Update README.md

README.md

@@ -54,7 +54,32 @@ To address these challenges, 'opensr-test' provides a fair approach for SR bench
 
 ## **Datasets**
 
-The `opensr-test` package provides five datasets for benchmarking SR models. These datasets are carefully crafted to minimize spatial and spectral misalignment. See our Hugging Face repository for more details about the datasets. [**https://huggingface.co/datasets/isp-uv-es/opensr-test**](https://huggingface.co/datasets/isp-uv-es/opensr-test)
+The `opensr-test` package provides five datasets for benchmarking SR models. These datasets are carefully crafted to minimize spatial and spectral misalignment. Each dataset consist of a dictionary with the following keys:
+
+- **`L2A`**: Sentinel-2 L2A bands (12 bands).
+- **`L1C`**: Sentinel-2 L1C bands (12 bands).
+- **`HR`**: High-resolution image (RGBNIR) without harmonization.
+- **`HRharm`**: Harmonized high-resolution image (RGBNIR). The HRharm image is **harmonized with respect to the Sentinel-2 L2A bands**.
+- **`metadata`**: A pandas DataFrame with the images' metadata.
+
+We provide 12 bands for Sentinel-2 L2A (see table below) and 13 for Sentinel-2 L1C (see table below).
+
+| Band | Description | Resolution (m) | L2A Index | L1C index |
+|------|-------------|----------------|-------| -------|
+| B01  | Coastal aerosol | 60 | 0 | 0 |
+| B02  | Blue | 10 | 1 | 1 |
+| B03  | Green | 10 | 2 | 2 |
+| B04  | Red | 10 | 3 | 3 |
+| B05  | Vegetation red edge | 20 | 4 | 4 |
+| B06  | Vegetation red edge | 20 | 5 | 5 |
+| B07  | Vegetation red edge | 20 | 6 | 6 |
+| B08  | NIR | 10 | 7 | 7 |
+| B8A  | Narrow NIR | 20 | 8 | 8 |
+| B09  | Water vapor | 60 | 9 | 9 |
+| B10  | Cirrus | 60 | - | 10 |
+| B11  | SWIR-I | 20 | 10 | 11 |
+| B12  | SWIR-II | 20 | 11 | 12 |
+
 
 ### **NAIP (X4 scale factor)**