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Merge pull request #7786 from radarhere/type_hints_imageops
Added type hints to ImageOps
This commit is contained in:
Hugo van Kemenade
GitHub
commit
80d4fc14b8
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@ -1430,7 +1430,7 @@ class Image:
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root = ElementTree.fromstring(xmp_tags)
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return {get_name(root.tag): get_value(root)}
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def getexif(self):
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def getexif(self) -> Exif:
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"""
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Gets EXIF data from the image.
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@ -1438,7 +1438,6 @@ class Image:
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"""
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if self._exif is None:
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self._exif = Exif()
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self._exif._loaded = False
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elif self._exif._loaded:
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return self._exif
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self._exif._loaded = True
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@ -1525,7 +1524,7 @@ class Image:
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self.load()
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return self.im.ptr
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def getpalette(self, rawmode="RGB"):
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def getpalette(self, rawmode: str | None = "RGB") -> list[int] | None:
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"""
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Returns the image palette as a list.
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@ -1615,7 +1614,7 @@ class Image:
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x, y = self.im.getprojection()
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return list(x), list(y)
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def histogram(self, mask=None, extrema=None):
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def histogram(self, mask=None, extrema=None) -> list[int]:
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"""
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Returns a histogram for the image. The histogram is returned as a
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list of pixel counts, one for each pixel value in the source
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@ -1804,7 +1803,7 @@ class Image:
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result = alpha_composite(background, overlay)
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self.paste(result, box)
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def point(self, lut, mode=None):
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def point(self, lut, mode: str | None = None) -> Image:
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"""
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Maps this image through a lookup table or function.
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@ -1928,7 +1927,7 @@ class Image:
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self.im.putdata(data, scale, offset)
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def putpalette(self, data, rawmode="RGB"):
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def putpalette(self, data, rawmode="RGB") -> None:
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"""
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Attaches a palette to this image. The image must be a "P", "PA", "L"
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or "LA" image.
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@ -2108,7 +2107,7 @@ class Image:
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min(self.size[1], math.ceil(box[3] + support_y)),
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)
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def resize(self, size, resample=None, box=None, reducing_gap=None):
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def resize(self, size, resample=None, box=None, reducing_gap=None) -> Image:
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"""
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Returns a resized copy of this image.
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@ -2200,10 +2199,11 @@ class Image:
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if factor_x > 1 or factor_y > 1:
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reduce_box = self._get_safe_box(size, resample, box)
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factor = (factor_x, factor_y)
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if callable(self.reduce):
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self = self.reduce(factor, box=reduce_box)
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else:
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self = Image.reduce(self, factor, box=reduce_box)
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self = (
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self.reduce(factor, box=reduce_box)
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if callable(self.reduce)
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else Image.reduce(self, factor, box=reduce_box)
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)
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box = (
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(box[0] - reduce_box[0]) / factor_x,
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(box[1] - reduce_box[1]) / factor_y,
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@ -2818,7 +2818,7 @@ class Image:
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self.im.transform2(box, image.im, method, data, resample, fill)
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def transpose(self, method):
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def transpose(self, method: Transpose) -> Image:
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"""
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Transpose image (flip or rotate in 90 degree steps)
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@ -2870,7 +2870,9 @@ class ImagePointHandler:
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(for use with :py:meth:`~PIL.Image.Image.point`)
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"""
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pass
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@abc.abstractmethod
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def point(self, im: Image) -> Image:
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pass
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class ImageTransformHandler:
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@ -3690,6 +3692,7 @@ class Exif(_ExifBase):
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endian = None
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bigtiff = False
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_loaded = False
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def __init__(self):
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self._data = {}
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@ -3805,7 +3808,7 @@ class Exif(_ExifBase):
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return merged_dict
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def tobytes(self, offset=8):
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def tobytes(self, offset: int = 8) -> bytes:
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from . import TiffImagePlugin
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head = self._get_head()
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@ -3960,7 +3963,7 @@ class Exif(_ExifBase):
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del self._info[tag]
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self._data[tag] = value
