ForestFireVLM-7B is a specialized vision-language model fine-tuned from Qwen2.5-VL-7B-Instruct specifically for forest fire detection and analysis tasks. This model is designed to identify and analyze various aspects of forest fires from aerial imagery, including smoke detection, flame visibility, fire characteristics, and potential hazards. The LLaMA-Factory framework was used for fine-tuning this model.

The model can be used with vLLM to create an OpenAI API compatible endpoint:

Evaluations were done with our code available on GitHub, using the ForestFireInsights-Eval dataset.

This model is associated with research currently under peer review with MDPI. Please cite our paper when using this model:

Seidel, L., Gehringer, S., Raczok, T., Ivens, S.-N., Eckardt, B., & Maerz, M. (2025).
Advancing Early Wildfire Detection: Integration of Vision Language Models with Unmanned Aerial Vehicle Remote Sensing for Enhanced Situational Awareness.
Drones, 9(5), 347. https://doi.org/10.3390/drones9050347