mirror of https://gitlab.com/bashrc2/epicyon
				
				
				
			
		
			
	
	
		
			255 lines
		
	
	
		
			9.7 KiB
		
	
	
	
		
			Python
		
	
	
		
		
			
		
	
	
			255 lines
		
	
	
		
			9.7 KiB
		
	
	
	
		
			Python
		
	
	
|  | """
 | ||
|  | Copyright (c) 2019 Lorenz Diener | ||
|  | 
 | ||
|  | Permission is hereby granted, free of charge, to any person obtaining a copy | ||
|  | of this software and associated documentation files (the "Software"), to deal | ||
|  | in the Software without restriction, including without limitation the rights | ||
|  | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell | ||
|  | copies of the Software, and to permit persons to whom the Software is | ||
|  | furnished to do so, subject to the following conditions: | ||
|  | 
 | ||
|  | * The above copyright notice and this permission notice shall be included in all | ||
|  | copies or substantial portions of the Software. | ||
|  | * You and any organization you work for may not promote white supremacy, hate  | ||
|  | speech and homo- or transphobia - this license is void if you do. | ||
|  | 
 | ||
|  | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR | ||
|  | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, | ||
|  | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE | ||
|  | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER | ||
|  | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, | ||
|  | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE | ||
|  | SOFTWARE. | ||
|  | 
 | ||
|  | https://github.com/halcy/blurhash-python | ||
|  | 
 | ||
|  | Pure python blurhash decoder with no additional dependencies, for  | ||
|  | both de- and encoding. | ||
|  | 
 | ||
|  | Very close port of the original Swift implementation by Dag Ågren. | ||
|  | """
 | ||
|  | 
 | ||
|  | import math | ||
|  | 
 | ||
|  | # Alphabet for base 83 | ||
|  | alphabet = "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz#$%*+,-.:;=?@[]^_{|}~" | ||
|  | alphabet_values = dict(zip(alphabet, range(len(alphabet)))) | ||
|  | 
 | ||
|  | def base83_decode(base83_str): | ||
|  |     """
 | ||
|  |     Decodes a base83 string, as used in blurhash, to an integer. | ||
|  |     """
 | ||
|  |     value = 0 | ||
|  |     for base83_char in base83_str: | ||
|  |         value = value * 83 + alphabet_values[base83_char] | ||
|  |     return value | ||
|  | 
 | ||
|  | def base83_encode(value, length): | ||
|  |     """
 | ||
|  |     Decodes an integer to a base83 string, as used in blurhash. | ||
|  |      | ||
|  |     Length is how long the resulting string should be. Will complain | ||
|  |     if the specified length is too short. | ||
|  |     """
 | ||
|  |     if int(value) // (83 ** (length)) != 0: | ||
|  |         raise ValueError("Specified length is too short to encode given value.") | ||
|  |          | ||
|  |     result = "" | ||
|  |     for i in range(1, length + 1): | ||
|  |         digit = int(value) // (83 ** (length - i)) % 83 | ||
|  |         result += alphabet[int(digit)] | ||
|  |     return result | ||
|  | 
 | ||
|  | def srgb_to_linear(value): | ||
|  |     """
 | ||
|  |     srgb 0-255 integer to linear 0.0-1.0 floating point conversion. | ||
|  |     """
 | ||
|  |     value = float(value) / 255.0 | ||
|  |     if value <= 0.04045: | ||
|  |         return value / 12.92 | ||
|  |     return math.pow((value + 0.055) / 1.055, 2.4) | ||
|  | 
 | ||
|  | def sign_pow(value, exp): | ||
|  |     """
 | ||
|  |     Sign-preserving exponentiation. | ||
|  |     """
 | ||
|  |     return math.copysign(math.pow(abs(value), exp), value) | ||
|  | 
 | ||
|  | def linear_to_srgb(value): | ||
|  |     """
 | ||
|  |     linear 0.0-1.0 floating point to srgb 0-255 integer conversion. | ||
|  |     """
 | ||
|  |     value = max(0.0, min(1.0, value)) | ||
|  |     if value <= 0.0031308: | ||
|  |         return int(value * 12.92 * 255 + 0.5) | ||
|  |     return int((1.055 * math.pow(value, 1 / 2.4) - 0.055) * 255 + 0.5) | ||
|  | 
 | ||
|  | def blurhash_components(blurhash): | ||
|  |     """
 | ||
|  |     Decodes and returns the number of x and y components in the given blurhash. | ||
|  |     """
 | ||
|  |     if len(blurhash) < 6: | ||
