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Draw a triangle with centroid using OpenCV

Last Updated : 14 Aug, 2025

OpenCV is not just for image processing it can also be used for creating and manipulating geometric shapes. we’ll take three vertices of a triangle, draw triangle on a black window, calculate its centroid and mark it visually.

Given three vertices of a triangle, find its centroid using formula:

(X, Y) = \left( \frac{x_1 + x_2 + x_3}{3},\ \frac{y_1 + y_2 + y_3}{3} \right)

Then, draw the triangle and highlight its centroid using OpenCV.

Refer to this article for Draw geometric shapes on images using OpenCV.

The given vertices form a triangle whose centroid is calculated as average of their x and y coordinates, resulting in (150, 116).

Input: (100, 200), (50, 50), (300, 100)
Output: (150, 116)

• OpenCV : for drawing shapes and displaying images.
• NumPy : for creating a black image canvas.

Install them if needed:

pip install opencv-python numpy

• Create a black window of resolution 400 x 300 with three color channels.
• Draw the triangle by connecting the given vertices with cv2.line().
• Calculate the centroid using the average of all x and y coordinates.
• Draw the centroid as a small green circle using cv2.circle().
• Display the image with cv2.imshow().

This code creates a triangle on a black canvas using OpenCV, calculates its centroid and marks the centroid with a green dot.

import numpy as np
import cv2

# Canvas dimensions
width = 400
height = 300

# Create a black image
img = np.zeros((height, width, 3), np.uint8)

# Vertices of the triangle
p1 = (100, 200)
p2 = (50, 50)
p3 = (300, 100)

# Draw the triangle using cv2.line()
cv2.line(img, p1, p2, (255, 0, 0), 3)  # Blue line
cv2.line(img, p2, p3, (255, 0, 0), 3)
cv2.line(img, p1, p3, (255, 0, 0), 3)

# Calculate centroid
centroid = ( (p1[0] + p2[0] + p3[0]) // 3, (p1[1] + p2[1] + p3[1]) // 3)
print("Centroid:",centroid)

# Draw centroid as a green filled circle
cv2.circle(img, centroid, 4, (0, 255, 0), -1)

# Show the result
cv2.imshow("Triangle with Centroid", img)
cv2.waitKey(0)
cv2.destroyAllWindows()

Output

Centroid: (150, 116)

Explanation:

• np.zeros((height, width, 3), np.uint8): Creates a black image of given size.
• p1, p2, p3: Defines the three vertices of the triangle.
• cv2.line(img, p1, p2, (255, 0, 0), 3): Draws a blue line from p1 to p2.
• cv2.line(img, p2, p3, (255, 0, 0), 3): Draws a blue line from p2 to p3.
• cv2.line(img, p1, p3, (255, 0, 0), 3): Draws a blue line from p1 to p3.
• ((p1[0]+p2[0]+p3[0])//3, (p1[1]+p2[1]+p3[1])//3): Calculates centroid coordinates using the average of x and y values.
• cv2.circle(img, centroid, 4, (0, 255, 0), -1): Draws a filled green circle at the centroid.

• Computer Vision Annotations: Marking center points of detected objects.
• Geometry Simulations: Visualizing points, lines and shapes.
• Educational Tools: Teaching geometry with visuals.

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