SSL
Datasets
All datasets matching “SSL”SSL4EO-S12-v1.1
SSL4EO-S12-v1.1
Attention: The Zarr Chunk file version of SSL4EO-S12-v1.1 was moved to embed2scale/SSL4EO-S12-v1.1-Zarr. This repository contains data that can be used with webdataset.
The dataset includes 246,144 locations with four timestamps each from the modalities S2L1C, S2L2A, S2RGB, S1GRD, LULC, DEM, and NDVI.
We refer to our technical report for details.
The samples are stored in as Zarr Zip files (zarr version 2) with the metadata directly aligned as additional data… See the full description on the dataset page: https://huggingface.co/datasets/embed2scale/SSL4EO-S12-v1.1.sslm-corpus-segmentsssl-checkpoints
ssl-checkpoints
The code to load the checkpoints to follow...
The repository is organised as follows:
Each folder corresponds to the data set used for our experiment.
Each subfolder represents the corresponding SSL technique used.
These subfolders contain the checkpoints for each transformation/pretext task considered. The five checkpoint files correspond to
the transformation Baseline, SimClr, Orthogonality, LoRot and DCL, respectively, described in the blog.
Llama3-SSL4EO-S12-v1.1-captions
Llama3-SSL4EO-S12-Captions
The captions are aligned with the SSL4EO-S12 v1.1 dataset and were automatically generated using the Llama3-LLaVA-Next-8B model.
Please find more information regarding the generation and evaluation in the Llama3-MS-CLIP paper.
Code: https://github.com/IBM/MS-CLIP
Data Structure
We provide the captions in two versions: As a single compressed Parquet file per split and as CSV files with 256 captions each that match the Zarr Zip files of the… See the full description on the dataset page: https://huggingface.co/datasets/ibm-esa-geospatial/Llama3-SSL4EO-S12-v1.1-captions.mmu_ssl_legacysurvey_north
mmu_ssl_legacysurvey_north HATS Catalog Collection
This is the collection of HATS catalogs representing mmu_ssl_legacysurvey_north.
This dataset is part of the Multimodal Universe,
a large-scale collection of multimodal astronomical data. For full details, see the paper:
The Multimodal Universe: Enabling Large-Scale Machine Learning with 100TBs of Astronomical Scientific Data.
Access the catalog
We recommend the use of the LSDB Python framework to access HATS… See the full description on the dataset page: https://huggingface.co/datasets/UniverseTBD/mmu_ssl_legacysurvey_north.SSL4EO-S12