Detect objects and track body movements in real-time
Detect objects in live video feeds
A UI for drone detection for YOLO-powered detection system.
Automated Insect Detection
YOLOv11n & DeepSeek 1.5B LLM—Running Locally
Detect cars, trucks, buses, and motorcycles in videos
ObjectCounter
YOLOv11 Model for Aerial Object Detection
Process video to count and track cars
Object_detection_from_Video
Analyze images and videos to identify objects
Segment objects in videos with point clicks
Powerful foundation model for zero-shot object tracking
😊RTMP🤸♂️MediaPipe🕺 is a powerful tool designed for real-time object tracking and body movement detection in video streams. It leverages the capabilities of RTMP (Real-Time Messaging Protocol) for streaming and MediaPipe, Google's open-source framework for machine learning-based media processing. This tool is optimized for high-performance video analysis and offers a seamless experience for users seeking to detect and track objects or movements in live or recorded video feeds.
• Real-Time Tracking: Process video streams in real-time with minimal latency.
• Multi-Object Detection: Detect and track multiple objects or body movements simultaneously.
• MediaPipe Integration: Utilizes Google's MediaPipe framework for accurate and efficient media processing.
• RTMP Streaming Support: Compatible with RTMP for streaming video content.
• Customizable Models: Option to use or train custom models for specific detection tasks.
• User-Friendly Interface: Easy-to-use interface for configuring tracking parameters.
What is RTMP, and why is it used here?
RTMP is a protocol for streaming audio, video, and data over the internet. It is used here for its efficiency in real-time video streaming, enabling low-latency communication between the tool and the video source.
Can this tool be used for live footage?
Yes, 😊RTMP🤸♂️MediaPipe🕺 is specifically designed for real-time processing, making it suitable for live footage analysis.
How accurate is the object tracking?
The accuracy depends on the quality of the input video and the selected detection model. Using high-resolution video and trained models will improve tracking precision.