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.