Determine if a point is inside or outside of a shape with opencv

Question

I have images with white background and simple shapes in them (each image has one shape). I want to determine if a certain point (x,y) is inside the shape or not. How can I

Answer 1

if you want to access all the points inside the convex hull, you can do masking

I solve this by first painting my convex hull white colour with cv2.fillPoly() on a black frame

1. First create black frame that follows your frame's shape
   black_frame = np.zeros_like(your_frame).astype(np.uint8)
2. Paint the convex hull with white
   cv2.fillPoly(black_frame , [hull], (255, 255, 255))
3. Create a mask by using numpy boolean indexing, it will produce a mask with True/False values inside, it will be True is the pixel value is white
   mask = black_frame == 255
4. You can access your pixel values by getting the product between your frame and mask, if False, value will
   targetROI = your_frame * mask
5. Access your pixels by using the mask.

black_frame = np.zeros_like(your_frame).astype(np.uint8)
cv2.fillPoly(black_frame , [hull], (255, 255, 255))
mask = black_frame == 255
targetROI = your_frame * mask

Answer 2

To determine if a point is inside, outside, or on the edge of a shape you can check if the point is within a contour using cv2.pointPolygonTest(). The function returns +1, -1, or 0 to indicate if a point is inside, outside, or on the contour, respectively. Assuming we already have the contour of the shape, we can simply pass the contour and the (x,y) point to the function.

result = cv2.pointPolygonTest(contour, (x,y), False) 

In the function, the third argument is measureDist. If it is True, it finds the shortest distance between a point in the image and a contour. If False, it finds whether the point is inside, outside, or on the contour. Since we don't want to find the distance, we set the measureDist argument to False

Here's an example that finds the square contour then checks if the points are within the contour

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Test image

Image after finding contour and checking points

Results

point1: -1.0

point2: 1.0

point3: 0.0

Therefore point1 is outside, point2 is inside, and point3 is on the contour

import cv2

image = cv2.imread('1.png')
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
canny = cv2.Canny(gray, 120, 255, 1)
cnts = cv2.findContours(canny, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]

point1 = (25, 50)
point2 = (200, 250)
point3 = (200, 350)

# Perform check if point is inside contour/shape
for c in cnts:
    cv2.drawContours(image, [c], -1, (36, 255, 12), 2)
    result1 = cv2.pointPolygonTest(c, point1, False)
    result2 = cv2.pointPolygonTest(c, point2, False)
    result3 = cv2.pointPolygonTest(c, point3, False)

# Draw points
cv2.circle(image, point1, 8, (100, 100, 255), -1)
cv2.putText(image, 'point1', (point1[0] -10, point1[1] -20), cv2.FONT_HERSHEY_SIMPLEX, 1.0, (0, 0, 0), lineType=cv2.LINE_AA)
cv2.circle(image, point2, 8, (200, 100, 55), -1)
cv2.putText(image, 'point2', (point2[0] -10, point2[1] -20), cv2.FONT_HERSHEY_SIMPLEX, 1.0, (0, 0, 0), lineType=cv2.LINE_AA)
cv2.circle(image, point3, 8, (150, 50, 155), -1)
cv2.putText(image, 'point3', (point3[0] -10, point3[1] -20), cv2.FONT_HERSHEY_SIMPLEX, 1.0, (0, 0, 0), lineType=cv2.LINE_AA)

print('point1:', result1)
print('point2:', result2)
print('point3:', result3)
cv2.imshow('image', image)
cv2.waitKey()

Answer 3

Use pointPolygonTest function. Here's tutorial.