ComputerVision

A collection of computer-graphics and computer-vision labs in Python, progressing from raster primitives and 3D projections to OpenCV image processing and YOLO object detection. Real-time rendering is done with OpenGL/GLUT through the shared graphics module; image work uses OpenCV, NumPy and Matplotlib.

Labs

Lab	Topic
1-lab	Calculation strategies — scalar vs. sequential/composed matrix pipelines
2-lab	Spatial transforms — axonometric projection, custom rotation, layered drawing
3-lab	Raster algorithms — Bresenham lines, vertical intersection, contour extraction
4-lab	Vector graphics — least-squares fitting, painter's algorithm, orthogonal projection
5-lab	Fractals — Sierpinski carpet and a recursive fractal tree
6-lab	OpenGL/GLUT — interactive 3D bearing model
7-lab	OpenCV — image transforms and histograms
8-lab	Image segmentation — Otsu thresholding, k-means, Roberts cross
9-lab	Object detection — YOLOv3 on highway-traffic video (OpenCV DNN)
control-task	3D face model with plane-normal back-face culling

Stack

• Python with NumPy and math for the geometry
• PyOpenGL (GLUT) for real-time rendering via the local graphics module
• OpenCV (cv2) and Matplotlib for image processing and visualization

Run

Each lab is self-contained — run its main.py from inside the lab directory:

cd 8-lab
python main.py

Dependencies: pip install numpy opencv-python matplotlib PyOpenGL PyOpenGL_accelerate. Lab 9 additionally needs the YOLOv3 weights/config placed under 9-lab/model/.