marker_separation/py/common.py

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import cv2
import numpy as np
from math import sqrt
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
elif color_space_a == 'RGB' and color_space_b == 'RGB' :
b = None
elif color_space_a == 'BGR' and color_space_b == 'BGR' :
b = None
elif color_space_a == 'LAB' and color_space_b == 'LAB' :
b = None
elif color_space_a == 'HSV' and color_space_b == 'HSV' :
b = None
if b is not None :
cvt = cv2.cvtColor(pixel, b)
else :
cvt = pixel
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[0]
# Works for RGB, BGR, LAB and HSV(?)
def closest_color_pythagorean (colors, color) :
mDist = float('inf')
mIdx = -1
for idx, comp in enumerate(colors) :
dist = pythagorean_distance(comp[0], comp[1], comp[2], color[0], color[1], color[2])
if dist < mDist :
mDist = dist
mIds = idx
return color[mIdx], mDist
def closest_color_weighted_pythagorean (colors, color, space) :
mDist = float('inf')
mIdx = -1
for idx, comp in enumerate(colors) :
if space == 'BGR' :
dist = weighed_pythagorean_distance(comp[2], comp[1], comp[0], color[2], color[1], color[1])
elif space == 'RGB' :
dist = weighed_pythagorean_distance(comp[0], comp[1], comp[2], color[0], color[1], color[2])
else :
raise Exception(f'closest_color_weighted_pythagorean does not support color space {space}')
break
if dist < mDist :
mDist = dist
mIds = idx
return color[mIdx], mDist
def create_colored_image (width, height, bgr_color):
image = np.zeros((height, width, 3), np.uint8)
image[:] = bgr_color
return image
def remove_from_list (l, item) :
new_array = []
for i in l :
if not list_match(i, item) :
new_array.append(i)
return new_array
def list_match (a, b) :
for i in range(len(a)) :
if a[i] != b[i] :
return False
return True
def pythagorean_distance (r1, g1, b1, r2, g2, b2) :
return sqrt(pow(r1-r2, 2) + pow(g1-g2, 2) + pow(b1-b2, 2))
def weighted_pythagorean_distance (r1, g1, b1, r2, g2, b2) :
R = 0.30
G = 0.59
B = 0.11
return sqrt(pow((r1-r2) * R, 2) + pow((g1-g2) * G, 2) + pow((b1-b2) * B, 2))