OpenCV · 25 Weeks · 9 Phases · Python
Every concept runs in the browser. Write Python, watch the image change, and learn to see the way the algorithm does.
LLMs can describe a photo in words, but the answers can be vague or inconsistent. OpenCV gives you exact numbers from the pixels: locations, counts, and timing, and the same code produces the same result every run.
No environment setup. No downloading datasets. Every lesson is bite-sized and interactive, so you can make real progress in short bursts and always know what to expect from your output.
What you will learn
Each phase builds on the last. Start anywhere, or begin with Phase 0 if you are new to OpenCV.
Get oriented with images as data and learn how the lab works.
Pixels, color spaces, thresholding, and morphological operations.
Gradients, edges, contours, and local feature descriptors.
Frame-by-frame processing, optical flow, and background subtraction.
Object detection, face recognition, and keypoint matching.
Camera models, homography, and stereo geometry.
Text recognition and end-to-end OpenCV pipelines.
Profiling, optimization, and engineering performance trade-offs.
Real-world capstone projects combining all prior phases.