🔍 Detect anatomical landmarks in chest X-rays using ResNet-18 transfer learning, achieving 8.13 pixels average error for clinical excellence.

Professional & Modular Image Processing Library in Python

PyTorch-based toolkit for landmark localization

Gaze estimation algorithms in C++ using laptop's camera as input and machine learning algorithms for the prediction of gaze's direction.

[ultralytics v8.3.75][yolov8/yolo11-pose][WIDER FACE]Upgrade YOLO5Face to YOLO8Face and YOLO11Face

HandTrackPy is a real time hand tracking which detects and tracks multiple hands, providing key landmarks for gesture recognition and interactive applications.

Real time hand detection and classification with landmark visualization. Works with any webcam for fast and efficient hand tracking.

Medical Landmarks Prediction with Deep Learning: Achieving Clinical Excellence (8.13px precision) using ResNet-18 Transfer Learning for Anatomical Landmark Detection in Chest X-rays

Official PyTorch implementation of the paper: "Self-supervised pre-training with diffusion model for few-shot landmark detection in x-ray images" (WACV 2025)

Landmark detection engine for 3D medical images (MICCAI workshop 2021)

Detects a person’s age range, gender, and facial landmarks in real time via webcam or from uploaded images.

🧍 Human pose estimation using MediaPipe Pose & OpenCV for landmark detection, skeleton tracking, and activity analysis.

Hourglass Networks for Knee Anatomical Landmark Localization: PyTorch Implementation

[ICCV 2025] Official implementation of CABLD

Pose estimation implemented in tensorflow 2.

Automatic head CT alignment using deep learning-based landmark detection and geometric transformations. Standardizes orientation for robust analysis.

Using opencv2 and mediapipe for live detection of Hands and displaying the landmarks along with their FPS

Facial landmark detection is widely used in computer vision for tasks like face alignment, expression tracking, AR filters, and emotion analysis. This project showcases how it can be applied efficiently using MediaPipe and Streamlit.

This Python program uses Mediapipe and OpenCV to detect a smile by measuring the distance between mouth landmarks. When the smile is wide enough, it captures a selfie and plays a sound. It runs in real time via webcam and stops when the Esc key is pressed.

realtime ASL translation via rasp pi + sunglasses + ensemble gesture classification