Use OpenCV to Construct a Triangle with Centroid Calculation
In the realm of computer vision, drawing shapes and highlighting their important points can be a valuable tool for various applications. Here's a simple Python code that demonstrates how to draw a triangle and mark its centroid using OpenCV and NumPy.
First, let's define the vertices of our triangle:
Next, we calculate the centroid of the triangle by averaging the x-coordinates and y-coordinates of its vertices:
Now, let's create a black image canvas:
With our canvas ready, we can draw the triangle edges using :
To mark the centroid on the image, we use :
Finally, we display the image with the drawn triangle and centroid using :
This code creates a black window of size 400×300 pixels, draws the triangle by connecting the given vertices, calculates and highlights the centroid at the average of the vertices' coordinates, and displays the result.
Real-world uses of this method include computer vision annotations, geometry simulations, and educational tools. To get started, make sure you have OpenCV and NumPy installed using the command "pip install opencv-python numpy".
[1] Note: The given example calculates the centroid of a triangle with vertices (100, 200), (50, 50), (300, 100) as (150, 116).
In the intersection of computer vision and technology, one could leverage mathematical concepts like triangulation to enhance geometric simulations in various applications. To illustrate this, a Python script uses OpenCV and NumPy to calculate the centroid of a triangle and draw it on a canvas, showcasing the power of these technologies in creating educational tools and annotation systems.
