py/common.py

@@ -1,53 +0,0 @@
-import cv2
-import numpy as np
-
-def convert_color (color, color_space_a, color_space_b) :
-	pixel = np.zeros([1, 1, 3], dtype=np.uint8)
-	if color_space_a == 'RGB' :
-		pixel = cv2.cvtColor(pixel, cv2.COLOR_BGR2RGB)
-	elif color_space_a == 'LAB' :
-		pixel = cv2.cvtColor(pixel, cv2.COLOR_BGR2LAB)
-	elif color_space_a == 'HSV' :
-		pixel = cv2.cvtColor(pixel, cv2.COLOR_BGR2HSV)
-	#default is BGR
-	pixel[:] = color
-	if color_space_a == 'RGB' and color_space_b == 'BGR' :
-		b = cv2.COLOR_RGB2BGR
-	elif color_space_a == 'BGR' and color_space_b == 'RGB' :
-		b = cv2.COLOR_BGR2RGB
-	elif color_space_a == 'RGB' and color_space_b == 'LAB' :
-		b = cv2.COLOR_RGB2LAB
-	elif color_space_a == 'LAB' and color_space_b == 'RGB' :
-		b = cv2.COLOR_LAB2RGB
-	elif color_space_a == 'BGR' and color_space_b == 'LAB' :
-		b = cv2.COLOR_BGR2LAB
-	elif color_space_a == 'LAB' and color_space_b == 'BGR' :
-		b = cv2.COLOR_LAB2BGR
-	elif color_space_a == 'HSV' and color_space_b == 'LAB' :
-		b = cv2.COLOR_HSV2LAB
-	elif color_space_a == 'LAB' and color_space_b == 'HSV' :
-		b = cv2.COLOR_LAB2HSV
-	elif color_space_a == 'RGB' and color_space_b == 'HSV' :
-		b = cv2.COLOR_RGB2HSV
-	elif color_space_a == 'HSV' and color_space_b == 'RGB' :
-		b = cv2.COLOR_HSV2RGB
-	elif color_space_a == 'BGR' and color_space_b == 'HSV' :
-		b = cv2.COLOR_BGR2HSV
-	elif color_space_a == 'HSV' and color_space_b == 'BGR' :
-		b = cv2.COLOR_HSV2BGR
-
-	cvt = cv2.cvtColor(pixel, b)
-	return cvt[0, 0]
-
-def closest_color (colors, color):
-	colors = np.array(colors)
-	color = np.array(color)
-	distances = np.sqrt(np.sum((colors - color) ** 2, axis=1))
-	index_of_smallest = np.where(distances == np.amin(distances))
-	smallest_distance = colors[index_of_smallest]
-	return smallest_distance
-
-def create_colored_image (width, height, bgr_color):
-	image = np.zeros((height, width, 3), np.uint8)
-	image[:] = bgr_color
-	return image

py/comparison_comparison.py

@@ -1,32 +1,22 @@
 import cv2
 import numpy as np
 from pallete_schema import PalleteSchema
-from common import convert_color, closest_color, create_colored_image
 
 class ComparisonComparison:
 	def __init__ (self) :
-		red = [0, 10, 200]
+		c = [0, 0, 255]
-		green = [5, 250, 5]
+		print(c)
-		blue = [240, 0, 20]
+		cc = self.convert_color(c, cv2.COLOR_BGR2RGB, cv2.COLOR_RGB2LAB)
-		comp_colors = [red, green, blue]
+		print(cc)
-		pallete = PalleteSchema('./palletes/printed_pallete.json')
+		print(self.convert_color(cc, cv2.COLOR_BGR2LAB, cv2.COLOR_LAB2RGB))
-		colors = self.get_colors(pallete.colors)
-		for cc in comp_colors :
-			ccbgr = convert_color(cc, 'RGB', 'HSV')
-			closest = closest_color(colors, ccbgr)
-			ccbgr = convert_color(cc, 'RGB', 'BGR')
-			#print(f'{convert_color(closest,"BGR","RGB")} for {convert_color(ccbgr,"BGR","RGB")}')
-			original = create_colored_image(100, 100, convert_color(closest, 'HSV', 'BGR'))
-			chosen = create_colored_image(100, 100, ccbgr)
-			combined = np.hstack([original, chosen])
-			cv2.imshow("image", combined)
-			cv2.waitKey(0)
 
-	def get_colors (self, pallete) :
+
-		colors = []
+	def convert_color (self, color, color_space_a, color_space_b) :
-		for color in pallete :
+		pixel = np.zeros([1, 1, 3], dtype=np.uint8)
-			colors.append(convert_color(color['color'], 'BGR', 'HSV'))
+		pixel = cv2.cvtColor(pixel, color_space_a)
-		return colors
+		pixel[:] = color
+		cvt = cv2.cvtColor(pixel, color_space_b)
+		return cvt[0, 0]
 
 if __name__ == "__main__":
 	ComparisonComparison()

py/pallete_schema.py

@@ -21,10 +21,8 @@ class PalleteSchema :
 	def __init__ (self, file = None, obj = None):
 		if file is not None and obj is None:
 			self.parse_file(file)
-		elif file is not None and obj is not None :
-			self.write(file, obj)
 		else :
-			print('Not sure what you\'re trying to do here')
+			self.write(file, obj)
 
 	def parse_file (self, file) :
 		with open(file) as f :

py/posterize.py

@@ -2,7 +2,6 @@ from sklearn.cluster import MiniBatchKMeans
 import numpy as np
 import argparse
 import cv2
-from common import convert_color, closest_color
 
 class Posterize:
 	"""Posterize an image and then find nearest colors to use"""
@@ -57,3 +56,18 @@ class Posterize:
 	def extract_color_mask (self, image, color):
 		mask = cv2.inRange(image, color, color)
 		return cv2.bitwise_not(mask)
+
+	def convert_color (self, color, color_space_a, color_space_b) :
+		pixel = np.zeros([1, 1, 3], dtype=np.uint8)
+		pixel = cv2.cvtColor(pixel, color_space_a)
+		pixel[:] = color
+		cvt = cv2.cvtColor(pixel, color_space_b)
+		return cvt[0, 0]
+
+	def closest(self, colors, color):
+		colors = np.array(colors)
+		color = np.array(color)
+		distances = np.sqrt(np.sum((colors - color) ** 2, axis=1))
+		index_of_smallest = np.where(distances == np.amin(distances))
+		smallest_distance = colors[index_of_smallest]
+		return smallest_distance