Detecting Nested Shapes in opencv

Question

The problem with this code is that it even detect a triangle as nested triangle if it is inside another shape like circle, square or rectangular. I can't seem to find a solution to this problem.

Usecases: If the triangle is inside another shape like square, cricle or rectangular it not detect it as nested triangle.

import numpy as np
import cv2

img = cv2.imread('triangles.png', cv2.IMREAD_GRAYSCALE)  # Read input image as grayscale,

# edges = cv2.Canny(img, 50, 200)

# Invert polarity of img, instead of using Canny - we need the contours to be white.
img = 255 - img

contours, hierarchy = cv2.findContours(img, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

hierarchy = hierarchy[0] # get the actual inner list of hierarchy descriptions

img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR) # Convert image to BGR, for using colored text.

for component in zip(contours, hierarchy):
currentContour = component[0]
#currentHierarchy = hierarchy[1] # Why ?
currentHierarchy = component[1]

approx = cv2.approxPolyDP(currentContour, 0.01 * cv2.arcLength(currentContour, True), True)
x = approx.ravel()[0]
y = approx.ravel()[1] - 5

# https://docs.opencv.org/master/d9/d8b/tutorial_py_contours_hierarchy.html
# Hierarchy Representation in OpenCV
# Each contour has its own information regarding what hierarchy it is, who is its child, who is its parent etc. 
# OpenCV represents it as an array of four values : [Next, Previous, First_Child, Parent]

#if (currentHierarchy[1] < 0) and len(approx) == 3:

if (currentHierarchy[2] < 0) and len(approx) == 3:
    # These are the innermost child components

    parent_idx = currentHierarchy[3]  # Get the index of the parent contour
    parent_hier = hierarchy[parent_idx]  # Get the hierarchy of the parent.

    if parent_hier[3] >= 0:
        # Contour is nested only if the parent has a parent.
        cv2.putText(img, "Nested", (x, y), cv2.FONT_HERSHEY_COMPLEX, 0.5, (255, 0, 0), 2)
        cv2.drawContours(img, [currentContour], -1, (0, 255, 0), 1)
        cv2.waitKey(1000)
        cv2.imshow("image", img)

   cv2.waitKey()
   cv2.destroyAllWindows()

Image For Testing:

Answer 1

We have this image:

We want to detect every triangle that is inside a triangle, while not inside any other shape. With the above image, there are two such triangles.

1. Import the necessary libraries:

import cv2
import numpy as np

2. Read the image into a variable, define another variable to store the image converted into gray scale, and with the gray scale image, find the contours and hierarchies of the image:

img = cv2.imread('shapes.png')
img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

contours, hierarchy = cv2.findContours(255 - img_gray, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
hierarchy = hierarchy[0]

3. Define two lists; one to store each triangle that is in a shape, potential_nested , and the other to store every shape that is not a triangle, not_triangles :

potential_nested = list()
not_triangles = list()

4. Loop through the contours and hierarchies of the image in parallel using the built-in zip() method, and find the approximate contour for each contours of the iterations:

for cnt, hry in zip(contours, hierarchy):
    peri = cv2.arcLength(cnt, True)
    approx = cv2.approxPolyDP(cnt, 0.01 * peri, True)

5. Check to see if it's a triangle by checking if the length of the approximate contour is equal to 3. If not, append it to the not_triangles list. If so, check to see if it's in another shape before appending it to the potential_nested list.

    if len(approx) == 3:
        if hry[2] < 0:
            parent_idx = hry[3]
            parent_hier = hierarchy[parent_idx]
            if parent_hier[3] >= 0:
                potential_nested.append(cnt)
    else:
        not_triangles.append(cnt)

6. Now we can loop though every triangle that is in another shape and every shape that's not a triangle, and if none of the points in the triangle are within the non-triangle shapes, we found our nested triangle:

for triangle in potential_nested:
    for cnt in not_triangles:
        if any(cv2.pointPolygonTest(cnt, tuple(p), True) > 0 for p in triangle.squeeze()):
            break
    else:
        cv2.putText(img, "Nested", tuple(triangle[0, 0]), cv2.FONT_HERSHEY_COMPLEX, 0.5, (0, 255, 255), 2)

7. Finally, we can display the image that has text drawn over it:

cv2.imshow("Shapes", img)
cv2.waitKey(0)

Output:

Altogether:

import cv2
import numpy as np

img = cv2.imread('shapes.png')
img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

contours, hierarchy = cv2.findContours(255 - img_gray, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
hierarchy = hierarchy[0]

potential_nested = list()
not_triangles = list()

for cnt, hry in zip(contours, hierarchy):
    peri = cv2.arcLength(cnt, True)
    approx = cv2.approxPolyDP(cnt, 0.01 * peri, True)
    if len(approx) == 3:
        if hry[2] < 0:

            parent_idx = hry[3]
            parent_hier = hierarchy[parent_idx]

            if parent_hier[3] >= 0:
                potential_nested.append(cnt)
    else:
        not_triangles.append(cnt)

for triangle in potential_nested:
    for cnt in not_triangles:
        if any(cv2.pointPolygonTest(cnt, tuple(p), True) > 0 for p in triangle.squeeze()):
            break
    else:
        cv2.putText(img, "Nested", tuple(triangle[0, 0]), cv2.FONT_HERSHEY_COMPLEX, 0.5, (0, 255, 255), 2)

cv2.imshow("Shapes", img)
cv2.waitKey(0)