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def __delitem__(self, tag):
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def __delitem__(self, tag: int) -> None:
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if self._info is not None and tag in self._info:
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del self._info[tag]
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else:
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@ -124,7 +124,7 @@ def getrgb(color):
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@lru_cache
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def getcolor(color, mode):
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def getcolor(color, mode: str) -> tuple[int, ...]:
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"""
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Same as :py:func:`~PIL.ImageColor.getrgb` for most modes. However, if
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``mode`` is HSV, converts the RGB value to a HSV value, or if ``mode`` is
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@ -21,6 +21,7 @@ from __future__ import annotations
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import functools
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import operator
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import re
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from typing import Protocol, Sequence, cast
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from . import ExifTags, Image, ImagePalette
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@ -28,7 +29,7 @@ from . import ExifTags, Image, ImagePalette
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# helpers
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def _border(border):
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def _border(border: int | tuple[int, ...]) -> tuple[int, int, int, int]:
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if isinstance(border, tuple):
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if len(border) == 2:
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left, top = right, bottom = border
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@ -39,7 +40,7 @@ def _border(border):
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return left, top, right, bottom
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def _color(color, mode):
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def _color(color: str | int | tuple[int, ...], mode: str) -> int | tuple[int, ...]:
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if isinstance(color, str):
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from . import ImageColor
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@ -47,7 +48,7 @@ def _color(color, mode):
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return color
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def _lut(image, lut):
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def _lut(image: Image.Image, lut: list[int]) -> Image.Image:
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if image.mode == "P":
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# FIXME: apply to lookup table, not image data
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msg = "mode P support coming soon"
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@ -65,7 +66,13 @@ def _lut(image, lut):
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# actions
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def autocontrast(image, cutoff=0, ignore=None, mask=None, preserve_tone=False):
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def autocontrast(
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image: Image.Image,
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cutoff: float | tuple[float, float] = 0,
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ignore: int | Sequence[int] | None = None,
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mask: Image.Image | None = None,
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preserve_tone: bool = False,
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) -> Image.Image:
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"""
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Maximize (normalize) image contrast. This function calculates a
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histogram of the input image (or mask region), removes ``cutoff`` percent of the
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@ -97,10 +104,9 @@ def autocontrast(image, cutoff=0, ignore=None, mask=None, preserve_tone=False):
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h = histogram[layer : layer + 256]
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if ignore is not None:
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# get rid of outliers
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try:
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if isinstance(ignore, int):
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h[ignore] = 0
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except TypeError:
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# assume sequence
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else:
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for ix in ignore:
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h[ix] = 0
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if cutoff:
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@ -112,7 +118,7 @@ def autocontrast(image, cutoff=0, ignore=None, mask=None, preserve_tone=False):
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for ix in range(256):
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n = n + h[ix]
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# remove cutoff% pixels from the low end
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cut = n * cutoff[0] // 100
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cut = int(n * cutoff[0] // 100)
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for lo in range(256):
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if cut > h[lo]:
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cut = cut - h[lo]
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@ -123,7 +129,7 @@ def autocontrast(image, cutoff=0, ignore=None, mask=None, preserve_tone=False):
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if cut <= 0:
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break
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# remove cutoff% samples from the high end
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cut = n * cutoff[1] // 100
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cut = int(n * cutoff[1] // 100)
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for hi in range(255, -1, -1):
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if cut > h[hi]:
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cut = cut - h[hi]
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@ -156,7 +162,15 @@ def autocontrast(image, cutoff=0, ignore=None, mask=None, preserve_tone=False):
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return _lut(image, lut)
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def colorize(image, black, white, mid=None, blackpoint=0, whitepoint=255, midpoint=127):
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def colorize(
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image: Image.Image,
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black: str | tuple[int, ...],
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white: str | tuple[int, ...],
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mid: str | int | tuple[int, ...] | None = None,
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blackpoint: int = 0,
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whitepoint: int = 255,
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midpoint: int = 127,
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) -> Image.Image:
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"""
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Colorize grayscale image.
