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.
History
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.