mirror of https://gitlab.com/bashrc2/epicyon
185 lines
6.6 KiB
Python
185 lines
6.6 KiB
Python
"""
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Copyright (c) 2019 Lorenz Diener
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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* The above copyright notice and this permission notice shall be included
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in all copies or substantial portions of the Software.
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* You and any organization you work for may not promote white supremacy, hate
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speech and homo- or transphobia - this license is void if you do.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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https://github.com/halcy/blurhash-python
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Pure python blurhash decoder with no additional dependencies, for
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both de- and encoding.
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Very close port of the original Swift implementation by Dag Ågren.
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"""
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import math
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# Alphabet for base 83
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alphabet = \
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"0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ" + \
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"abcdefghijklmnopqrstuvwxyz#$%*+,-.:;=?@[]^_{|}~"
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alphabet_values = dict(zip(alphabet, range(len(alphabet))))
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def _base83_encode(value, length):
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"""
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Decodes an integer to a base83 string, as used in blurhash.
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Length is how long the resulting string should be. Will complain
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if the specified length is too short.
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"""
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if int(value) // (83 ** (length)) != 0:
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raise ValueError("Specified length is too short to " +
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"encode given value.")
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result = ""
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for i in range(1, length + 1):
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digit = int(value) // (83 ** (length - i)) % 83
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result += alphabet[int(digit)]
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return result
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def _srgb_to_linear(value):
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"""
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srgb 0-255 integer to linear 0.0-1.0 floating point conversion.
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"""
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value = float(value) / 255.0
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if value <= 0.04045:
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return value / 12.92
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return math.pow((value + 0.055) / 1.055, 2.4)
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def _sign_pow(value, exp):
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"""
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Sign-preserving exponentiation.
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"""
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return math.copysign(math.pow(abs(value), exp), value)
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def _linear_to_srgb(value):
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"""
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linear 0.0-1.0 floating point to srgb 0-255 integer conversion.
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"""
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value = max(0.0, min(1.0, value))
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if value <= 0.0031308:
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return int(value * 12.92 * 255 + 0.5)
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return int((1.055 * math.pow(value, 1 / 2.4) - 0.055) * 255 + 0.5)
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def blurhash_encode(image, components_x=4, components_y=4, linear=False):
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"""
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Calculates the blurhash for an image using the given x and y
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component counts.
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Image should be a 3-dimensional array, with the first dimension
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being y, the second being x, and the third being the three rgb
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components that are assumed to be 0-255 srgb integers
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(incidentally, this is the format you will get from a PIL RGB image).
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You can also pass in already linear data - to do this, set linear
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to True. This is useful if you want to encode a version of your
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image resized to a smaller size (which you should ideally do in
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linear colour).
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"""
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if components_x < 1 or components_x > 9 or \
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components_y < 1 or components_y > 9:
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raise ValueError("x and y component counts must be " +
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"between 1 and 9 inclusive.")
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height = float(len(image))
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width = float(len(image[0]))
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# Convert to linear if neeeded
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image_linear = []
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if linear is False:
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for y in range(int(height)):
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image_linear_line = []
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for x in range(int(width)):
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image_linear_line.append([
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_srgb_to_linear(image[y][x][0]),
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_srgb_to_linear(image[y][x][1]),
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_srgb_to_linear(image[y][x][2])
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])
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image_linear.append(image_linear_line)
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else:
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image_linear = image
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# Calculate components
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components = []
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max_ac_component = 0.0
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for j in range(components_y):
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for i in range(components_x):
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norm_factor = 1.0 if (i == 0 and j == 0) else 2.0
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component = [0.0, 0.0, 0.0]
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for y in range(int(height)):
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for x in range(int(width)):
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basis = \
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norm_factor * \
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math.cos(math.pi * float(i) * float(x) / width) * \
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math.cos(math.pi * float(j) * float(y) / height)
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component[0] += basis * image_linear[y][x][0]
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component[1] += basis * image_linear[y][x][1]
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component[2] += basis * image_linear[y][x][2]
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component[0] /= (width * height)
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component[1] /= (width * height)
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component[2] /= (width * height)
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components.append(component)
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if not (i == 0 and j == 0):
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max_ac_component = \
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max(max_ac_component, abs(component[0]),
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abs(component[1]), abs(component[2]))
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# Encode components
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dc_value = (_linear_to_srgb(components[0][0]) << 16) + \
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(_linear_to_srgb(components[0][1]) << 8) + \
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_linear_to_srgb(components[0][2])
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quant_max_ac_component = int(max(0, min(82,
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math.floor(max_ac_component *
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166 - 0.5))))
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ac_component_norm_factor = float(quant_max_ac_component + 1) / 166.0
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ac_values = []
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for r, g, b in components[1:]:
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r2 = r / ac_component_norm_factor
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g2 = g / ac_component_norm_factor
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b2 = b / ac_component_norm_factor
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r3 = math.floor(_sign_pow(r2, 0.5) * 9.0 + 9.5)
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g3 = math.floor(_sign_pow(g2, 0.5) * 9.0 + 9.5)
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b3 = math.floor(_sign_pow(b2, 0.5) * 9.0 + 9.5)
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ac_values.append(
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int(max(0.0, min(18.0, r3))) * 19 * 19 +
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int(max(0.0, min(18.0, g3))) * 19 +
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int(max(0.0, min(18.0, b3)))
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)
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# Build final blurhash
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blurhash = ""
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blurhashValue = (components_x - 1) + (components_y - 1) * 9
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blurhash += _base83_encode(blurhashValue, 1)
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blurhash += _base83_encode(quant_max_ac_component, 1)
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blurhash += _base83_encode(dc_value, 4)
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for ac_value in ac_values:
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blurhash += _base83_encode(ac_value, 2)
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return blurhash
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