Upload Core-S2RGB-249k-DINOv2 dataset

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DINOv2_crop_384x384.parquet

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README.md

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+---
+license: cc-by-sa-4.0
+task_categories:
+  - text-to-image
+  - image-to-image
+  - other
+language:
+  - en
+tags:
+  - satellite-imagery
+  - earth-observation
+  - embeddings
+  - geospatial
+  - clip
+  - majortom
+size_categories:
+  - 100K<n<1M
+---
+
+# Core-S2RGB-249k-DINOv2
+
+Vision-only embedding dataset computed from **Core-S2L2A-249k** using the **DINOv2-large** model.
+
+## Overview
+
+| Property | Value |
+|----------|-------|
+| Source imagery | Core-S2L2A-249k (248,719 patches, 384 × 384 px) |
+| Model | DINOv2-large (facebook/dinov2-large) |
+| Input bands | RGB [B04, B03, B02] |
+| Embedding dimension | 768 |
+| Output format | GeoParquet |
+| License | CC-BY-SA-4.0 |
+
+## Computation Pipeline
+
+1. **Pre-processing**: Each 384 × 384 Sentinel-2 L2A patch is read from the source parquet files. The RGB bands (B04, B03, B02) are stacked and normalised with `2.5 * (bands / 1e4).clip(0, 1)` to produce a true-colour image in the [0, 1] range.
+2. **Resize**: The image is resized to the DINOv2 input size of **224 × 224** pixels using nearest-neighbour interpolation.
+3. **Encoding**: The resized RGB tensor is fed into DINOv2-large (a self-supervised ViT trained on natural images) to extract a 768-dimensional CLS-token embedding.
+4. **Post-processing**: No L2-normalisation is applied during dataset generation; normalisation is performed at retrieval time if required.
+5. **Geospatial metadata**: The original UTM footprint is reprojected to EPSG:4326 (WGS-84) to obtain the `geometry`, `centre_lat`, and `centre_lon` fields. Additional metadata (`product_id`, `grid_cell`, `timestamp`, `utm_crs`, `pixel_bbox`) is preserved from the source dataset.
+
+## File Layout
+
+```
+.
+├── DINOv2_crop_384x384.parquet   # Main embedding GeoParquet (248,719 rows)
+└── README.md
+```
+
+## Schema
+
+| Column | Type | Description |
+|--------|------|-------------|
+| `unique_id` | string | SHA-256 hash of geometry + timestamp + product_id + embedding |
+| `embedding` | list<float> | 768-dim DINOv2 feature vector |
+| `timestamp` | datetime | Acquisition timestamp |
+| `product_id` | string | Original Sentinel-2 product identifier |
+| `grid_cell` | string | Major-TOM grid cell identifier |
+| `grid_row_u` | int16 | Grid row index |
+| `grid_col_r` | int16 | Grid column index |
+| `geometry` | geometry | WGS-84 polygon (footprint) |
+| `centre_lat` | float32 | Latitude of patch centre |
+| `centre_lon` | float32 | Longitude of patch centre |
+| `utm_footprint` | string | Original UTM footprint as WKT |
+| `utm_crs` | string | UTM CRS (e.g. EPSG:32633) |
+| `pixel_bbox` | list<int> | Pixel bounding box [x_min, y_min, x_max, y_max] |
+| `parquet_url` | string | Source parquet file path in the image dataset |
+| `parquet_row` | int64 | Row index within the source parquet file |
+
+## Usage
+
+```python
+import pandas as pd
+
+df = pd.read_parquet("DINOv2_crop_384x384.parquet")
+print(len(df), "embeddings")
+print(df.iloc[0].embedding.shape)  # (768,)
+```
+
+## Citation
+
+If you use this embedding dataset, please cite the original Major-TOM paper and the DINOv2 paper:
+
+```bibtex
+@article{zheng2026earthembeddingexplorer,
+  title={EarthEmbeddingExplorer: A Web Application for Cross-Modal Retrieval of Global Satellite Images},
+  author={Zheng, Yijie and Wu, Weijie and Wu, Bingyue and Zhao, Long and Li, Guoqing and Czerkawski, Mikolaj and Klemmer, Konstantin},
+  journal={arXiv preprint arXiv:2603.29441},
+  year={2026},
+  note={ICLR 2026 Workshop ML4RS Tutorial Track (oral)}
+}
+```
+
+```bibtex
+@inproceedings{francis2024majortom,
+  title={Major TOM: Expandable Datasets for Earth Observation},
+  author={Francis, Alistair and Czerkawski, Mikolaj},
+  year={2024},
+  booktitle={IGARSS 2024},
+  eprint={2402.12095},
+  archivePrefix={arXiv}
+}
+```