Fire and non-fire forest dataset

# Dataset Description: Forest Fire Image Dataset (Generated with Stable Diffusion 2.1)

This dataset was created using the Stable Diffusion 2.1 model to support research in automated forest fire detection. It contains synthetically generated images across two distinct classes:

* Fire
* Non-Fire

#Dataset Composition

Total Classes: 2 (Fire, Non-Fire)
Images per Class: 1000
Total Images: 2,000
Image Resolutions:

768 × 768 pixels
Image Format: All images are in PNG format

#Class Details

Fire Class:
Includes a wide variety of forest fire scenarios, primarily focused on surface-level forest fires. Images depict fires from multiple angles and viewpoints, such as:

* Ground-level perspectives
* Aerial (sky-to-surface) views
* Close-ups and panoramic scenes
This diversity ensures robust representation of real-world fire conditions.

Non-Fire Class:
Comprises natural forest and landscape scenes without any signs of fire, providing essential contrast for binary classification or detection tasks.

#Purpose

This dataset is intended for use in:

* Forest fire detection using computer vision and AI
* Training and evaluating deep learning models
* Exploring the effectiveness of synthetic data in hazard monitoring tasks