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I will develop MMA,boxing ai pose tracking punch detection system in opencv yolo python
I build advanced sports analytics systems using YOLOv8, DeepSORT, MediaPipe, OpenCV, and PyTorch to deliver accurate, scalable insights across multiple sports—including football, basketball, volleybal...
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Hello,
We build a real time Python system that detects fighters, tracks poses, and identifies punch events (jab, cross, hook, uppercut) using YOLO for detection, pose estimation for keypoints, and OpenCV for processing and visualization
You'll get
- Real-time fighter detection using YOLO models
- Pose estimation for human body tracking (MediaPipe or OpenPose) to extract keypoints
- Multi-object tracking with consistent IDs (DeepSORT / ByteTrack)
- Punch detection (jab/cross/hook/uppercut) using keypoint dynamics + ML or rule-based classifiers
- Strike counting and accuracy analysis
- Metrics: punch count, speed/velocity estimate, impact timestamps, combos detection
- Annotated output video with overlays (skeletons, labels, trajectories)
- Timestamps, fighter ID, punch type, confidence
- Strike counting and accuracy analysis
- Motion tracking of arms, legs, and torso
- Fight movement analytics and performance metrics
- Multi-person tracking in sparring or matches
- Video analysis for recorded fights or live streams
- Frame-by-frame action recognition
- Custom alerts for punches or significant movements
Contact me now to get started!
Meine weiteren Dienstleistungen im Bereich Datenwissenschaft & ML
FAQ
Deliverables
Working Python codebase (detection, pose, tracking, punch classifier) Annotated demo video(s) and sample outputs (CSV/JSON) PC/Web/Mobile Apps
Use Cases:
Boxing and MMA training analysis Athlete performance tracking Sports science and biomechanics research Coaching and technique improvement tools Fight breakdown and analytics platforms Smart gym and training applications AI-based refereeing assistance systems
Why choose this gig?
Custom-built AI for combat sports analysis Real-time detection and tracking capabilities Accurate pose estimation and motion analysis Scalable for both training and live video systems Clean, well-documented, production-ready code Continuous support and optimization options
Technologies I use:
Python OpenCV YOLO (v5/v8) for object detection MediaPipe / OpenPose (pose estimation) Deep learning models for action recognition NumPy / SciPy for motion analysis TensorFlow / PyTorch (optional custom training)
