File size: 7,003 Bytes
b6068b4 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 |
#
# The Python Imaging Library.
# $Id$
#
# standard channel operations
#
# History:
# 1996-03-24 fl Created
# 1996-08-13 fl Added logical operations (for "1" images)
# 2000-10-12 fl Added offset method (from Image.py)
#
# Copyright (c) 1997-2000 by Secret Labs AB
# Copyright (c) 1996-2000 by Fredrik Lundh
#
# See the README file for information on usage and redistribution.
#
from . import Image
def constant(image, value):
"""Fill a channel with a given grey level.
:rtype: :py:class:`~PIL.Image.Image`
"""
return Image.new("L", image.size, value)
def duplicate(image):
"""Copy a channel. Alias for :py:meth:`PIL.Image.Image.copy`.
:rtype: :py:class:`~PIL.Image.Image`
"""
return image.copy()
def invert(image):
"""
Invert an image (channel). ::
out = MAX - image
:rtype: :py:class:`~PIL.Image.Image`
"""
image.load()
return image._new(image.im.chop_invert())
def lighter(image1, image2):
"""
Compares the two images, pixel by pixel, and returns a new image containing
the lighter values. ::
out = max(image1, image2)
:rtype: :py:class:`~PIL.Image.Image`
"""
image1.load()
image2.load()
return image1._new(image1.im.chop_lighter(image2.im))
def darker(image1, image2):
"""
Compares the two images, pixel by pixel, and returns a new image containing
the darker values. ::
out = min(image1, image2)
:rtype: :py:class:`~PIL.Image.Image`
"""
image1.load()
image2.load()
return image1._new(image1.im.chop_darker(image2.im))
def difference(image1, image2):
"""
Returns the absolute value of the pixel-by-pixel difference between the two
images. ::
out = abs(image1 - image2)
:rtype: :py:class:`~PIL.Image.Image`
"""
image1.load()
image2.load()
return image1._new(image1.im.chop_difference(image2.im))
def multiply(image1, image2):
"""
Superimposes two images on top of each other.
If you multiply an image with a solid black image, the result is black. If
you multiply with a solid white image, the image is unaffected. ::
out = image1 * image2 / MAX
:rtype: :py:class:`~PIL.Image.Image`
"""
image1.load()
image2.load()
return image1._new(image1.im.chop_multiply(image2.im))
def screen(image1, image2):
"""
Superimposes two inverted images on top of each other. ::
out = MAX - ((MAX - image1) * (MAX - image2) / MAX)
:rtype: :py:class:`~PIL.Image.Image`
"""
image1.load()
image2.load()
return image1._new(image1.im.chop_screen(image2.im))
def soft_light(image1, image2):
"""
Superimposes two images on top of each other using the Soft Light algorithm
:rtype: :py:class:`~PIL.Image.Image`
"""
image1.load()
image2.load()
return image1._new(image1.im.chop_soft_light(image2.im))
def hard_light(image1, image2):
"""
Superimposes two images on top of each other using the Hard Light algorithm
:rtype: :py:class:`~PIL.Image.Image`
"""
image1.load()
image2.load()
return image1._new(image1.im.chop_hard_light(image2.im))
def overlay(image1, image2):
"""
Superimposes two images on top of each other using the Overlay algorithm
:rtype: :py:class:`~PIL.Image.Image`
"""
image1.load()
image2.load()
return image1._new(image1.im.chop_overlay(image2.im))
def add(image1, image2, scale=1.0, offset=0):
"""
Adds two images, dividing the result by scale and adding the
offset. If omitted, scale defaults to 1.0, and offset to 0.0. ::
out = ((image1 + image2) / scale + offset)
:rtype: :py:class:`~PIL.Image.Image`
"""
image1.load()
image2.load()
return image1._new(image1.im.chop_add(image2.im, scale, offset))
def subtract(image1, image2, scale=1.0, offset=0):
"""
Subtracts two images, dividing the result by scale and adding the offset.
If omitted, scale defaults to 1.0, and offset to 0.0. ::
out = ((image1 - image2) / scale + offset)
:rtype: :py:class:`~PIL.Image.Image`
"""
image1.load()
image2.load()
return image1._new(image1.im.chop_subtract(image2.im, scale, offset))
def add_modulo(image1, image2):
"""Add two images, without clipping the result. ::
out = ((image1 + image2) % MAX)
:rtype: :py:class:`~PIL.Image.Image`
"""
image1.load()
image2.load()
return image1._new(image1.im.chop_add_modulo(image2.im))
def subtract_modulo(image1, image2):
"""Subtract two images, without clipping the result. ::
out = ((image1 - image2) % MAX)
:rtype: :py:class:`~PIL.Image.Image`
"""
image1.load()
image2.load()
return image1._new(image1.im.chop_subtract_modulo(image2.im))
def logical_and(image1, image2):
"""Logical AND between two images.
Both of the images must have mode "1". If you would like to perform a
logical AND on an image with a mode other than "1", try
:py:meth:`~PIL.ImageChops.multiply` instead, using a black-and-white mask
as the second image. ::
out = ((image1 and image2) % MAX)
:rtype: :py:class:`~PIL.Image.Image`
"""
image1.load()
image2.load()
return image1._new(image1.im.chop_and(image2.im))
def logical_or(image1, image2):
"""Logical OR between two images.
Both of the images must have mode "1". ::
out = ((image1 or image2) % MAX)
:rtype: :py:class:`~PIL.Image.Image`
"""
image1.load()
image2.load()
return image1._new(image1.im.chop_or(image2.im))
def logical_xor(image1, image2):
"""Logical XOR between two images.
Both of the images must have mode "1". ::
out = ((bool(image1) != bool(image2)) % MAX)
:rtype: :py:class:`~PIL.Image.Image`
"""
image1.load()
image2.load()
return image1._new(image1.im.chop_xor(image2.im))
def blend(image1, image2, alpha):
"""Blend images using constant transparency weight. Alias for
:py:func:`PIL.Image.blend`.
:rtype: :py:class:`~PIL.Image.Image`
"""
return Image.blend(image1, image2, alpha)
def composite(image1, image2, mask):
"""Create composite using transparency mask. Alias for
:py:func:`PIL.Image.composite`.
:rtype: :py:class:`~PIL.Image.Image`
"""
return Image.composite(image1, image2, mask)
def offset(image, xoffset, yoffset=None):
"""Returns a copy of the image where data has been offset by the given
distances. Data wraps around the edges. If ``yoffset`` is omitted, it
is assumed to be equal to ``xoffset``.
:param image: Input image.
:param xoffset: The horizontal distance.
:param yoffset: The vertical distance. If omitted, both
distances are set to the same value.
:rtype: :py:class:`~PIL.Image.Image`
"""
if yoffset is None:
yoffset = xoffset
image.load()
return image._new(image.im.offset(xoffset, yoffset))
|