OpenCV (Open Source Computer Vision Library) is written in C/C++, for real time computer vision. It takes advantage of multi-core processing and hardware acceleration. Applications of OpenCV includes egomotion estimation, gesture recognition, facial recognition system, and artificial neural networks.
OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation
The minimal opencv for Android, iOS, ARM Linux, Windows, Linux, MacOS, WebAssembly
(CGCSTCD'2017) An easy, flexible, and accurate plate recognition project for Chinese licenses in unconstrained situations
A High-performance cross-platform Video Processing Python framework powerpacked with unique trailblazing features
Fast face detection, pupil/eyes localization and facial landmark points detection library in pure Go
A C++ Background Subtraction Library with wrappers for Python, MATLAB, Java and GUI on QT
Python scripts performing optical flow estimation using the NeuFlowV2 model in ONNX
ML Nexus is an open-source collection of machine learning projects, covering topics like neural networks, computer vision, and NLP
This project is a face recognition-based attendance system that uses Python, OpenCV, Scikit-learn, Streamlit, and various other libraries like Pandas, Numpy, Datetime, and OS for different functionalities
This repository contains my code and solutions for the Digital Image Processing course at Amirkabir University of Technology, Biomedical Engineering Department
A webcam that visualizes its output as ASCII art directly in the terminal
Personal tasks or codes of Machine Learning and Artificial Intelligence
Installation of OpenCV on JetsonNano with CUDA support
Live Vehicle & Pedestrian tracker using OpenCV, YOLOv8 and ByteTrack
Jarvis is an innovative intelligent assistant tailored to support students in their academic endeavors
Real-time sign language detection using CNN and MediaPipe for hand landmark recognition
Learned how Neural Networks, Multi-Layer Perceptron and Convolutional Neural Networks are used for Image Classification and Segmentation, and trained CNN model on a custom dataset