⚠️ This repository is no longer actively maintained. It previously dealt with Non-Intrusive Load Monitoring (NILM), focusing on predicting household appliance status from aggregated power load data. We explored different thresholding methods and evaluated deep learning models for regression and classification tasks.

A set of algorithms and other cool things that I learned while doing image processing with openCV using C++ and python.

Interactive image viewer and processing application for computer vision research and real-time parameter tuning with OpenCV

opencv for face detection, segmentation, recognition, lane findings,

A project on Image Processing, leveraging PyQt5 for a user-friendly GUI and implementing essential operations like Low Pass Filter, Downsampling, Upsampling, Thresholding, and Negative Image Generation. It offers a visually engaging experience while exploring the realm of image processing techniques.

Two methods for segmenting skin on ultrasound B-mode images

See movement patterns over time using Python and OpenCV

This GitHub repository serves as a valuable resource for researchers, developers, and enthusiasts working with AUVs, providing a range of image processing algorithms and tools tailored to enhance visual perception and analysis in underwater scenarios.

Decision-safe evaluation + Streamlit dashboard for AI vs Human vs Post-Edited AI text detection. Generates a reliability report card (Accuracy, Macro F1, ECE, Brier), calibration plots, confidence histograms, and a coverage-vs-performance abstention curve. Recommends an operating threshold for human-review routing.

Water level detection using draft marker readings, through the means of computer vision, machine learning and optical flow methods

Implementation of various image processing methods from scratch in python.

This application can be used to quickly view how different Thresholding Methods work on images. Selected threshold method can be applied for bulk images in a folder, results are saved in a user selected folder with histograms.

Medical Image processing and segmentation for the automatic detection and counting of blood platelets and WBCs.

(Semi) Automated Image Processing

Complete resource for people wanting to learn Computer Vision with the latest OpenCV4, Dlib and DeepLearning

EdgeVisionCam is a real-time edge detection tool using Python and Pygame. It processes live webcam video to highlight edges and contours, offering a clear view of your environment's features. With an easy-to-use interface and adjustable settings, EdgeVisionCam is ideal for dynamic visual analysis.

Preprocess, noise-reduction, threshold & quantify images to get box plots for each class (mainly cell cultures of different cel llines). Colocalization due to a naive trick of counting all overlapping signals/pixels. Could be done in ImageJ as well, but i thought this is better suited than fiddling with macros.

Threshold an image interactively (HSV,HSL, Sobel X/Y)

Lane finding with computer vision

Image Processing with OpenCv-Computer Vision