Synthetic Image fire and non-fire dataset

This dataset consists of 1,000 AI-generated images, created using a Stable Diffusion model. The images are organized into two distinct folders: Fire: Contains 500 images depicting synthetic representations of forest fires. Non-Fire: Contains 500 images showing various forest scenes without any fire activity. Each image has a resolution of 260x260 pixels, optimized for use in machine learning tasks such as classification, detection, and environmental monitoring. Purpose The dataset is intended to aid research and development in areas such as: Forest fire detection and prevention using AI. Benchmarking deep learning models for image classification tasks. Studying the environmental impact of forest fires.本数据集包含1000张由Stable Diffusion模型生成的人工智能（Artificial Intelligence）图像。该数据集被划分为两个独立文件夹： 火灾（Fire）类：内含500张森林火灾的合成表征图像； 非火灾（Non-Fire）类：内含500张无任何火情的各类森林场景图像。 每张图像分辨率均为260×260像素，适配分类、检测与环境监测等机器学习任务需求。 本数据集旨在助力以下领域的研究与开发工作： 1. 基于人工智能的森林火灾检测与防控研究； 2. 面向图像分类任务的深度学习模型性能基准测试； 3. 森林火灾环境影响相关研究。

搜集汇总

背景与挑战

背景概述

该数据集包含1,000张由Stable Diffusion模型生成的合成图像，分为500张森林火灾图像和500张无火灾森林场景，每张图像分辨率为260x260像素。它专为机器学习任务设计，旨在支持森林火灾检测、AI模型基准测试和环境监测研究。