| --- |
| license: cc0-1.0 |
| base_model: tacofoundation/SEN2SR |
| tags: |
| - sentinel-2 |
| - super-resolution |
| - remote-sensing |
| - pytorch |
| pipeline_tag: image-to-image |
| model-index: |
| - name: WEO-SAS/sen2sr |
| results: |
| - task: |
| type: image-to-image |
| name: Satellite Image Super-Resolution |
| dataset: |
| name: NAIP (4x Sentinel-2 → NAIP) |
| type: custom |
| config: naip |
| metrics: |
| - name: Improvement Score |
| type: improvement |
| value: 0.8743 |
| - name: Hallucination Rate |
| type: hallucination |
| value: 0.0561 |
| - name: Omission Rate |
| type: omission |
| value: 0.0696 |
| - task: |
| type: image-to-image |
| name: Satellite Image Super-Resolution |
| dataset: |
| name: SPOT (4x Sentinel-2 → SPOT) |
| type: custom |
| config: spot |
| metrics: |
| - name: Improvement Score |
| type: improvement |
| value: 0.7992 |
| - name: Hallucination Rate |
| type: hallucination |
| value: 0.0734 |
| - name: Omission Rate |
| type: omission |
| value: 0.1274 |
| - task: |
| type: image-to-image |
| name: Satellite Image Super-Resolution |
| dataset: |
| name: Spain Crops (4x Sentinel-2 → SPOT) |
| type: custom |
| config: spain_crops |
| metrics: |
| - name: Improvement Score |
| type: improvement |
| value: 0.8406 |
| - name: Hallucination Rate |
| type: hallucination |
| value: 0.0735 |
| - name: Omission Rate |
| type: omission |
| value: 0.0859 |
| - task: |
| type: image-to-image |
| name: Satellite Image Super-Resolution |
| dataset: |
| name: Spain Urban (4x Sentinel-2 → SPOT) |
| type: custom |
| config: spain_urban |
| metrics: |
| - name: Improvement Score |
| type: improvement |
| value: 0.6954 |
| - name: Hallucination Rate |
| type: hallucination |
| value: 0.1156 |
| - name: Omission Rate |
| type: omission |
| value: 0.1890 |
| --- |
| |
| <p align="center"> |
| <img src="https://cdn-uploads.huggingface.co/production/uploads/6402474cfa1acad600659e92/G1o2oiRwJaqw4ZP9nG0NO.webp" width="100%"> |
| </p> |
|
|
| <p align="center"> |
| <em>Sentinel-2 super-resolution up to 2.5 m — WEO-SAS packaging of <a href="https://huggingface.co/tacofoundation/SEN2SR">tacofoundation/SEN2SR</a></em> |
| </p> |
|
|
| --- |
|
|
| This repository re-packages the original [tacofoundation/SEN2SR](https://huggingface.co/tacofoundation/SEN2SR) models with the **WEO-SAS standard interface** (`model.py`, `predictor.py`, `config.json`) so they can be loaded and used identically to all other WEO-SAS models. |
|
|
| **Original work:** [ESAOpenSR/sen2sr](https://github.com/ESAOpenSR/sen2sr) — license CC0-1.0. |
|
|
| --- |
|
|
| ## Model Variants |
|
|
| Six variants are available as **HuggingFace branches**, each with a different architecture, input bands, and upscaling factor. |
|
|
| | Branch | Architecture | Input bands | Output bands | Scale | Description | |
| |---|---|---|---|---|---| |
| | `main` *(default)* | CNN | 4 (RGBN) | 4 (RGBN) | 4× | SEN2SRLite — RGBN 10 m → 2.5 m | |
| | `lite-rswir-x2` | CNN | 10 (all S2) | 6 (RSWIR) | 2× | SEN2SRLite — 20 m bands → 10 m | |
| | `lite-main` | CNN | 10 (all S2) | 10 (all S2) | 4× | SEN2SRLite — full 10-band pipeline 10 m → 2.5 m | |
| | `mamba-rgbn-x4` | Mamba | 4 (RGBN) | 4 (RGBN) | 4× | SEN2SR — RGBN 10 m → 2.5 m (higher accuracy) | |
| | `mamba-rswir-x2` | Swin2SR | 10 (all S2) | 6 (RSWIR) | 2× | SEN2SR — 20 m bands → 10 m (higher accuracy) | |
| | `mamba-main` | Mamba + Swin2SR | 10 (all S2) | 10 (all S2) | 4× | SEN2SR — full 10-band pipeline (highest accuracy) | |
|
|
| **Band order expected as input:** |
|
|
| | Variant | Bands | |
| |---|---| |
| | RGBN (`main`, `mamba-rgbn-x4`) | B04, B03, B02, B08 | |
| | All others (10 bands) | B04, B03, B02, B08, B05, B06, B07, B8A, B11, B12 | |
|
|
| --- |
|
|
| ## Installation |
|
|
| ```bash |
| # For CNN variants (main, lite-rswir-x2, lite-main) |
| pip install sen2sr safetensors huggingface_hub rasterio |
| |
| # For Mamba/Swin variants (mamba-*) |
| pip install mamba-ssm --no-build-isolation |
| pip install sen2sr safetensors huggingface_hub rasterio |
| ``` |
|
|
| --- |
|
|
| ## Usage |
|
|
| All variants share the **same interface**. Only the `revision` argument changes. |
|
|
