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张标注图像，用于在多样化真实场景中开展火灾与烟雾实例检测任务。标注采用YOLO格式，包含两类目标的边界框与类别标签：火灾与烟雾。本数据集划分为三部分：80%为训练集，包含10090个火灾实例与9724个烟雾实例；10%为验证集，包含1255个火灾实例与1241个烟雾实例；剩余10%为测试集，包含1255个火灾实例与1241个烟雾实例。本数据集适用于训练与评估火灾与烟雾检测模型，例如YOLOv8、YOLOv9及其他同类基于深度学习的框架，可应用于应急响应、野火监测与智能监控等场景。