| --- |
| pretty_name: hyperComp Satellite Training Scenes |
| task_categories: |
| - image-to-image |
| size_categories: |
| - 10K<n<100K |
| --- |
| |
| # hyperComp satellite training scenes |
|
|
| This dataset contains 10,000 training scenes and 1,000 validation scenes for |
| training the hyperComp compression autoencoder. Every scene is an unpadded, |
| unresized 1024x1024 RGB provider response. The training loader slices each scene |
| into sixteen non-overlapping 256x256 patches at indexing time. |
|
|
| The imagery comes from seven open provider families: NASA Worldview |
| MODIS/VIIRS, USDA NAIP, Queensland aerial orthophotos, Netherlands PDOK, Spain |
| PNOA, France BD ORTHO, and Switzerland SWISSIMAGE. Exact decoded-pixel, |
| perceptual, and pretrained ResNet-18 semantic deduplication are applied before |
| the leakage-safe train/validation split. |
|
|
| `manifests/dataset.csv` records the split, source family, provider, product, |
| location, capture date, request URL, license URL, attribution, image hashes, |
| ground resolution, leakage group, and diversity measurements for every scene. |
| `manifests/dedup_report.json` and `manifests/diversity_report.json` document the |
| build filters and five diversity axes. Consult each row's license and |
| attribution fields when redistributing or using an image. |
|
|
