forked from indymedia/epicyon
				
			
		
			
				
	
	
		
			289 lines
		
	
	
		
			10 KiB
		
	
	
	
		
			Python
		
	
	
			
		
		
	
	
			289 lines
		
	
	
		
			10 KiB
		
	
	
	
		
			Python
		
	
	
| """
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| Copyright (c) 2019 Lorenz Diener
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| 
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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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| 
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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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| 
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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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| 
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| https://github.com/halcy/blurhash-python
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| 
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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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| 
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| Very close port of the original Swift implementation by Dag Ågren.
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| """
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| 
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| import math
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| 
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| 
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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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| 
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| 
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| def base83_decode(base83_str):
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|     """
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|     Decodes a base83 string, as used in blurhash, to an integer.
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|     """
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|     value = 0
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|     for base83_char in base83_str:
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|         value = value * 83 + alphabet_values[base83_char]
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|     return value
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| 
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| 
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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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| 
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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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| 
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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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| 
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| 
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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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| 
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| 
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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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| 
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| 
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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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| 
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| 
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| def blurhash_components(blurhash):
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|     """
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|     Decodes and returns the number of x and y components in the given blurhash.
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|     """
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|     if len(blurhash) < 6:
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|         raise ValueError("BlurHash must be at least 6 characters long.")
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| 
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|     # Decode metadata
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|     size_info = base83_decode(blurhash[0])
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|     size_y = int(size_info / 9) + 1
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|     size_x = (size_info % 9) + 1
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| 
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|     return size_x, size_y
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| 
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| 
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| def blurhash_decode(blurhash, width, height, punch=1.0, linear=False):
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|     """
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|     Decodes the given blurhash to an image of the specified size.
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| 
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|     Returns the resulting image a list of lists of 3-value sRGB 8 bit integer
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|     lists. Set linear to True if you would prefer to get linear floating point
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|     RGB back.
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| 
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|     The punch parameter can be used to de- or increase the contrast of the
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|     resulting image.
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| 
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|     As per the original implementation it is suggested to only decode
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|     to a relatively small size and then scale the result up, as it
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|     basically looks the same anyways.
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|     """
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|     if len(blurhash) < 6:
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|         raise ValueError("BlurHash must be at least 6 characters long.")
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| 
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|     # Decode metadata
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|     size_info = base83_decode(blurhash[0])
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|     size_y = int(size_info / 9) + 1
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|     size_x = (size_info % 9) + 1
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| 
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|     quant_max_value = base83_decode(blurhash[1])
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|     real_max_value = (float(quant_max_value + 1) / 166.0) * punch
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| 
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|     # Make sure we at least have the right number of characters
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|     if len(blurhash) != 4 + 2 * size_x * size_y:
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|         raise ValueError("Invalid BlurHash length.")
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| 
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|     # Decode DC component
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|     dc_value = base83_decode(blurhash[2:6])
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|     colours = [(
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|         srgb_to_linear(dc_value >> 16),
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|         srgb_to_linear((dc_value >> 8) & 255),
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|         srgb_to_linear(dc_value & 255)
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|     )]
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| 
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|     # Decode AC components
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|     for component in range(1, size_x * size_y):
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|         ac_value = base83_decode(blurhash[4+component*2:4+(component+1)*2])
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|         colours.append((
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|             sign_pow((float(int(ac_value / (19 * 19))) - 9.0)
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|                      / 9.0, 2.0) * real_max_value,
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|             sign_pow((float(int(ac_value / 19) % 19) - 9.0)
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|                      / 9.0, 2.0) * real_max_value,
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|             sign_pow((float(ac_value % 19) - 9.0)
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|                      / 9.0, 2.0) * real_max_value
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|         ))
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| 
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|     # Return image RGB values, as a list of lists of lists,
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|     # consumable by something like numpy or PIL.
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|     pixels = []
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|     for y in range(height):
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|         pixel_row = []
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|         for x in range(width):
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|             pixel = [0.0, 0.0, 0.0]
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| 
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|             for j in range(size_y):
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|                 for i in range(size_x):
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|                     basis = \
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|                         math.cos(math.pi * float(x) * float(i) /
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|                                  float(width)) * \
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|                         math.cos(math.pi * float(y) * float(j) / float(height))
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|                     colour = colours[i + j * size_x]
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|                     pixel[0] += colour[0] * basis
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|                     pixel[1] += colour[1] * basis
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|                     pixel[2] += colour[2] * basis
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|             if linear is False:
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|                 pixel_row.append([
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|                     linear_to_srgb(pixel[0]),
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|                     linear_to_srgb(pixel[1]),
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|                     linear_to_srgb(pixel[2]),
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|                 ])
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|             else:
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|                 pixel_row.append(pixel)
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|         pixels.append(pixel_row)
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|     return pixels
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| 
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| 
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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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| 
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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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| 
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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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| 
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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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| 
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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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| 
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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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| 
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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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| 
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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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| 
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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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| 
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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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| 
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|     # Build final blurhash
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|     blurhash = ""
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|     blurhash += base83_encode((components_x - 1) + (components_y - 1) * 9, 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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| 
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|     return blurhash
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