Ultralytics YOLO11 Gradio Application for Testing
Identify the main objects in an image
Identify objects in images using URLs or uploads
Upload images to detect objects
Upload images/videos to detect wildfires and smoke
Detect and measure areas of objects in images
Identify labels in an image with a score threshold
Detect objects in an image
Detect objects in images using drag-and-drop
Identify objects in images
Draw a box to detect objects
Generic YOLO Models Trained on COCO
Identify objects in images
YOLO11 is an advanced object detection application developed by Ultralytics, designed for real-time object detection in images. It leverages the YOLOv11 model, known for its high accuracy and speed, to deliver robust detection capabilities. The application allows users to detect objects in images with customizable confidence thresholds, making it suitable for various use cases.
• Real-Time Detection: Perform object detection on images with minimal latency.
• Customizable Thresholds: Adjust confidence thresholds to filter detection results based on accuracy needs.
• Multi-Device Support: Runs efficiently on CPUs, GPUs, and edge devices.
• User-Friendly Interface: Intuitive interface for seamless interaction and configuration.
• High Accuracy: Built on the state-of-the-art YOLOv11 model for precise object recognition.
What is YOLO11 used for?
YOLO11 is primarily used for object detection in images, enabling users to identify and locate objects within visual data.
How can I improve detection accuracy?
To improve accuracy, adjust the confidence threshold to a higher value, ensure high-quality input images, and use appropriate models optimized for your specific use case.
Where can I find the documentation for YOLO11?
The official documentation and usage guides can be found on the Ultralytics YOLO11 GitHub repository or the associated project website.