img = cv2.imread('example.jpg')

img_hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)

# lower mask (0-10)

lower_red = np.array([0, 50, 50])

upper_red = np.array([10, 255, 255]

mask0 = cv2.inRange(img_hsv, lower_red, upper_red)

# upper mask (170-180)

lower_red = np.array([170, 50, 50])

upper_red = np.array([180, 255, 255])

mask1 = cv2.inRange(img_hsv, lower_red, upper_red)

# join my masks

mask = mask0 + mask1

height = mask.shape[0]

width = mask.shape[1]

# iterate over every pixel

for i in range(height):

for j in range(width):

px = mask[i,j]

print px

# check if pixel is white or black

if (px[2] >= 0 and px[2] <= 40):

在上面的例子中,’px’是BGR中的一个像素.我需要将值转换为HSV,因为我想检查像素是否在某个颜色范围内.

我已经试过了

colorsys.rgb_to_hsv(px[2], px[1], px[0})

这会引起错误：标量变量的索引无效

谢谢！

最佳答案 从

docs：

# Convert BGR to HSV

hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)

# define range of blue color in HSV

lower_blue = np.array([110,50,50])

upper_blue = np.array([130,255,255])

# Threshold the HSV image to get only blue colors

mask = cv2.inRange(hsv, lower_blue, upper_blue)

您可以使用内置方法将整个img转换为hsv：

hsv_img = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)