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I'm trying to crop an image to the boundaries of a contour. I've found a code from this answer 

mask = np.zeros_like(image)
cv2.drawContours(mask, [c], -1, 255, -1)
out = np.zeros_like(image)
out[mask == 255] = image[mask == 255]

(y, x) = np.where(mask == 255)
(topy, topx) = (np.min(y), np.min(x))
(bottomy, bottomx) = (np.max(y), np.max(x))
out = out[topy: bottomy + 1, topx:bottomx + 1]

crop_img = image[topy: bottomy + 1, topx:bottomx + 1]
cv2.imshow("croppedd", crop_img)

where c is a contour.

I'm getting error like :

Traceback (most recent call last):
  File "detect_shapes.py", line 66, in <module>
    (y, x) = np.where(mask == 255)
ValueError: too many values to unpack (expected 2)

How can I solve my issue?

  • Python version 3.7
  • OpenCV version 3.4.4

I don't think this is related to my image but, here my image;

enter image description here

Yunus Karakaya
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2 Answers2

4

The answer you are referring to above is loading image in grayscale mode using 

image = cv2.imread('...', 0)

Here, 0 refers to cv2.IMREAD_GRAYSCALE flag. This is important because in this case, the image will have just 1 channel. If you load your image in this way and run your code, it will work fine. I already tested it. In this case, (y, x) = np.where(mask == 255) won't give any error as output of np.where(mask == 255) is a tuple of two numpy array, since mask is a 2d array(check it using mask.shape).

But, if you are loading your image as image = cv2.imread('...') and not doing something like image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) to convert it to grayscale, then in this case, np.where(mask == 255) return a tuple of three numpy array as mask is a 3d array here This is the reason why you are getting above error.

Anubhav Singh
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2

Look at 

np.where(mask == 255)

without the x,y unpacking. My guess it is a 3 element tuple. where produces an array for each dimension of the input array. If mask is 3d (x,y,channel), the where is a (3,) tuple.

hpaulj
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