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README.md

@@ -1,6 +1,6 @@
 ---
 pretty_name: PanScale
-license: other
+license: cc-by-4.0
 task_categories:
   - image-to-image
 tags:
@@ -12,23 +12,21 @@ size_categories:
   - 1K<n<10K
 ---
 
-# PanScale Dataset
+# PanScale
 
 ## Dataset Summary
 
-PanScale is a remote sensing pansharpening dataset organized as paired multispectral (`ms`) and panchromatic (`pan`) TIFF images.
+PanScale is a remote-sensing pansharpening dataset with paired multispectral (`ms`) and panchromatic (`pan`) TIFF images for cross-scale evaluation.
 
-- Total paired samples: **7,559**
-- Total size on disk: **~6.9 GB**
-- Pairing rule: files are matched by identical filename in `ms/` and `pan/` (for example, `123.tif` with `123.tif`)
-- Data type (checked from files): **8-bit TIFF**, with `ms` as **4-channel** and `pan` as **1-channel**
-
-This release contains standard train/test subsets and full-resolution cross-scale test subsets.
+- Total pairs: **7,559**
+- Disk size: **~6.9 GB**
+- Format: **8-bit TIFF**, `ms` = **4 channels**, `pan` = **1 channel**
+- Pairing: same filename in `ms/` and `pan/` (for example, `123.tif` <-> `123.tif`)
 
 ## Supported Tasks
 
 - Pansharpening (PAN + MS fusion)
-- Cross-scale generalization evaluation for pansharpening methods
+- Cross-scale generalization benchmarking
 
 ## Dataset Structure
 
@@ -68,101 +66,36 @@ PanScale/
     test2000/{ms,pan}
 ```
 
-## Split Statistics
-
-### Standard subsets (same spatial size for `ms` and `pan`)
-
-| Sensor | Split | # Pairs | MS size | PAN size |
-|---|---:|---:|---:|---:|
-| jilin | train200 | 1055 | 200x200 | 200x200 |
-| jilin | test200 | 34 | 200x200 | 200x200 |
-| jilin | test400 | 34 | 400x400 | 400x400 |
-| jilin | test800 | 34 | 800x800 | 800x800 |
-| landsat | train256 | 2484 | 256x256 | 256x256 |
-| landsat | test200 | 96 | 200x200 | 200x200 |
-| landsat | test400 | 96 | 400x400 | 400x400 |
-| landsat | test800 | 96 | 800x800 | 800x800 |
-| landsat | test1600 | 96 | 1600x1600 | 1600x1600 |
-| skysat | train200 | 2370 | 200x200 | 200x200 |
-| skysat | test200 | 88 | 200x200 | 200x200 |
-| skysat | test400 | 88 | 400x400 | 400x400 |
-| skysat | test800 | 88 | 800x800 | 800x800 |
-| skysat | test1600 | 88 | 1600x1600 | 1600x1600 |
-
-### Full-resolution cross-scale subsets (`f*`)
-
-| Sensor | Split | # Pairs | MS size | PAN size | PAN/MS scale |
-|---|---:|---:|---:|---:|---:|
-| fjilin | test800 | 121 | 200x200 | 800x800 | 4.0 |
-| fjilin | test1200 | 121 | 300x300 | 1200x1200 | 4.0 |
-| fjilin | test1600 | 121 | 400x400 | 1600x1600 | 4.0 |
-| fjilin | test2000 | 121 | 500x500 | 2000x2000 | 4.0 |
-| flandsat | test800 | 48 | 400x400 | 800x800 | 2.0 |
-| flandsat | test1200 | 48 | 600x600 | 1200x1200 | 2.0 |
-| flandsat | test1600 | 48 | 800x800 | 1600x1600 | 2.0 |
-| flandsat | test2000 | 48 | 1000x1000 | 2000x2000 | 2.0 |
-| fskysat | test800 | 34 | 320x320 | 800x800 | 2.5 |
-| fskysat | test1200 | 34 | 480x480 | 1200x1200 | 2.5 |
-| fskysat | test1600 | 34 | 640x640 | 1600x1600 | 2.5 |
-| fskysat | test2000 | 34 | 800x800 | 2000x2000 | 2.5 |
-
-## Data Fields
-
-Each sample consists of:
-
-- `pan`: panchromatic image (`.tif`, 1 channel)
-- `ms`: multispectral image (`.tif`, 4 channels)
-- `id`: numeric filename stem (for example, `1`, `2`, ...)
+## Subsets at a Glance
 
-## Example Loading (Python)
-
-```python
-from pathlib import Path
-
-root = Path("PanScale/jilin/train200")
-ms_dir = root / "ms"
-pan_dir = root / "pan"
-
-for ms_path in sorted(ms_dir.glob("*.tif")):
-    pan_path = pan_dir / ms_path.name
-    if not pan_path.exists():
-        continue
-    # Use your TIFF reader here (e.g., tifffile, rasterio, PIL)
-    # ms = read_tiff(ms_path)
-    # pan = read_tiff(pan_path)
-```
+| Subset | Splits | # Pairs | MS size | PAN size | PAN/MS scale |
+|---|---|---:|---|---|---:|
+| `jilin` | `train200`, `test200/400/800` | 1,157 | 200-800 | 200-800 | 1.0 |
+| `landsat` | `train256`, `test200/400/800/1600` | 2,868 | 200-1600 | 200-1600 | 1.0 |
+| `skysat` | `train200`, `test200/400/800/1600` | 2,722 | 200-1600 | 200-1600 | 1.0 |
+| `fjilin` | `test800/1200/1600/2000` | 484 | 200-500 | 800-2000 | 4.0 |
+| `flandsat` | `test800/1200/1600/2000` | 192 | 400-1000 | 800-2000 | 2.0 |
+| `fskysat` | `test800/1200/1600/2000` | 136 | 320-800 | 800-2000 | 2.5 |
 
-## Recommended Hugging Face Upload Layout
+## Data Fields
 
-Upload the `PanScale/` directory directly so users can keep the current sensor/split organization:
+- `ms`: 4-channel multispectral image (`.tif`)
+- `pan`: 1-channel panchromatic image (`.tif`)
+- `id`: filename stem (integer)
 
-```text
-dataset-repo/
-  README.md
-  PanScale/
-    ...
-```
 
 ## Intended Use
 
-This dataset is intended for research and benchmarking in:
-
-- pansharpening model training and evaluation
-- cross-scale robustness analysis
-- comparison of remote sensing fusion methods across sensors
-
-## Limitations
-
-- The dataset card currently omits full acquisition/annotation details because the corresponding paper metadata is pending public release.
-- Sensor-specific radiometric and preprocessing details should be added before final camera-ready publication.
+- Pansharpening training and evaluation
+- Cross-scale robustness analysis across sensors
 
 ## License
 
-**TBD**. Please replace this section with the actual license and usage restrictions before public release.
+This dataset is released under **CC BY 4.0**.
 
 ## Citation
 
-Citation will be added after the paper is publicly available.
+Citation information will be added after the paper is publicly available.
 
 ```bibtex
 @article{,
@@ -172,7 +105,3 @@ Citation will be added after the paper is publicly available.
   year={}
 }
 ```
-
-## Contact
-
-Please add maintainer contact information (email or project page) before release.