# 加载图片 读取彩色图像
image = cv2.imread('./Files_image/img1.jpg', cv2.IMREAD_COLOR)
# print(image)
# cv2.imshow("image", image)
# 图像归一化，且转换为浮点型
fImg = image.astype(np.float32)
fImg = fImg / 255.0
# 颜色空间转换 BGR转为HLS
hlsImg = cv2.cvtColor(fImg, cv2.COLOR_BGR2HLS)
l = 100
s = 100
MAX_VALUE = 100
# 调节饱和度和亮度的窗口
cv2.namedWindow("l and s", cv2.WINDOW_AUTOSIZE)
def nothing(*arg):
# 滑动块
cv2.createTrackbar("l", "l and s", l, MAX_VALUE, nothing)
cv2.createTrackbar("s", "l and s", s, MAX_VALUE, nothing)
# 调整饱和度和亮度后的效果
lsImg = np.zeros(image.shape, np.float32)
# 调整饱和度和亮度
while True:
hlsCopy = np.copy(hlsImg)
# 得到 l 和 s 的值
l = cv2.getTrackbarPos('l', 'l and s')
s = cv2.getTrackbarPos('s', 'l and s')
# 1.调整亮度（线性变换) , 2.将hlsCopy[:, :, 1]和hlsCopy[:, :, 2]中大于1的全部截取
hlsCopy[:, :, 1] = (1.0 + l / float(MAX_VALUE)) * hlsCopy[:, :, 1]
hlsCopy[:, :, 1][hlsCopy[:, :, 1] > 1] = 1
# 饱和度
hlsCopy[:, :, 2] = (1.0 + s / float(MAX_VALUE)) * 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("l and s", 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
# 保存结果
lsImg = lsImg * 255
lsImg = lsImg.astype(np.uint8)
cv2.imwrite("lsImg.jpg", lsImg)
break
# 关闭所有的窗口
cv2.destroyAllWindows()
if __name__ == "__main__":
main()
