Track and label objects in videos
Detect objects in real-time from webcam video
Analyze video to recognize actions or objects
Detect objects in real-time video streams
Process video to detect specified objects
ObjectCounter
Detect cars, trucks, buses, and motorcycles in videos
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Process videos to detect and track objects
Analyze video for object detection and counting
Detect objects in images or videos
Track and count vehicles in real-time
Product Prototype 1
SAHI YOLOv11 is a state-of-the-art object detection and tracking model designed to track and label objects in video streams with high accuracy and efficiency. Built on the foundation of YOLOv11, it leverages advanced techniques to deliver robust performance for real-time applications. SAHI YOLOv11 is particularly optimized for video object tracking, making it ideal for applications requiring continuous monitoring and analysis.
• High Accuracy: Delivers precise object detection and tracking in video streams.
• Speed Optimized: Designed for real-time performance, making it suitable for live applications.
• Multi-Object Tracking: Capable of tracking multiple objects simultaneously with high reliability.
• Support for Various Frameworks: Compatible with popular AI frameworks for seamless integration.
• Real-Time Processing: Enables immediate analysis and response to video data.
• Automatic Labeling: Assigns meaningful labels to detected objects for better understanding.
• Customizable: Allows users to fine-tune settings for specific use cases.
What is SAHI YOLOv11 used for?
SAHI YOLOv11 is primarily used for tracking and labeling objects in video streams, making it ideal for applications like surveillance, autonomous vehicles, and robotics.
Is SAHI YOLOv11 more accurate than previous YOLO models?
Yes, SAHI YOLOv11 builds on the advancements of YOLOv11 and incorporates additional optimizations for object tracking, resulting in improved accuracy and efficiency.
Do I need a GPU to run SAHI YOLOv11?
While a GPU is recommended for optimal performance, SAHI YOLOv11 can also run on CPU-only systems, though with reduced speed and efficiency.