Middle East Tech University

fire and smoke detection

Object Detection

fire and smoke detection Computer Vision Project

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Explore Dataset

The Fire and Smoke Detection Dataset is a comprehensive collection of images and annotations specifically curated for training object detection models, such as YOLOv8, to recognize and classify instances of fire and smoke in various real-world scenarios. This dataset is designed to empower computer vision applications for early fire detection, safety monitoring, and disaster prevention.

Key Features:

Image Variety: The dataset includes a diverse range of images captured from different sources, encompassing indoor and outdoor environments, different lighting conditions, and various perspectives.

Annotation: Each image in the dataset is meticulously annotated with bounding boxes that precisely delineate the regions containing fire and smoke. This high-quality annotation facilitates accurate model training.

Data Size: The dataset comprises thousands of annotated images, providing a substantial amount of training data to ensure the robustness and generalization of your YOLOv8 model.

Realistic Scenarios: Images include realistic scenarios such as fire outbreaks in buildings, industrial settings, forests, and more. The presence of smoke underlines the potential dangers.

Safety and Security: By utilizing this dataset, you can develop applications that contribute to safety and security by automatically detecting and alerting to fire and smoke incidents.

Use Cases:

Fire and smoke detection systems for buildings and public spaces Early warning systems for forest fires Industrial safety applications Disaster response and monitoring Detection of wildfires Environmental monitoring

License: The Fire and Smoke Detection Dataset is available under MIT License. Data Access: You can access and download the dataset from Roboflow.com, where you will find the images, annotations, and any additional resources needed for training your YOLOv8 model.

Citation: If you use this dataset in your research or projects, please consider citing it as follows:

fire and smoke detection. https://universe.roboflow.com/middle-east-tech-university/fire-and-smoke-detection-hiwia. Roboflow, 2023.

Acknowledgments: We would like to acknowledge the contributors and annotators who made this dataset possible, as well as the Roboflow team for hosting and maintaining it.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Find utilities and guides to help you start using the fire and smoke detection project in your project.

Last Updated

3 months ago

Project Type

Object Detection


fire and smoke


fire, smoke

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