live_size[1]
+    elif live_size_ratio >= output_ratio:
+        # live_size is wider than what's needed, crop the sides
+        crop_width = output_ratio * live_size[1]
+        crop_height = live_size[1]
+    else:
+        # live_size is taller than what's needed, crop the top and bottom
+        crop_width = live_size[0]
+        crop_height = live_size[0] / output_ratio
+
+    # make the crop
+    crop_left = bleed_pixels[0] + (live_size[0] - crop_width) * centering_x
+    crop_top = bleed_pixels[1] + (live_size[1] - crop_height) * centering_y
+
+    crop = (crop_left, crop_top, crop_left + crop_width, crop_top + crop_height)
+
+    # resize the image and return it
+    return image.resize(size, method, box=crop)
+
+
+def flip(image: Image.Image) -> Image.Image:
+    """
+    Flip the image vertically (top to bottom).
+
+    :param image: The image to flip.
+    :return: An image.
+    """
+    return image.transpose(Image.Transpose.FLIP_TOP_BOTTOM)
+
+
+def grayscale(image: Image.Image) -> Image.Image:
+    """
+    Convert the image to grayscale.
+
+    :param image: The image to convert.
+    :return: An image.
+    """
+    return image.convert("L")
+
+
+def invert(image: Image.Image) -> Image.Image:
+    """
+    Invert (negate) the image.
+
+    :param image: The image to invert.
+    :return: An image.
+    """
+    lut = list(range(255, -1, -1))
+    return image.point(lut) if image.mode == "1" else _lut(image, lut)
+
+
+def mirror(image: Image.Image) -> Image.Image:
+    """
+    Flip image horizontally (left to right).
+
+    :param image: The image to mirror.
+    :return: An image.
+    """
+    return image.transpose(Image.Transpose.FLIP_LEFT_RIGHT)
+
+
+def posterize(image: Image.Image, bits: int) -> Image.Image:
+    """
+    Reduce the number of bits for each color channel.
+
+    :param image: The image to posterize.
+    :param bits: The number of bits to keep for each channel (1-8).
+    :return: An image.
+    """
+    mask = ~(2 ** (8 - bits) - 1)
+    lut = [i & mask for i in range(256)]
+    return _lut(image, lut)
+
+
+def solarize(image: Image.Image, threshold: int = 128) -> Image.Image:
+    """
+    Invert all pixel values above a threshold.
+
+    :param image: The image to solarize.
+    :param threshold: All pixels above this grayscale level are inverted.
+    :return: An image.
+    """
+    lut = []
+    for i in range(256):
+        if i < threshold:
+            lut.append(i)
+        else:
+            lut.append(255 - i)
+    return _lut(image, lut)
+
+
+def exif_transpose(image: Image.Image, *, in_place: bool = False) -> Image.Image | None:
+    """
+    If an image has an EXIF Orientation tag, other than 1, transpose the image
+    accordingly, and remove the orientation data.
+
+    :param image: The image to transpose.
+    :param in_place: Boolean. Keyword-only argument.
+        If ``True``, the original image is modified in-place, and ``None`` is returned.
+        If ``False`` (default), a new :py:class:`~PIL.Image.Image` object is returned
+        with the transposition applied. If there is no transposition, a copy of the
+        image will be returned.
+    """
+    image.load()
+    image_exif = image.getexif()
+    orientation = image_exif.get(ExifTags.Base.Orientation, 1)
+    method = {
+        2: Image.Transpose.FLIP_LEFT_RIGHT,
+        3: Image.Transpose.ROTATE_180,
+        4: Image.Transpose.FLIP_TOP_BOTTOM,
+        5: Image.Transpose.TRANSPOSE,
+        6: Image.Transpose.ROTATE_270,
+        7: Image.Transpose.TRANSVERSE,
+        8: Image.Transpose.ROTATE_90,
+    }.get(orientation)
+    if method is not None:
+        if in_place:
+            image.im = image.im.transpose(method)
+            image._size = image.im.size
+        else:
+            transposed_image = image.transpose(method)
+        exif_image = image if in_place else transposed_image
+
+        exif = exif_image.getexif()
+        if ExifTags.Base.Orientation in exif:
+            del exif[ExifTags.Base.Orientation]
+            if "exif" in exif_image.info:
+                exif_image.info["exif"] = exif.tobytes()
+            elif "Raw profile type exif" in exif_image.info:
+                exif_image.info["Raw profile type exif"] = exif.tobytes().hex()
+            for key in ("XML:com.adobe.xmp", "xmp"):
+                if key in exif_image.info:
+                    for pattern in (
+                        r'tiff:Orientation="([0-9])"',
+                        r"<tiff:Orientation>([0-9])</tiff:Orientation>",
+                    ):
+                        value = exif_image.info[key]
+                        exif_image.info[key] = (
+                            re.sub(pattern, "", value)
+                            if isinstance(value, str)
+                            else re.sub(pattern.encode(), b"", value)
+                        )
+        if not in_place:
+            return transposed_image
+    elif not in_place:
+        return image.copy()
+    return None