SDO
Datasets
All datasets matching “SDO”SDO
🌞 SDO ML-Ready Dataset: AIA and HMI Level-1.5
Overview
This dataset provides machine learning (ML)-ready solar data curated from NASA’s Solar Dynamics Observatory (SDO), covering observations from May 13, 2010, to July 31, 2024. It includes Level-1.5 processed data from:
Atmospheric Imaging Assembly (AIA):
Helioseismic and Magnetic Imager (HMI):
The dataset is designed to facilitate large-scale ML applications in heliophysics, such as solar activity forecasting… See the full description on the dataset page: https://huggingface.co/datasets/harshinde/SDO.core-sdo
ML-Ready Multi-Modal Image Dataset from SDO
Overview
This dataset provides machine learning (ML)-ready solar data curated from NASA’s Solar Dynamics Observatory (SDO), covering observations from May 13, 2010, to Dec 31, 2024. It includes Level-1.5 processed data from: Atmospheric Imaging Assembly (AIA)
and Helioseismic and Magnetic Imager (HMI).
The dataset is designed to facilitate large-scale learning applications in heliophysics, such as space weather forecasting… See the full description on the dataset page: https://huggingface.co/datasets/nasa-ibm-ai4science/core-sdo.sdoml-lite
SDOML-lite
SDOML-lite is a lightweight alternative to the SDOML dataset specifically designed for machine learning applications in solar physics, providing continuous full-disk images of the Sun with magnetic field and extreme ultraviolet data in several wavelengths. The data source is the Solar Dynamics Observatory (SDO) space telescope, a NASA mission that has been in operation since 2010.
NASA’s SDO mission has generated over 20 petabytes of high-resolution solar imagery… See the full description on the dataset page: https://huggingface.co/datasets/oxai4science/sdoml-lite.sdocx-compatibility
SDOCX Compatibility Corpus
This dataset contains paired Samsung Notes .sdocx documents and reference PDF exports for parser, renderer, and visual-regression testing. Each pair has a numeric ID and descriptive name recorded below.
The .sdocx file is the source fixture. The matching PDF is the expected visible result exported from Samsung Notes; it is a visual reference, not a byte-for-byte rendering requirement.
Files
ID
Source
Reference
Coverage… See the full description on the dataset page: https://huggingface.co/datasets/twangodev/sdocx-compatibility.sdo_mobilesd-orgasmic-c1
epicff series: Based on epicphotogasm, using dreambooth to finetuning. Nice outputs, but a little stiff.
epicmq : I don't remember.
htc: Based on SD-1.5 pruned (my mistake), using dreambooth to finetuning. Very creative model, but very hard to create good images by itself.
merged_ft: Based on a mix of SD-1.5 full (7GB) with 70% on epicphotogasm for structure, using Novel AI finetuning. Good mix between flexibility and polish.