119 lines
3.5 KiB
Python
119 lines
3.5 KiB
Python
import cv2
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import numpy as np
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from math import sqrt
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def convert_color (color, color_space_a, color_space_b) :
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pixel = np.zeros([1, 1, 3], dtype=np.uint8)
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if color_space_a == 'RGB' :
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pixel = cv2.cvtColor(pixel, cv2.COLOR_BGR2RGB)
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elif color_space_a == 'LAB' :
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pixel = cv2.cvtColor(pixel, cv2.COLOR_BGR2LAB)
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elif color_space_a == 'HSV' :
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pixel = cv2.cvtColor(pixel, cv2.COLOR_BGR2HSV)
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#default is BGR
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pixel[:] = color
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if color_space_a == 'RGB' and color_space_b == 'BGR' :
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b = cv2.COLOR_RGB2BGR
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elif color_space_a == 'BGR' and color_space_b == 'RGB' :
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b = cv2.COLOR_BGR2RGB
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elif color_space_a == 'RGB' and color_space_b == 'LAB' :
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b = cv2.COLOR_RGB2LAB
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elif color_space_a == 'LAB' and color_space_b == 'RGB' :
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b = cv2.COLOR_LAB2RGB
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elif color_space_a == 'BGR' and color_space_b == 'LAB' :
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b = cv2.COLOR_BGR2LAB
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elif color_space_a == 'LAB' and color_space_b == 'BGR' :
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b = cv2.COLOR_LAB2BGR
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elif color_space_a == 'HSV' and color_space_b == 'LAB' :
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b = cv2.COLOR_HSV2LAB
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elif color_space_a == 'LAB' and color_space_b == 'HSV' :
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b = cv2.COLOR_LAB2HSV
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elif color_space_a == 'RGB' and color_space_b == 'HSV' :
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b = cv2.COLOR_RGB2HSV
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elif color_space_a == 'HSV' and color_space_b == 'RGB' :
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b = cv2.COLOR_HSV2RGB
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elif color_space_a == 'BGR' and color_space_b == 'HSV' :
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b = cv2.COLOR_BGR2HSV
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elif color_space_a == 'HSV' and color_space_b == 'BGR' :
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b = cv2.COLOR_HSV2BGR
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elif color_space_a == 'RGB' and color_space_b == 'RGB' :
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b = None
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elif color_space_a == 'BGR' and color_space_b == 'BGR' :
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b = None
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elif color_space_a == 'LAB' and color_space_b == 'LAB' :
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b = None
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elif color_space_a == 'HSV' and color_space_b == 'HSV' :
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b = None
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if b is not None :
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cvt = cv2.cvtColor(pixel, b)
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else :
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cvt = pixel
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return cvt[0, 0]
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def closest_color (colors, color):
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colors = np.array(colors)
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color = np.array(color)
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distances = np.sqrt(np.sum((colors - color) ** 2, axis=1))
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index_of_smallest = np.where(distances == np.amin(distances))
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smallest_distance = colors[index_of_smallest]
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return smallest_distance[0]
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# Works for RGB, BGR, LAB and HSV(?)
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def closest_color_pythagorean (colors, color) :
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mDist = float('inf')
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mIdx = -1
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for idx, comp in enumerate(colors) :
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dist = pythagorean_distance(comp[0], comp[1], comp[2], color[0], color[1], color[2])
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if dist < mDist :
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mDist = dist
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mIds = idx
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return color[mIdx], mDist
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def closest_color_weighted_pythagorean (colors, color, space) :
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mDist = float('inf')
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mIdx = -1
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for idx, comp in enumerate(colors) :
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if space == 'BGR' :
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dist = weighed_pythagorean_distance(comp[2], comp[1], comp[0], color[2], color[1], color[1])
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elif space == 'RGB' :
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dist = weighed_pythagorean_distance(comp[0], comp[1], comp[2], color[0], color[1], color[2])
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else :
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raise Exception(f'closest_color_weighted_pythagorean does not support color space {space}')
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break
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if dist < mDist :
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mDist = dist
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mIds = idx
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return color[mIdx], mDist
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def create_colored_image (width, height, bgr_color):
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image = np.zeros((height, width, 3), np.uint8)
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image[:] = bgr_color
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return image
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def remove_from_list (l, item) :
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new_array = []
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for i in l :
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if not list_match(i, item) :
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new_array.append(i)
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return new_array
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def list_match (a, b) :
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for i in range(len(a)) :
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if a[i] != b[i] :
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return False
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return True
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def pythagorean_distance (r1, g1, b1, r2, g2, b2) :
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return sqrt(pow(r1-r2, 2) + pow(g1-g2, 2) + pow(b1-b2, 2))
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def weighted_pythagorean_distance (r1, g1, b1, r2, g2, b2) :
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R = 0.30
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G = 0.59
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B = 0.11
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return sqrt(pow((r1-r2) * R, 2) + pow((g1-g2) * G, 2) + pow((b1-b2) * B, 2)) |