Detect objects in a video stream
Track moving objects in videos or webcam feed
Analyze video for object detection and counting
Product Prototype 1
Detect cars, trucks, buses, and motorcycles in videos
Track and count vehicles in real-time
Process video to detect specified objects
Detect and track parcels in videos
Video captioning/tracking
Detect objects in short videos
Identify objects in images and videos
Detect and track objects in images or videos
Video captioning/open-vocabulary/zero-shot
RT-DETR-Object-Detection is an advanced object detection model designed to track objects in video streams. Based on the DETR (DEtection TRansformer) architecture, this model enables accurate and efficient object detection in real-time video feeds. It leverages transformer-based technology to deliver high-performance detection capabilities, making it suitable for applications requiring precise object tracking and recognition.
• Real-time object detection: Process video streams with low latency for immediate object recognition. • High accuracy: Utilizes state-of-the-art transformer architecture for precise detection. • Video stream optimization: Designed to handle continuous frames efficiently for smooth tracking. • Multi-object tracking support: Detect and track multiple objects simultaneously in a video. • Compatible with various frameworks: Easily integrates with popular deep learning frameworks. • Lightweight and scalable: Optimized for deployment on different devices, from edge devices to cloud servers.
What video formats are supported?
RT-DETR supports common video formats such as MP4, AVI, and MOV. It can also process live camera feeds.
Can this model run on edge devices?
Yes, RT-DETR is optimized for deployment on edge devices with sufficient computational capabilities, ensuring low-latency processing.
How accurate is the object detection?
The model achieves high accuracy, comparable to state-of-the-art detectors, with precise bounding box predictions and class labels.