import cv2
import numpy as np


# BGR -> HSV
def BGR2HSV(_img):
	img = _img.copy() / 255.

	hsv = np.zeros_like(img, dtype=np.float32)

	# get max and min
	max_v = np.max(img, axis=2).copy()
	min_v = np.min(img, axis=2).copy()
	min_arg = np.argmin(img, axis=2)

	# H
	hsv[..., 0][np.where(max_v == min_v)]= 0
	## if min == B
	ind = np.where(min_arg == 0)
	hsv[..., 0][ind] = 60 * (img[..., 1][ind] - img[..., 2][ind]) / (max_v[ind] - min_v[ind]) + 60
	## if min == R
	ind = np.where(min_arg == 2)
	hsv[..., 0][ind] = 60 * (img[..., 0][ind] - img[..., 1][ind]) / (max_v[ind] - min_v[ind]) + 180
	## if min == G
	ind = np.where(min_arg == 1)
	hsv[..., 0][ind] = 60 * (img[..., 2][ind] - img[..., 0][ind]) / (max_v[ind] - min_v[ind]) + 300
		
	# S
	hsv[..., 1] = max_v.copy() - min_v.copy()

	# V
	hsv[..., 2] = max_v.copy()
	
	return hsv


def HSV2BGR(_img, hsv):
	img = _img.copy() / 255.

	# get max and min
	max_v = np.max(img, axis=2).copy()
	min_v = np.min(img, axis=2).copy()

	out = np.zeros_like(img)

	H = hsv[..., 0]
	S = hsv[..., 1]
	V = hsv[..., 2]

	C = S
	H_ = H / 60.
	X = C * (1 - np.abs( H_ % 2 - 1))
	Z = np.zeros_like(H)

	vals = [[Z,X,C], [Z,C,X], [X,C,Z], [C,X,Z], [C,Z,X], [X,Z,C]]

	for i in range(6):
		ind = np.where((i <= H_) & (H_ < (i+1)))
		out[..., 0][ind] = (V - C)[ind] + vals[i][0][ind]
		out[..., 1][ind] = (V - C)[ind] + vals[i][1][ind]
		out[..., 2][ind] = (V - C)[ind] + vals[i][2][ind]

	out[np.where(max_v == min_v)] = 0
	out = np.clip(out, 0, 1)
	out = (out * 255).astype(np.uint8)

	return out


# Read image
img = cv2.imread("imori.jpg").astype(np.float32)

# RGB > HSV
hsv = BGR2HSV(img)

# Transpose Hue
hsv[..., 0] = (hsv[..., 0] + 180) % 360

# HSV > RGB
out = HSV2BGR(img, hsv)

# Save result
cv2.imwrite("out.jpg", out)
cv2.imshow("result", out)
cv2.waitKey(0)
cv2.destroyAllWindows()
	out = np.clip(out, 0, 1)
	out = (out * 255).astype(np.uint8)

	return out


# Read image
img = cv2.imread("imori.jpg").astype(np.float32)

# RGB > HSV
hsv = BGR2HSV(img)

# Transpose Hue
hsv[..., 0] = (hsv[..., 0] + 180) % 360

# HSV > RGB
out = HSV2BGR(img, hsv)

# Save result
cv2.imwrite("out.jpg", out)
cv2.imshow("result", out)
cv2.waitKey(0)
cv2.destroyAllWindows()
pythonを用いて、HSV変換を実装して、色相Hを反転せよ。

HSV変換とは、Hue(色相)、Saturation(彩度)、Value(明度) で色を表現する手法である。