This repository contains a collection of weekly assignments completed as part of the Computer Vision course at Poznan University of Technology during the winter semester of 2024/25.
The course involved both theoretical and practical aspects of computer vision, including topics like image filtering, segmentation, inpainting, and object detection. Each lab focuses on a specific task, implemented primarily in Python using libraries such as OpenCV and NumPy.
Each lab is available in two formats:
.ipynb– Jupyter notebook (editable, runnable).html– Static version for quick preview
Here’s what each lab covers:
| Lab | Topic | Description |
|---|---|---|
| Lab 1 | 🚀 Introduction | NumPy and Game of Life. |
| Lab 2 | 🖼️ Image processing | Introduction to image processing, colour spaces, image arithmetics, geometric transfromations. |
| Lab 3 | 🔍 Convolution | Convolutional operations and graphic interpretations, use of convolution in image processing and in mathemathics. |
| Lab 4 | ☯ Morphology | Binary and grayscale morphology, morphological operations as a tool to segmentation. |
| Lab 5 | 🌐 Frequency domain | Frequency domain image, image analysis in frequency domain, high-pass and low-pass filtering. |
| Lab 6 | 🧠 Descriptors | Description of pixels based on known image processing methods, matching key points of multiple images. |
| Lab 7 | ✂️ Image segmentation | Thresholding, cluster analysis, detecting image features (e.g. edges), region growing. |
| Lab 8 | 🎥 Video | Film processing techniques. |
🚛 Moving objects detection in DAS recordings
🧩 Game events detection using traditional CV techniques
🫛 Image inpainting