Ndtyjky

I am a bit confused on how I can filter out the contour coordinates (which are in a tuple) and keep only the part of the contour that corresponds to the top segmented layer of this image.

My code is this

img = cv2.imread(image_path)

img = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)

blur = cv2.GaussianBlur(img, (1, 1), 1000)

flag, thresh = cv2.threshold(blur, 120, 255, cv2.THRESH_BINARY)

thresh = cv2.dilate(thresh, None)

thresh = cv2.dilate(thresh, None)

thresh = cv2.erode(thresh, None)

thresh = cv2.erode(thresh, None)

im2, contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

contours = sorted(contours, key=cv2.contourArea, reverse=True)[:1]

perimeters = [cv2.arcLength(contours[i], True) for i in range(len(contours))]

listindex = [i for i in range(1) if perimeters[i] > perimeters[0] / 2]

num_of_layers = len(listindex)

imgcont = img.copy()

[cv2.drawContours(imgcont, [contours[i]], 0, (0, 255, 0), 5) for i in listindex]

M = cv2.moments(contours[0])

cx = int(M['m10'] / M['m00'])

cy = int(M['m01'] / M['m00'])

print(cx, cy)

plt.imshow(imgcont, cmap='gray')