import cv2
import numpy as np
from pallete_schema import PalleteSchema
from common import convert_color, closest_color, create_colored_image, remove_from_list

class ComparisonComparison:
	def __init__ (self) :
		
		red = [0, 10, 200]
		green = [5, 250, 5]
		blue = [240, 0, 20]
		
		comp_colors = [red, green, blue]

		pallete = PalleteSchema('./palletes/printed_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('image', show)
		cv2.waitKey(0)	
		
		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)
				print(cccompare)
				closest = closest_color(colors, cccompare)
				print(closest)
				colors = remove_from_list(colors, closest)

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

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

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

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

			show = np.vstack(show)
			cv2.imshow('image', show)
			cv2.waitKey(0)

	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()