SOTA real-time object detection model
Paligemma2 Detection with Supervision
Detect and track cars in a video
YOLOv11n & DeepSeek 1.5B LLM—Running Locally
Identify and track faces in videos
Detect objects in a video stream
Detect cars, trucks, buses, and motorcycles in videos
Identify objects in live video
Detect objects in live video from your webcam
Detect objects in images and videos
Powerful foundation model for zero-shot object tracking
yolo-bdd-inference
Video captioning/tracking
RF-DETR is a state-of-the-art (SOTA) real-time object detection model designed for tracking objects in videos. It enables efficient and accurate annotation of objects in both images and videos, making it a powerful tool for various computer vision applications.
• High-Speed Processing: Optimized for real-time object detection, ensuring fast and accurate results.
• State-of-the-Art Performance: Delivers cutting-edge accuracy in object detection tasks.
• Multi-Format Support: Works seamlessly with both images and videos, providing versatility for different use cases.
• Efficient Tracking: Capable of tracking objects across frames in videos with high precision.
What makes RF-DETR suitable for real-time applications?
RF-DETR is optimized for speed and efficiency, making it ideal for real-time object detection and tracking in videos.
How accurate is RF-DETR compared to other models?
RF-DETR achieves state-of-the-art performance, outperforming many other models in object detection benchmarks.
Can RF-DETR process both images and videos?
Yes, RF-DETR supports both image and video inputs, providing consistent results across different formats.