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Yolov5s Smoke

Developed by keremberke
A smoke object detection model based on YOLOv5s architecture, specifically designed to identify smoke regions in images.
Downloads 97
Release Time : 1/4/2023

Model Overview

This model is an object detection model based on the YOLOv5s architecture, specifically used for detecting smoke regions in images. Suitable for scenarios such as fire warning and environmental monitoring.

Model Features

High-precision Detection
Achieves an mAP@0.5 accuracy of 0.9945 on the smoke object detection dataset.
Lightweight Architecture
Based on the YOLOv5s architecture, suitable for deployment in resource-constrained environments.
Easy to Use
Provides a simple Python interface, supporting quick integration into existing systems.

Model Capabilities

Smoke detection in images
Real-time object detection
Bounding box prediction

Use Cases

Public Safety
Early Fire Warning
Real-time smoke detection via surveillance cameras to achieve early fire warning.
Helps reduce losses caused by fires.
Environmental Monitoring
Industrial Emission Monitoring
Monitoring emissions from factory chimneys.
Assists environmental regulatory authorities in enforcement.
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