Yolos-base Open-source Object Detection Model - Efficiently Handle Various Visual Detection Tasks

Yolos Base

Developed by Xenova

YOLOS is an object detection model based on the Transformer architecture, designed for efficient visual task processing.

Downloads 16

Release Time : 8/26/2023

Model Overview

YOLOS-base is a Transformer-based object detection model with a DETR-like architecture, suitable for object detection tasks in images.

Transformer Architecture

Utilizes Transformer architecture for object detection, differing from traditional CNN-based methods.

ONNX Support

Provides ONNX format weights for easy deployment on web platforms.

Efficient Detection

Designed for efficient object detection, balancing accuracy and speed.

Image Object Detection

Multi-class Object Recognition

Bounding Box Prediction

Computer Vision

Smart Surveillance

Used for object detection and tracking in surveillance videos.

Autonomous Driving

Real-time detection of vehicles, pedestrians, and obstacles on the road.

Industrial Applications

Quality Inspection

Defect detection in production line products.

Property	Details
Base Model	hustvl/yolos-base
Library Name	transformers.js

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