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This function calculates a color wedge which maps all black pixels in
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@ -188,10 +202,9 @@ def colorize(image, black, white, mid=None, blackpoint=0, whitepoint=255, midpoi
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assert 0 <= blackpoint <= midpoint <= whitepoint <= 255
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# Define colors from arguments
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black = _color(black, "RGB")
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white = _color(white, "RGB")
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if mid is not None:
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mid = _color(mid, "RGB")
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rgb_black = cast(Sequence[int], _color(black, "RGB"))
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rgb_white = cast(Sequence[int], _color(white, "RGB"))
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rgb_mid = cast(Sequence[int], _color(mid, "RGB")) if mid is not None else None
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# Empty lists for the mapping
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red = []
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@ -200,18 +213,24 @@ def colorize(image, black, white, mid=None, blackpoint=0, whitepoint=255, midpoi
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# Create the low-end values
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for i in range(0, blackpoint):
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red.append(black[0])
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green.append(black[1])
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blue.append(black[2])
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red.append(rgb_black[0])
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green.append(rgb_black[1])
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blue.append(rgb_black[2])
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# Create the mapping (2-color)
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if mid is None:
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if rgb_mid is None:
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range_map = range(0, whitepoint - blackpoint)
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for i in range_map:
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red.append(black[0] + i * (white[0] - black[0]) // len(range_map))
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green.append(black[1] + i * (white[1] - black[1]) // len(range_map))
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blue.append(black[2] + i * (white[2] - black[2]) // len(range_map))
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red.append(
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rgb_black[0] + i * (rgb_white[0] - rgb_black[0]) // len(range_map)
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)
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green.append(
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rgb_black[1] + i * (rgb_white[1] - rgb_black[1]) // len(range_map)
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)
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blue.append(
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rgb_black[2] + i * (rgb_white[2] - rgb_black[2]) // len(range_map)
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)
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# Create the mapping (3-color)
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else:
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@ -219,26 +238,36 @@ def colorize(image, black, white, mid=None, blackpoint=0, whitepoint=255, midpoi
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range_map2 = range(0, whitepoint - midpoint)
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for i in range_map1:
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red.append(black[0] + i * (mid[0] - black[0]) // len(range_map1))
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green.append(black[1] + i * (mid[1] - black[1]) // len(range_map1))
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blue.append(black[2] + i * (mid[2] - black[2]) // len(range_map1))
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red.append(
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rgb_black[0] + i * (rgb_mid[0] - rgb_black[0]) // len(range_map1)
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)
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green.append(
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rgb_black[1] + i * (rgb_mid[1] - rgb_black[1]) // len(range_map1)
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)
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blue.append(
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rgb_black[2] + i * (rgb_mid[2] - rgb_black[2]) // len(range_map1)
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)
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for i in range_map2:
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red.append(mid[0] + i * (white[0] - mid[0]) // len(range_map2))
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green.append(mid[1] + i * (white[1] - mid[1]) // len(range_map2))
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blue.append(mid[2] + i * (white[2] - mid[2]) // len(range_map2))
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red.append(rgb_mid[0] + i * (rgb_white[0] - rgb_mid[0]) // len(range_map2))
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green.append(
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rgb_mid[1] + i * (rgb_white[1] - rgb_mid[1]) // len(range_map2)
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)
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blue.append(rgb_mid[2] + i * (rgb_white[2] - rgb_mid[2]) // len(range_map2))
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# Create the high-end values
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for i in range(0, 256 - whitepoint):
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red.append(white[0])
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green.append(white[1])
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blue.append(white[2])
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red.append(rgb_white[0])
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green.append(rgb_white[1])
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blue.append(rgb_white[2])
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# Return converted image
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image = image.convert("RGB")
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return _lut(image, red + green + blue)
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def contain(image, size, method=Image.Resampling.BICUBIC):
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def contain(
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image: Image.Image, size: tuple[int, int], method: int = Image.Resampling.BICUBIC
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) -> Image.Image:
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"""
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Returns a resized version of the image, set to the maximum width and height
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within the requested size, while maintaining the original aspect ratio.
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@ -267,7 +296,9 @@ def contain(image, size, method=Image.Resampling.BICUBIC):
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return image.resize(size, resample=method)
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def cover(image, size, method=Image.Resampling.BICUBIC):
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def cover(
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image: Image.Image, size: tuple[int, int], method: int = Image.Resampling.BICUBIC
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) -> Image.Image:
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"""
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Returns a resized version of the image, so that the requested size is
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covered, while maintaining the original aspect ratio.
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@ -296,7 +327,13 @@ def cover(image, size, method=Image.Resampling.BICUBIC):
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return image.resize(size, resample=method)
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def pad(image, size, method=Image.Resampling.BICUBIC, color=None, centering=(0.5, 0.5)):
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def pad(
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image: Image.Image,
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size: tuple[int, int],
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method: int = Image.Resampling.BICUBIC,
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color: str | int | tuple[int, ...] | None = None,
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centering: tuple[float, float] = (0.5, 0.5),
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) -> Image.Image:
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"""
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Returns a resized and padded version of the image, expanded to fill the
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requested aspect ratio and size.
