OpenMMLab Pose Estimation Toolbox and Benchmark.
RTMPose series (RTMPose, DWPose, RTMO, RTMW) without mmcv, mmpose, mmdet etc.
Compute 2D human pose and angles from a video or a webcam.
A fully automated, markerless extrinsic camera calibration pipeline using human motion. Features RTMPose or Metrabs, 3D lifting, and real-world metric scaling.
juxtapose: Multi-Person Pose Tracking Inference SDK with RTMDet, YOLOv8, GDino, RTMPose (ONNX) & Trackers (ByteTrack & BotSORT) & Tapnet with custom ROIs + FastAPI GPU exe
Markerless motion capture with GoPro
Tennis broadcast analysis pipeline: F3ED shot detection + scoreboard OCR + score-delta reconciler that recovers events the model has no class for (aces, double-faults, first-serve faults). Two-phase Colab→local.
C++ library and set of command-line tools for batched keypoint inference on synchronized image and video inputs
Two-stage skeleton-based action recognition: YOLOv8 + RTMPose + ST-GCN, C++ on NVIDIA DeepStream / TensorRT
Browser-only AI library for real-time object detection (YOLOv8n / YOLOv12n / YOLOv26n, MediaPipe EfficientDet-Lite0) and 3D pose estimation (RTMW3D-X COCO-WholeBody 133-keypoint 3D, InstantHMR MHR70 mesh) on ONNX Runtime Web — wasm, WebGL, WebGPU, WebNN.
AI pull-up detection & technique scoring from video — RTMPose pose estimation, rep counting and GTO-standard violation detection. FastAPI CV engine + Flask web platform.
Real-time 3D Hand & Body Pose Estimation with NVIDIA FoundationStereo & RTMPose for Dual-Eye Intelligence Perception (DIP)
Real-time home training posture feedback system using pose estimation and TCN-based exercise quality classification.
High-Precision Human Velocity Analysis Framework
Desktop tennis-swing auto-segmentation. Vendored MediaPipe + RTMDet + RTMPose cutting pipeline wrapped as a Python FastAPI backend with a pluggable Electron/CLI/Web UI.
from a gait video to recognition emotion
Track Analyzer is the first mobile app providing high-level motion analysis for athletics balancing accuracy, speed, accessibility and portability. By using pose estimation AI models, the system provides immediate and accurate feedback on technical gestures without expensive hardware.
Experiment: real-time human pose estimation desktop app built with Tauri v2 + WebAssembly (RTMPose/ONNX). Compared with a Flutter implementation.
On-device real-time pose estimation with RTMPose + ONNX Runtime. Flutter Web & desktop. Live demo on GitHub Pages.
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