| ### Load any variant |
|
|
| ```python |
| from huggingface_hub import snapshot_download |
| import sys |
| |
| # Choose your variant: |
| local_dir = snapshot_download("WEO-SAS/sen2sr") # RGBN 4x (CNN) — default |
| local_dir = snapshot_download("WEO-SAS/sen2sr", revision="lite-rswir-x2") # RSWIR 2x (CNN) |
| local_dir = snapshot_download("WEO-SAS/sen2sr", revision="lite-main") # Full 10-band 4x (CNN) |
| local_dir = snapshot_download("WEO-SAS/sen2sr", revision="mamba-rgbn-x4") # RGBN 4x (Mamba) |
| local_dir = snapshot_download("WEO-SAS/sen2sr", revision="mamba-rswir-x2")# RSWIR 2x (Swin2SR) |
| local_dir = snapshot_download("WEO-SAS/sen2sr", revision="mamba-main") # Full 10-band 4x (Mamba+Swin) |
| |
| sys.path.insert(0, local_dir) |
| from model import Model |
| |
| model = Model(local_dir=local_dir) |
| print(model.description) |
| ``` |
|
|
| ### Array inference |
|
|
| ```python |
| import numpy as np |
| |
| # image: (C, H, W) float32, values in [0, 1] (C=4 for RGBN, C=10 for full-band) |
| image = np.random.rand(4, 128, 128).astype("float32") |
| |
| sr = model.predict(image) # (C, H*4, W*4) float32 |
| print(sr.shape) # (4, 512, 512) |
| ``` |
|
|
| ### GeoTIFF pipeline |
|
|
| Reads Sentinel-2 DN values directly (auto-normalises by /10000), writes a super-resolved GeoTIFF with the correct pixel size. |
|
|
| ```python |
| model.predict_tif( |
| input_path = "s2_scene_10m.tif", |
| output_path = "s2_scene_2p5m.tif", |
| bands = [0, 1, 2, 3], # 0-based band indices (default: first C bands) |
| ) |
| ``` |
|
|
| ### Override config at load time |
|
|
| ```python |
| model = Model(local_dir=local_dir, patch_size=256, overlap=64) |
| ``` |
|
|
| --- |
|
|
| ## RGBN 10 m → 2.5 m (`main`, `mamba-rgbn-x4`) |
|
|
| Super-resolves the four 10 m Sentinel-2 bands (Red, Green, Blue, NIR) by 4×. |
|
|
| <p align="center"> |
| <img src="https://huggingface.co/tacofoundation/SEN2SR/resolve/main/assets/srimg02.png" width="100%"> |
| </p> |
|
|
| --- |
|
|
| ## Full 10-band 10 m → 2.5 m (`lite-main`, `mamba-main`) |
|
|
| Multi-stage pipeline: RGBN bands are super-resolved at 4×, while the 20 m bands (B05, B06, B07, B8A, B11, B12) are first sharpened to 10 m then to 2.5 m. All 10 bands are returned at 2.5 m. |
|
|
| <p align="center"> |
| <img src="https://huggingface.co/tacofoundation/SEN2SR/resolve/main/assets/srimg01.png" width="100%"> |
| </p> |
|
|
| --- |
|
|
| ## RSWIR 20 m → 10 m (`lite-rswir-x2`, `mamba-rswir-x2`) |
|
|
| Sharpens the six 20 m Sentinel-2 bands (B05, B06, B07, B8A, B11, B12) to 10 m resolution using all 10 bands as context input. |
|
|
| <p align="center"> |
| <img src="https://huggingface.co/tacofoundation/SEN2SR/resolve/main/assets/srimg03.png" width="100%"> |
| </p> |
|
|
| --- |
|
|
| ## Large image inference |
|
|
| For images larger than the 128×128 training patch size, `predict_tif` and `predict` automatically tile the input with overlapping patches and blend them seamlessly. |
|
|
| <p align="center"> |
| <img src="https://huggingface.co/tacofoundation/SEN2SR/resolve/main/assets/srimg05.png" width="95%"> |
| </p> |
|
|
| --- |
|
|
| ## Repository structure |
|
|
| Each branch contains a flat directory with the same set of files: |
|
|
| ``` |
| config.json # Variant-specific inference parameters |
| model.py # Public entry point (WEO-SAS standard) |
| predictor.py # Tiled inference logic |
| sen2sr_pt.py # HF-aware model loader (handles CNN / Mamba / Swin) |
| base.py # Abstract base class |
| model.safetensor # Primary model weights |
| hard_constraint.safetensor# Hard-constraint weights |
| load.py # Original tacofoundation loading script |
| mlm.json # Original MLSTAC metadata |
| # multi-stage branches also include: |
| sr_model.safetensor / sr_hard_constraint.safetensor (RGBN stage) |
| f2_model.safetensor / f2_hard_constraint.safetensor (RSWIR 2x stage) |
| ``` |
|
|
| --- |
|
|
| ## Citation |
|
|
| If you use these models please cite the original work: |
|
|
| ```bibtex |
| @software{sen2sr2024, |
| author = {Aybar, Cesar and others}, |
| title = {SEN2SR: Sentinel-2 Super-Resolution}, |
| url = {https://github.com/ESAOpenSR/sen2sr}, |
| year = {2024} |
| } |
| ``` |
|
|