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|
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@ -334,7 +371,7 @@ def pad(image, size, method=Image.Resampling.BICUBIC, color=None, centering=(0.5
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return out
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def crop(image, border=0):
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def crop(image: Image.Image, border: int = 0) -> Image.Image:
|
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"""
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Remove border from image. The same amount of pixels are removed
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from all four sides. This function works on all image modes.
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|
|
@ -349,7 +386,9 @@ def crop(image, border=0):
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return image.crop((left, top, image.size[0] - right, image.size[1] - bottom))
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def scale(image, factor, resample=Image.Resampling.BICUBIC):
|
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def scale(
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image: Image.Image, factor: float, resample: int = Image.Resampling.BICUBIC
|
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) -> Image.Image:
|
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"""
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Returns a rescaled image by a specific factor given in parameter.
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A factor greater than 1 expands the image, between 0 and 1 contracts the
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|
|
@ -372,7 +411,19 @@ def scale(image, factor, resample=Image.Resampling.BICUBIC):
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return image.resize(size, resample)
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def deform(image, deformer, resample=Image.Resampling.BILINEAR):
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class _SupportsGetMesh(Protocol):
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def getmesh(
|
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self, image: Image.Image
|
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) -> list[
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tuple[tuple[int, int, int, int], tuple[int, int, int, int, int, int, int, int]]
|
||||
]: ...
|
||||
|
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|
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def deform(
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image: Image.Image,
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deformer: _SupportsGetMesh,
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resample: int = Image.Resampling.BILINEAR,
|
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) -> Image.Image:
|
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"""
|
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Deform the image.
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|
||||
|
|
@ -388,7 +439,7 @@ def deform(image, deformer, resample=Image.Resampling.BILINEAR):
|
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)
|
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|
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|
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def equalize(image, mask=None):
|
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def equalize(image: Image.Image, mask: Image.Image | None = None) -> Image.Image:
|
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"""
|
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Equalize the image histogram. This function applies a non-linear
|
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mapping to the input image, in order to create a uniform
|
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|
|
@ -419,7 +470,11 @@ def equalize(image, mask=None):
|
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return _lut(image, lut)
|
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|
||||
|
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def expand(image, border=0, fill=0):
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def expand(
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image: Image.Image,
|
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border: int | tuple[int, ...] = 0,
|
||||
fill: str | int | tuple[int, ...] = 0,
|
||||
) -> Image.Image:
|
||||
"""
|
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Add border to the image
|
||||
|
||||
|
|
@ -445,7 +500,13 @@ def expand(image, border=0, fill=0):
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return out
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def fit(image, size, method=Image.Resampling.BICUBIC, bleed=0.0, centering=(0.5, 0.5)):
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def fit(
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image: Image.Image,
|
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size: tuple[int, int],
|
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method: int = Image.Resampling.BICUBIC,
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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.
|
||||
|
|
@ -479,13 +540,12 @@ def fit(image, size, method=Image.Resampling.BICUBIC, bleed=0.0, centering=(0.5,
|
|||
# kevin@cazabon.com
|
||||
# https://www.cazabon.com
|
||||
|
||||
# ensure centering is mutable
|
||||
centering = list(centering)
|
||||
centering_x, centering_y = centering
|
||||
|
||||
if not 0.0 <= centering[0] <= 1.0:
|
||||
centering[0] = 0.5
|
||||
if not 0.0 <= centering[1] <= 1.0:
|
||||
centering[1] = 0.5
|
||||
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
|
||||
|
|
@ -522,8 +582,8 @@ def fit(image, size, method=Image.Resampling.BICUBIC, bleed=0.0, centering=(0.5,
|
|||
crop_height = live_size[0] / output_ratio
|
||||
|
||||
# make the crop
|
||||
crop_left = bleed_pixels[0] + (live_size[0] - crop_width) * centering[0]
|
||||
crop_top = bleed_pixels[1] + (live_size[1] - crop_height) * centering[1]
|
||||
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)
|
||||
|
||||
|
|
@ -531,7 +591,7 @@ def fit(image, size, method=Image.Resampling.BICUBIC, bleed=0.0, centering=(0.5,
|
|||
return image.resize(size, method, box=crop)
|
||||
|
||||
|
||||
def flip(image):
|
||||
def flip(image: Image.Image) -> Image.Image:
|
||||
"""
|
||||
Flip the image vertically (top to bottom).
