Y

Yolos Tiny

Developed by Xenova
YOLOS-tiny is a lightweight object detection model based on the Transformer architecture, suitable for real-time object detection tasks.
Downloads 1,912
Release Time : 8/26/2023

Model Overview

YOLOS-tiny is a Transformer-based object detection model designed for multi-object detection in images. It is adapted for Transformers.js in ONNX format, making it easy to use on the web.

Model Features

Lightweight Design
The model has a small size, making it suitable for running in resource-limited environments.
Transformer-based
Utilizes the Transformer architecture to provide efficient object detection capabilities.
ONNX Format Support
The model is provided in ONNX format, facilitating deployment and use across multiple platforms.

Model Capabilities

Image Object Detection
Multi-object Recognition
Real-time Detection

Use Cases

Smart Surveillance
Real-time Surveillance Object Detection
Used for real-time object detection in surveillance cameras, identifying people and objects.
Efficiently identifies multiple targets in surveillance footage.
Smart Home
Home Object Recognition
Recognizes common objects in home environments, such as remote controls and pets.
Accurately identifies objects in home environments, enhancing the interaction capabilities of smart home systems.
Featured Recommended AI Models
AIbase
Empowering the Future, Your AI Solution Knowledge Base
Š 2025AIbase