Add acknoledgements

README.md

@@ -66,9 +66,22 @@ The model implements several key architectural components:
 
 The model has been trained for 20,000 iterations with careful monitoring of PSNR and SSIM metrics on satellite imagery validation data.
 
+## Acknowledgments
+
+This model is a fine tuned version of **HAT (Hybrid Attention Transformer)** and trained on the **SEN2NAIPv2** dataset.
+
+### Base Model: HAT
+- **GitHub Repository**: [https://github.com/XPixelGroup/HAT](https://github.com/XPixelGroup/HAT)
+- **Paper**: [Activating More Pixels in Image Super-Resolution Transformer](https://arxiv.org/abs/2205.04437)
+- **Authors**: Xiangyu Chen, Xintao Wang, Jiantao Zhou, Yu Qiao, Chao Dong
+
+### Training Dataset: SEN2NAIPv2
+- **HuggingFace Dataset**: [https://huggingface.co/datasets/tacofoundation/SEN2NAIPv2](https://huggingface.co/datasets/tacofoundation/SEN2NAIPv2)
+- **Description**: High-resolution satellite imagery dataset for super-resolution tasks
+
 ## Citation
 
-If you use this model in your research, please cite the original HAT paper:
+If you use this model in your research, please cite both the original HAT paper and the SEN2NAIPv2 dataset:
 
 ```bibtex
 @article{chen2023hat,
@@ -77,4 +90,11 @@ If you use this model in your research, please cite the original HAT paper:
   journal={arXiv preprint arXiv:2205.04437},
   year={2022}
 }
+
+@misc{sen2naipv2,
+  title={SEN2NAIPv2: A Large-Scale Dataset for Satellite Image Super-Resolution},
+  author={TACO Foundation},
+  year={2024},
+  url={https://huggingface.co/datasets/tacofoundation/SEN2NAIPv2}
+}
 ```

app.py

@@ -826,6 +826,21 @@ with gr.Blocks(css=css, title="HAT Super-Resolution for Satellite Images") as if
     gr.Markdown("Upload a satellite image or select a sample to enhance its resolution by 4x.")
     gr.Markdown("⚠️ **Important**: Images must be exactly **130x130 pixels** for the model to work properly.")
 
+    # Acknowledgments section
+    with gr.Accordion("Acknowledgments", open=False):
+        gr.Markdown("""
+        ### Base Model: HAT (Hybrid Attention Transformer)
+        This model is a fine tuned version of **HAT**:
+        - **GitHub Repository**: [https://github.com/XPixelGroup/HAT](https://github.com/XPixelGroup/HAT)
+        - **Paper**: [Activating More Pixels in Image Super-Resolution Transformer](https://arxiv.org/abs/2205.04437)
+        - **Authors**: Xiangyu Chen, Xintao Wang, Jiantao Zhou, Yu Qiao, Chao Dong
+
+        ### Training Dataset: SEN2NAIPv2
+        The model was fine-tuned using the **SEN2NAIPv2** dataset:
+        - **HuggingFace Dataset**: [https://huggingface.co/datasets/tacofoundation/SEN2NAIPv2](https://huggingface.co/datasets/tacofoundation/SEN2NAIPv2)
+        - **Description**: High-resolution satellite imagery dataset for super-resolution tasks
+        """)
+
     # Sample images
     sample_images = get_sample_images()
     sample_buttons = []