marker_separation/py/comparison_comparison.py

import cv2
import numpy as np
from pallete_schema import PalleteSchema
from common import convert_color, closest_color, create_colored_image, remove_from_list, closest_color_euclidean, closest_color_weighted_euclidean, euclidean_distance, weighted_euclidean_distance

class ComparisonComparison:
	def __init__ (self) :
		self.compare_a()
		# self.compare_b()
		
	def compare_b (self) :
		red = [0, 0, 255]
		green = [0, 255, 0]
		blue = [255, 0, 0]
		white = [255, 255, 255]
		black = [0, 0, 0]

		print(euclidean_distance(red[0], red[1], red[2], green[0], green[1], green[2]))

	def compare_a (self) :
		white = [255, 255, 255]
		red = [0, 10, 200]
		green = [5, 250, 5]
		blue = [240, 0, 20]
		black = [0, 0, 0]
		
		comp_colors = [white, red, green, blue, black]

		pallete = PalleteSchema('./palletes/colored_pallete.json')

		i = 0
		row = []
		rows = []
		for color in pallete.colors :
			cell = create_colored_image(60, 40, color['color'])
			row.append(cell)
			i += 1
			if i == 10 :
				i = 0
				rows.append(np.hstack(row))
				row = []
		show = np.vstack(rows)
		cv2.imshow('pallete', show)
		cv2.waitKey(0)
		cv2.destroyAllWindows()
		
		color_spaces = ['RGB', 'BGR', 'LAB', 'HSV']
		for space in color_spaces :
			print(f'Comparing in color space {space}')
			
			colors = self.get_colors(pallete.colors, space)
			show = []

			for cc in comp_colors :
				cccompare = convert_color(cc, 'RGB', space)

				if space == 'RGB' or space == 'BGR' :
					closest, dist = closest_color_weighted_euclidean(colors, cccompare, space)
				else :
					closest, dist = closest_color_euclidean(colors, cccompare)
				
				colors = remove_from_list(colors, closest)

				ccbgr = convert_color(cc, 'RGB', 'BGR')
				chosenbgr = convert_color(closest, space, 'BGR')

				dcheck = euclidean_distance(ccbgr[2], ccbgr[1], ccbgr[0], chosenbgr[2], chosenbgr[1], chosenbgr[0])

				original = create_colored_image(100, 100, ccbgr)
				chosen = create_colored_image(100, 100, chosenbgr)

				print(f'{ccbgr} => {chosenbgr} = {dist}')
				print(f'dcheck = {dcheck}')

				combined = np.hstack([original, chosen])
				show.append(combined)

			show = np.vstack(show)
			cv2.imshow(space, show)
			cv2.waitKey(0)
			cv2.destroyAllWindows()

	def get_colors (self, pallete, space) :
		colors = []
		for color in pallete :
			colors.append(convert_color(color['color'], color['space'], space))
		return colors

if __name__ == "__main__":
	ComparisonComparison()