Process videos to detect and track objects
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Identify objects in images and videos
Generate annotated video with object detection
ObjectCounter
Track and count objects in videos
YOLOv11n & DeepSeek 1.5B LLM—Running Locally
Identify objects in live video
Automated Insect Detection
Detect and track parcels in videos
Detect objects in real-time video stream
Segment objects in videos with point clicks
Detect objects in images and videos
Yolo7 Object Tracking is an advanced AI tool designed to detect and track objects within video footage. Built on the YOLOv7 (You Only Look Once version 7) model, it enables real-time processing with high accuracy, making it suitable for applications like surveillance, autonomous systems, and sports analytics. The tool combines state-of-the-art detection algorithms with robust tracking capabilities to provide seamless object monitoring across frames.
• Real-Time Processing: Analyzes video streams with low latency, ideal for live applications.
• High Accuracy: Leverages YOLOv7's advanced detection capabilities for precise object recognition.
• Multiple Object Tracking: Simultaneously tracks hundreds of objects in a single video frame.
• Customizable Models: Users can fine-tune models for specific use cases or environments.
• Video Compatibility: Supports various video formats and resolutions, including 4K and beyond.
What video formats does Yolo7 Object Tracking support?
Yolo7 Object Tracking supports MP4, AVI, MOV, and RAW video formats, ensuring compatibility with most common video types.
Can I customize the object detection model?
Yes, Yolo7 Object Tracking allows users to fine-tune models using custom datasets or predefined configurations for specific use cases.
What are the minimum system requirements for running Yolo7 Object Tracking?
The tool requires at least 4GB of RAM, an NVIDIA GPU (or equivalent), and a modern CPU to run efficiently. For optimal performance, an NVIDIA RTX Series GPU is recommended.