# 加载图片 读取彩色图像归一化且转换为浮点型
image = cv2.imread('./imgs/2.jpg', cv2.IMREAD_COLOR).astype(np.float32) / 255.0
# 颜色空间转换 BGR转为HLS
hlsImg = cv2.cvtColor(image, cv2.COLOR_BGR2HLS)
# 滑动条最大值
MAX_VALUE = 10
MAX_VALUE2 = 100
# 滑动条最小值
MIN_VALUE = 0
# 调节饱和度和亮度的窗口
cv2.namedWindow("lightness and saturation", cv2.WINDOW_GUI_NORMAL)
# 创建滑动块
cv2.createTrackbar("lightness", "lightness and saturation",
MIN_VALUE, MAX_VALUE, lambda x:x)
cv2.createTrackbar("saturation", "lightness and saturation",
MIN_VALUE, MAX_VALUE2, lambda x:x)
# 调整饱和度和亮度
while True:
# 复制原图
hlsCopy = np.copy(hlsImg)
# 得到 lightness 和 saturation 的值
lightness = cv2.getTrackbarPos('lightness', 'lightness and saturation')
saturation = cv2.getTrackbarPos('saturation', 'lightness and saturation')
# 调整亮度
hlsCopy[:, :, 1] = (1.0 + lightness / float(MAX_VALUE)) * hlsCopy[:, :, 1]
hlsCopy[:, :, 1][hlsCopy[:, :, 1] > 1] = 1
# 饱和度
hlsCopy[:, :, 2] = (1.0 + saturation / float(MAX_VALUE2)) * hlsCopy[:, :, 2]
hlsCopy[:, :, 2][hlsCopy[:, :, 2] > 1] = 1
# HLS2BGR
lsImg = cv2.cvtColor(hlsCopy, cv2.COLOR_HLS2BGR)
# 显示调整后的效果
cv2.imshow("lightness and saturation", lsImg)
ch = cv2.waitKey(5)
# 按 ESC 键退出
if ch == 27:
break
elif ch == ord('s'):
# 按 s 键保存并退出
lsImg = lsImg * 255
lsImg = lsImg.astype(np.uint8)
cv2.imwrite("./output/lsImg.jpg", lsImg)
break
print("lightness(亮度):",int(lightness))
print("saturation(饱和度):",int(saturation))
# 关闭所有的窗口
cv2.destroyAllWindows()
使用方法：
1. 按 “s” 键保存并退出
2. 按esc键，不保存，直接退出
lightness(亮度): 0
saturation(饱和度): 32
