Upload README.md

README.md

@@ -62,3 +62,49 @@ train_results = model.train(
 
 ## Test data
 If you do not have test images, I placed 4 test images from the khan dataset to be used during your testing phase.
+Test the model [here](https://huggingface.co/spaces/UEmmanuel5/profsam-fire-demo)
+
+
+## ⚖️ License
+
+* **Model weights** (`Fire_best.pt`): **AGPL-3.0** (Ultralytics-trained).
+* **Space code** (this repo): **Apache-2.0**.
+
+---
+
+## 🙏 Acknowledgements
+
+* Ultralytics YOLO11
+* SAM / SAM2 ecosystem and community
+
+---
+
+## 📚 Citation
+
+If this demo or the model is useful in your research, please cite:
+
+**Manuscript**
+
+```bibtex
+@inproceedings{profsam2025,
+  author    = {Emmanuel U. Ugwu and Xinming Zhang},
+  title     = {Promptable Fire Segmentation: Unleashing SAM2's Potential for Real-Time Mobile Deployment with Strategic Bounding Box Guidance},
+  booktitle = {ICIGP '26},
+  year      = {2026},
+  address   = {Wuhan, China},
+  month     = jan,
+  note      = {to appear}
+}
+```
+
+**Model/Code**
+
+```bibtex
+@software{profsam2025,
+  author    = {Ugwu, Emmanuel U. and Zhang, Xinming},
+  title     = {Promptable Fire Segmentation: Unleashing SAM2’s Potential for Real-Time Mobile Deployment with Strategic Bounding Box Guidance},
+  year      = {2025},
+  doi       = {10.5281/zenodo.17340313},
+  url       = {https://doi.org/10.5281/zenodo.17340313}
+}
+```