|  |         raise ValueError("BlurHash must be at least 6 characters long.") | ||
|  |      | ||
|  |     # Decode metadata | ||
|  |     size_info = base83_decode(blurhash[0]) | ||
|  |     size_y = int(size_info / 9) + 1 | ||
|  |     size_x = (size_info % 9) + 1 | ||
|  |      | ||
|  |     return size_x, size_y | ||
|  | 
 | ||
|  | def blurhash_decode(blurhash, width, height, punch = 1.0, linear = False): | ||
|  |     """
 | ||
|  |     Decodes the given blurhash to an image of the specified size. | ||
|  |      | ||
|  |     Returns the resulting image a list of lists of 3-value sRGB 8 bit integer | ||
|  |     lists. Set linear to True if you would prefer to get linear floating point  | ||
|  |     RGB back. | ||
|  |      | ||
|  |     The punch parameter can be used to de- or increase the contrast of the | ||
|  |     resulting image. | ||
|  |      | ||
|  |     As per the original implementation it is suggested to only decode | ||
|  |     to a relatively small size and then scale the result up, as it | ||
|  |     basically looks the same anyways. | ||
|  |     """
 | ||
|  |     if len(blurhash) < 6: | ||
|  |         raise ValueError("BlurHash must be at least 6 characters long.") | ||
|  |      | ||
|  |     # Decode metadata | ||
|  |     size_info = base83_decode(blurhash[0]) | ||
|  |     size_y = int(size_info / 9) + 1 | ||
|  |     size_x = (size_info % 9) + 1 | ||
|  |      | ||
|  |     quant_max_value = base83_decode(blurhash[1]) | ||
|  |     real_max_value = (float(quant_max_value + 1) / 166.0) * punch | ||
|  |      | ||
|  |     # Make sure we at least have the right number of characters | ||
|  |     if len(blurhash) != 4 + 2 * size_x * size_y: | ||
|  |         raise ValueError("Invalid BlurHash length.") | ||
|  |          | ||
|  |     # Decode DC component | ||
|  |     dc_value = base83_decode(blurhash[2:6]) | ||
|  |     colours = [( | ||
|  |         srgb_to_linear(dc_value >> 16), | ||
|  |         srgb_to_linear((dc_value >> 8) & 255), | ||
|  |         srgb_to_linear(dc_value & 255) | ||
|  |     )] | ||
|  |      | ||
|  |     # Decode AC components | ||
|  |     for component in range(1, size_x * size_y): | ||
|  |         ac_value = base83_decode(blurhash[4+component*2:4+(component+1)*2]) | ||
|  |         colours.append(( | ||
|  |             sign_pow((float(int(ac_value / (19 * 19))) - 9.0) / 9.0, 2.0) * real_max_value, | ||
|  |             sign_pow((float(int(ac_value / 19) % 19) - 9.0) / 9.0, 2.0) * real_max_value, | ||
|  |             sign_pow((float(ac_value % 19) - 9.0) / 9.0, 2.0) * real_max_value | ||
|  |         )) | ||
|  |      | ||
|  |     # Return image RGB values, as a list of lists of lists,  | ||
|  |     # consumable by something like numpy or PIL. | ||
|  |     pixels = [] | ||
|  |     for y in range(height): | ||
|  |         pixel_row = [] | ||
|  |         for x in range(width): | ||
|  |             pixel = [0.0, 0.0, 0.0] | ||
|  | 
 | ||
|  |             for j in range(size_y): | ||
|  |                 for i in range(size_x): | ||
|  |                     basis = math.cos(math.pi * float(x) * float(i) / float(width)) * \ | ||
|  |                             math.cos(math.pi * float(y) * float(j) / float(height)) | ||
|  |                     colour = colours[i + j * size_x] | ||
|  |                     pixel[0] += colour[0] * basis | ||
|  |                     pixel[1] += colour[1] * basis | ||
|  |                     pixel[2] += colour[2] * basis | ||
|  |             if linear == False: | ||
|  |                 pixel_row.append([ | ||
|  |                     linear_to_srgb(pixel[0]), | ||
|  |                     linear_to_srgb(pixel[1]), | ||
|  |                     linear_to_srgb(pixel[2]), | ||
|  |                 ]) | ||
|  |             else: | ||
|  |                 pixel_row.append(pixel) | ||
|  |         pixels.append(pixel_row) | ||
|  |     return pixels | ||
|  |      | ||
|  | def blurhash_encode(image, components_x = 4, components_y = 4, linear = False): | ||
|  |     """
 | ||
|  |     Calculates the blurhash for an image using the given x and y component counts. | ||
|  |      | ||
