[FIXED] How to use loop in thresholding operation in OpenCV

Issue

I would like to apply a thresholding operation to several grayscale images with different threshold values so that the output, which is displayed as a matplotlib plot, will be 15 or so different images with levels of threshold applied to each. The problem I am facing is that it only displays one image after it runs but if I say print(dst.shape) in the loop it will print 15 image shapes.

I have tried putting the output dst in a list so that I could access them by index dst[2] but this returned an error.

maxValue = 255
dst = []
for thresh in range(0, 255, 51):
    for img in imageB, imageG, imageR:
        th, dst = cv2.threshold(img, thresh, maxValue, cv2.THRESH_BINARY)
        #print(dst.shape)
        #print(len(dst))
        plt.imshow(dst)

What I am trying to achieve is 15 different images from the loop. Is this a matplotlib issue? Am I required to create a figure of a specific size then access each variable in the dst list? If so, why when I print(len(dst)) does it only return the length of the rows in the image?

Solution

You could use a figure with sub-plots, something like this:

fig = plt.figure()

step = 51
maxValue = 255
nrows = 3
ncols = maxValue // step

i = 1
for thresh in range(0, maxValue, step):
    for img in imageB, imageG, imageR:
        th, dst = cv2.threshold(img, thresh, maxValue, cv2.THRESH_BINARY)
        fig.add_subplot(nrows, ncols, i)
        plt.imshow(dst)
        i = i + 1

About your question why when I print(len(dst)) does it only return the length of the rows in the image?, see for example this question.

Answered By - dms