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Annotated Fire -Smoke Image Dataset for fire detection Using YOLO.

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posted on 2025-04-14, 01:13 authored by Shouthiri PartheepanShouthiri Partheepan
This dataset contains 11027 labeled images for the detection of fire and smoke instances in diverse real-world scenarios. The annotations are provided in YOLO format with bounding boxes and class labels for two classes: fire and smoke. The dataset is divided into an 80% training set with 10,090 fire instances and 9724 smoke instances, a 10% Validation set with 1,255 fire and 1,241 smoke instances, and a 10% Test set with 1,255 fire and 1,241 smoke instances. This dataset is suitable for training and evaluating fire and smoke detection models, such as YOLOv8, YOLOv9, and similar deep learning-based frameworks in the context of emergency response, wildfire monitoring, and smart surveillance.

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Open Access

  • Yes

Medium

The dataset consists of the following file formats: Image files: .jpg, .png Annotation files: .txt

Number and size of Dataset

The dataset includes 22,045 files, including image files, YOLO annotation .txt files, and supporting scripts and metadata. It occupies approximately 514 MB.

Supervisor

Farzad Sanati, Jahan Hassan

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