|  |     Image should be a 3-dimensional array, with the first dimension being y, the second | ||
|  |     being x, and the third being the three rgb components that are assumed to be 0-255  | ||
|  |     srgb integers (incidentally, this is the format you will get from a PIL RGB image). | ||
|  |      | ||
|  |     You can also pass in already linear data - to do this, set linear to True. This is | ||
|  |     useful if you want to encode a version of your image resized to a smaller size (which | ||
|  |     you should ideally do in linear colour). | ||
|  |     """
 | ||
|  |     if components_x < 1 or components_x > 9 or components_y < 1 or components_y > 9:  | ||
|  |         raise ValueError("x and y component counts must be between 1 and 9 inclusive.") | ||
|  |     height = float(len(image)) | ||
|  |     width = float(len(image[0])) | ||
|  |      | ||
|  |     # Convert to linear if neeeded | ||
|  |     image_linear = [] | ||
|  |     if linear == False: | ||
|  |         for y in range(int(height)): | ||
|  |             image_linear_line = [] | ||
|  |             for x in range(int(width)): | ||
|  |                 image_linear_line.append([ | ||
|  |                     srgb_to_linear(image[y][x][0]), | ||
|  |                     srgb_to_linear(image[y][x][1]), | ||
|  |                     srgb_to_linear(image[y][x][2]) | ||
|  |                 ]) | ||
|  |             image_linear.append(image_linear_line) | ||
|  |     else: | ||
|  |         image_linear = image | ||
|  |          | ||
|  |     # Calculate components | ||
|  |     components = [] | ||
|  |     max_ac_component = 0.0 | ||
|  |     for j in range(components_y): | ||
|  |         for i in range(components_x): | ||
|  |             norm_factor = 1.0 if (i == 0 and j == 0) else 2.0 | ||
|  |             component = [0.0, 0.0, 0.0] | ||
|  |             for y in range(int(height)): | ||
|  |                 for x in range(int(width)): | ||
|  |                     basis = norm_factor * math.cos(math.pi * float(i) * float(x) / width) * \ | ||
|  |                                           math.cos(math.pi * float(j) * float(y) / height) | ||
|  |                     component[0] += basis * image_linear[y][x][0] | ||
|  |                     component[1] += basis * image_linear[y][x][1] | ||
|  |                     component[2] += basis * image_linear[y][x][2] | ||
|  |                      | ||
|  |             component[0] /= (width * height) | ||
|  |             component[1] /= (width * height) | ||
|  |             component[2] /= (width * height) | ||
|  |             components.append(component) | ||
|  |              | ||
|  |             if not (i == 0 and j == 0): | ||
|  |                 max_ac_component = max(max_ac_component, abs(component[0]), abs(component[1]), abs(component[2])) | ||
|  |                  | ||
|  |     # Encode components | ||
|  |     dc_value = (linear_to_srgb(components[0][0]) << 16) + \ | ||
|  |                (linear_to_srgb(components[0][1]) << 8) + \ | ||
|  |                linear_to_srgb(components[0][2]) | ||
|  |      | ||
|  |     quant_max_ac_component = int(max(0, min(82, math.floor(max_ac_component * 166 - 0.5)))) | ||
|  |     ac_component_norm_factor = float(quant_max_ac_component + 1) / 166.0 | ||
|  |      | ||
|  |     ac_values = [] | ||
|  |     for r, g, b in components[1:]: | ||
|  |         ac_values.append( | ||
|  |             int(max(0.0, min(18.0, math.floor(sign_pow(r / ac_component_norm_factor, 0.5) * 9.0 + 9.5)))) * 19 * 19 + \ | ||
|  |             int(max(0.0, min(18.0, math.floor(sign_pow(g / ac_component_norm_factor, 0.5) * 9.0 + 9.5)))) * 19 + \ | ||
|  |             int(max(0.0, min(18.0, math.floor(sign_pow(b / ac_component_norm_factor, 0.5) * 9.0 + 9.5)))) | ||
|  |         ) | ||
|  |          | ||
|  |     # Build final blurhash | ||
|  |     blurhash = "" | ||
|  |     blurhash += base83_encode((components_x - 1) + (components_y - 1) * 9, 1) | ||
|  |     blurhash += base83_encode(quant_max_ac_component, 1) | ||
|  |     blurhash += base83_encode(dc_value, 4) | ||
|  |     for ac_value in ac_values: | ||
|  |         blurhash += base83_encode(ac_value, 2) | ||
|  |      | ||
|  |     return blurhash |