Full process is now producing and optimizing svg layers. It needs to be made deterministic by sorting the colors and have the ability to compare in different color spaces.
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10
py/common.py
10
py/common.py
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@ -155,4 +155,14 @@ def rgb_to_luma (r, g, b) :
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return (r * R) + (g * G) + (b * B)
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def convertScale(img, alpha, beta):
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"""Add bias and gain to an image with saturation arithmetics. Unlike
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cv2.convertScaleAbs, it does not take an absolute value, which would lead to
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nonsensical results (e.g., a pixel at 44 with alpha = 3 and beta = -210
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becomes 78 with OpenCV, when in fact it should become 0).
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"""
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new_img = img * alpha + beta
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new_img[new_img < 0] = 0
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new_img[new_img > 255] = 255
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return new_img.astype(np.uint8)
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@ -2,11 +2,12 @@ canvasWidth=1301
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canvasHeight=914
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windowWidth=1301
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windowHeight=914
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dotSize=6
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maxGenerations=50
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maxParticles=2500
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minDotSize=1.8
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line=1.8
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maxParticles=10000
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minDotSize=2.3
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maxDotSize=2.3
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dotSizeFactor=0
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line=2.3
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fill=true
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mode="stipple"
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display=true
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display=false
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@ -2,9 +2,19 @@ from sklearn.cluster import MiniBatchKMeans
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import numpy as np
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import argparse
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import cv2
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from common import convert_color, closest_color_weighted_euclidean, closest_color_euclidean, create_colored_image, remove_from_list, list_match
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from common import convert_color, closest_color_weighted_euclidean, closest_color_euclidean, create_colored_image, remove_from_list, list_match, to_luma, convertScale
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import os
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import subprocess
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from functools import cmp_to_key
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def sort_pallete (a, b):
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A = to_luma(a, 'BGR')
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B = to_luma(b, 'BGR')
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if A > B :
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return 1
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if B < A :
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return -1
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return 0
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class Posterize:
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"""Posterize an image and then find nearest colors to use"""
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@ -13,6 +23,8 @@ class Posterize:
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original_colors = []
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layers = []
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previews = []
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svgs = []
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headless = False
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pallete = None
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pallete_space = 'BGR'
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@ -23,20 +35,21 @@ class Posterize:
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h = 0
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w = 0
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n_colors = 3
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max_particles = 3000
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max_particles = 17000
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conf = os.path.abspath('./conf/base.conf')
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stipple_gen = os.path.abspath('../../../src/stipple_gen')
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stipple_gen = os.path.abspath('../../stipple_gen')
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white = [255, 255, 255]
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output = None
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def __init__ (self, image, pallete, n_colors, output) :
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def __init__ (self, image, pallete, n_colors, output, headless) :
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self.image = cv2.imread(image)
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(self.h, self.w) = self.image.shape[:2]
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self.pallete = pallete
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self.n_colors = n_colors + 1
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self.output = output
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self.headless = headless
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if not os.path.exists(self.output) :
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print(f'Output directory {self.output} does not exist, creating...')
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@ -65,9 +78,7 @@ class Posterize:
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self.image = bgrquant
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cv2.imshow('image', bgrquant)
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cv2.waitKey(0)
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cv2.destroyAllWindows()
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self.show(bgrquant)
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def determine_colors (self):
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reshaped = self.image.reshape(-1, self.image.shape[2])
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@ -108,11 +119,14 @@ class Posterize:
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'space' : self.pallete_space
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})
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mask = cv2.bitwise_not(mask)
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composite[mask > 0] = np.array(closest)
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composite[mask > 0] = np.array(convert_color(closest, self.pallete_space, 'BGR'))
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cv2.imshow('image', composite)
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cv2.waitKey(0)
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cv2.destroyAllWindows()
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composite_name = f'posterized.png'
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composite_path = os.path.join(self.output, composite_name)
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cv2.imwrite(composite_path, composite)
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self.show(composite)
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def extract_color_mask (self, image, color):
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mask = cv2.inRange(image, color, color)
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@ -121,9 +135,15 @@ class Posterize:
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def flatten_pallete (self) :
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for color in self.pallete.colors:
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self.colors.append(color['color'])
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self.colors_dict[f'{color["color"][0]},{color["color"][1]},{color["color"][2]}'] = color['name']
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self.colors_dict[f"{color['color'][0]},{color['color'][1]},{color['color'][2]}"] = color['name']
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self.pallete_space = color['space']
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#self.colors = sorted(self.colors, key=cmp_to_key(sort_pallete))
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#for color in self.colors :
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# print(to_luma(color, self.pallete_space))
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#quit()
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def match_color_name (self, key) :
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return self.colors_dict[f'{key[0]},{key[1]},{key[2]}']
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@ -154,10 +174,33 @@ class Posterize:
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]
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print(cmd)
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subprocess.call(cmd, cwd = self.stipple_gen)
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self.previews.append(output_image)
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self.svgs.append(output_svg)
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self.previews.append({
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'layer' : output_image,
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'color' : layer['color']
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})
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def preview (self) :
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#composite = create_colored_image(self.w, self.h, [255, 255, 255])
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print(self.previews)
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composite = create_colored_image(self.w, self.h, [255, 255, 255])
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for layer in self.previews :
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l = cv2.imread(layer['layer'], 0)
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mask = cv2.bitwise_not(l)
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composite[mask > 0] = np.array(convert_color(layer['color'], self.pallete_space, 'BGR'))
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composite_name = f'preview.png'
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composite_path = os.path.join(self.output, composite_name)
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cv2.imwrite(composite_path, composite)
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self.show(composite)
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for svg in self.svgs :
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cmd = [ 'svgopt', svg, svg]
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print(cmd)
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subprocess.call(cmd)
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def show (self, mat) :
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if not self.headless :
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cv2.imshow('image', mat)
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cv2.waitKey(0)
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cv2.destroyAllWindows()
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@ -9,6 +9,7 @@ parser.add_argument('input', type=str, help='Input image to separate')
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parser.add_argument('colors', type=int, help='Number of colors to separate into')
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parser.add_argument('pallete', type=str, help='Pallete file')
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parser.add_argument('output', type=str, help='Output dir to write to')
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parser.add_argument('--headless', type=bool, default=False, help='Run script headless')
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class Separate :
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input = ''
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@ -28,7 +29,7 @@ class Separate :
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print(f'File {args.pallete} does not exist')
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exit(2)
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Posterize(self.input, self.pallete, args.colors, args.output)
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Posterize(self.input, self.pallete, args.colors, args.output, args.headless)
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if __name__ == "__main__" :
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