Image and video analysis and processing 📷

This repository contains the code for the course Image and video analysis and processing (2023/24) of the Master in Artificial Intelligence at the Wrocław University of Science and Technology 🧑‍🎓. The course primarily focuses on classical computer vision techniques and image processing. The repository is organized into eight labs, each dedicated to a different topic. These labs leverage the OpenCV and Torchvision libraries, as detailed in the Technologies section.

General info

This repository contains the code for the course Image and video analysis and processing (2023/24) of the Master in Artificial Intelligence at the Wrocław University of Science and Technology.

Notebooks:

Basics of openCV:
- Podstawy_OpenCV.ipynb - Basic of openCV.
Binarization, image filtering:
- lab2-zadanie.ipynb - Global thresholding & adaptive thresholding.
Edge detection, histogram equalization & matching:
- zadanie.ipynb - Edge detection, Histogram matching.
Slic superpixels, image segmentation:
- zadanie.ipynb - Slic superpixels, image segmentation.
Pills detection and classification:
- Lab5_zadanie_Hough.ipynb - Overview of parameters Hough lines detection.
- Lab5_zadanie.ipynb - Pills detection and classification.
SIFT and Image Stitching:
- Lab6.1_zadanie.ipynb - Overview of SIFT parameters and their impact on key point detection and matching results.
- Lab6.2_zadanie.ipynb - Overview of SIFT parameters and their impact on key point detection and matching results.
Detection using Faster-RCNN:
- Detection and classification of chess pieces.
- Parameters overview.
Optical Flow: