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

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.

本数据集包含11027张带标注的图像，用于在多元真实场景下开展火灾与烟雾实例检测任务。标注采用YOLO（You Only Look Once）格式，包含火灾与烟雾两类目标的边界框及类别标签。该数据集按80%、10%、10%的比例划分为训练集、验证集与测试集：训练集含10090个火灾实例与9724个烟雾实例，验证集含1255个火灾实例与1241个烟雾实例，测试集含1255个火灾实例与1241个烟雾实例。本数据集可用于训练与评估火灾与烟雾检测模型，例如YOLOv8、YOLOv9及其他基于深度学习的同类框架，适用于应急响应、野火监测与智能监控等应用场景。