|
||||
|
||||
|
|
@ -541,7 +601,7 @@ def flip(image):
|
|||
return image.transpose(Image.Transpose.FLIP_TOP_BOTTOM)
|
||||
|
||||
|
||||
def grayscale(image):
|
||||
def grayscale(image: Image.Image) -> Image.Image:
|
||||
"""
|
||||
Convert the image to grayscale.
|
||||
|
||||
|
|
@ -551,7 +611,7 @@ def grayscale(image):
|
|||
return image.convert("L")
|
||||
|
||||
|
||||
def invert(image):
|
||||
def invert(image: Image.Image) -> Image.Image:
|
||||
"""
|
||||
Invert (negate) the image.
|
||||
|
||||
|
|
@ -562,7 +622,7 @@ def invert(image):
|
|||
return image.point(lut) if image.mode == "1" else _lut(image, lut)
|
||||
|
||||
|
||||
def mirror(image):
|
||||
def mirror(image: Image.Image) -> Image.Image:
|
||||
"""
|
||||
Flip image horizontally (left to right).
|
||||
|
||||
|
|
@ -572,7 +632,7 @@ def mirror(image):
|
|||
return image.transpose(Image.Transpose.FLIP_LEFT_RIGHT)
|
||||
|
||||
|
||||
def posterize(image, bits):
|
||||
def posterize(image: Image.Image, bits: int) -> Image.Image:
|
||||
"""
|
||||
Reduce the number of bits for each color channel.
|
||||
|
||||
|
|
@ -585,7 +645,7 @@ def posterize(image, bits):
|
|||
return _lut(image, lut)
|
||||
|
||||
|
||||
def solarize(image, threshold=128):
|
||||
def solarize(image: Image.Image, threshold: int = 128) -> Image.Image:
|
||||
"""
|
||||
Invert all pixel values above a threshold.
|
||||
|
||||
|
|
@ -602,7 +662,7 @@ def solarize(image, threshold=128):
|
|||
return _lut(image, lut)
|
||||
|
||||
|
||||
def exif_transpose(image, *, in_place=False):
|
||||
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.
|
||||
|
|
@ -616,7 +676,7 @@ def exif_transpose(image, *, in_place=False):
|
|||
"""
|
||||
image.load()
|
||||
image_exif = image.getexif()
|
||||
orientation = image_exif.get(ExifTags.Base.Orientation)
|
||||
orientation = image_exif.get(ExifTags.Base.Orientation, 1)
|
||||
method = {
|
||||
2: Image.Transpose.FLIP_LEFT_RIGHT,
|
||||
3: Image.Transpose.ROTATE_180,
|
||||
|
|
@ -653,3 +713,4 @@ def exif_transpose(image, *, in_place=False):
|
|||
return transposed_image
|
||||
elif not in_place:
|
||||
return image.copy()
|
||||
return None
|
||||
|
|
|
|||
|
|
@ -18,6 +18,7 @@
|
|||
from __future__ import annotations
|
||||
|
||||
import array
|
||||
from typing import Sequence
|
||||
|
||||
from . import GimpGradientFile, GimpPaletteFile, ImageColor, PaletteFile
|
||||
|
||||
|
|
@ -34,11 +35,11 @@ class ImagePalette:
|
|||
Defaults to an empty palette.
|
||||
"""
|
||||
|
||||
def __init__(self, mode="RGB", palette=None):
|
||||
def __init__(self, mode: str = "RGB", palette: Sequence[int] | None = None) -> None:
|
||||
self.mode = mode
|
||||
self.rawmode = None # if set, palette contains raw data
|
||||
self.palette = palette or bytearray()
|
||||
self.dirty = None
|
||||
self.dirty: int | None = None
|
||||
|
||||
@property
|
||||
def palette(self):
|
||||
|
|
@ -127,7 +128,7 @@ class ImagePalette:
|
|||
raise ValueError(msg) from e
|
||||
return index
|
||||
|
||||
def getcolor(self, color, image=None):
|
||||
def getcolor(self, color, image=None) -> int:
|
||||
"""Given an rgb tuple, allocate palette entry.
|
||||
|
||||
.. warning:: This method is experimental.
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user