Finding red color in image using Python & OpenCV

Question

I am trying to extract red color from an image. I have code that applies threshold to leave only values from specified range:

img=cv2.imread('img.bmp') img_hsv=cv2.cvtColor(img, cv2.COLOR_BGR2HSV) lower_red = np.array([0,50,50]) #example value upper_red = np.array([10,255,255]) #example value mask = cv2.inRange(img_hsv, lower_red, upper_red) img_result = cv2.bitwise_and(img, img, mask=mask) 

But, as i checked, red can have Hue value in range, let's say from 0 to 10, as well as in range from 170 to 180. Therefore, i would like to leave values from any of those two ranges. I tried setting threshold from 10 to 170 and using cv2.bitwise_not() function, but then i get all the white color as well. I think the best option would be to create a mask for each range and use them both, so I somehow have to join them together before proceeding.

Is there a way I could join two masks using OpenCV? Or is there some other way I could achieve my goal?

Edit. I came with not much elegant, but working solution:

image_result = np.zeros((image_height,image_width,3),np.uint8)  for i in range(image_height):  #those are set elsewhere     for j in range(image_width): #those are set elsewhere         if img_hsv[i][j][1]>=50 \             and img_hsv[i][j][2]>=50 \             and (img_hsv[i][j][0] <= 10 or img_hsv[i][j][0]>=170):             image_result[i][j]=img_hsv[i][j] 

It pretty much satisfies my needs, and OpenCV's functions probably do pretty much the same, but if there's a better way to do that(using some dedicated function and writing less code) please share it with me. :)

Answer 1

I would just add the masks together, and use np.where to mask the original image.

img=cv2.imread("img.bmp") 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  # set my output img to zero everywhere except my mask output_img = img.copy() output_img[np.where(mask==0)] = 0  # or your HSV image, which I *believe* is what you want output_hsv = img_hsv.copy() output_hsv[np.where(mask==0)] = 0 

This should be much faster and much more readable than looping through each pixel of your image.