Comments (1)
Hi @caseyslaught 👋
Currently, the radiant-mlhub
Python client downloads the STAC catalog (the metadata) for the entire dataset and then uses this complete metadata file to apply filters. So, the downloader is performing as expected. However, the speed of download should not be dramatically impacted by this additional download since the STAC catalog is relatively small.
As for improvements to the functionality, our team is currently developing Radiant MLHub 2.0, which will help ease many of the download issues that arise with the current Python client.
We look forward to unveiling the updated Radaint MLHub very soon. 🎉
from radiant-mlhub.
Related Issues (20)
- Failure to download catalogs or data for datasets dlr_fusion_competition_germany and ref_fusion_competition_south_africa HOT 4
- Enable downloading assets within a pytest environment HOT 5
- Bug caused by PySTAC upgrade. bad version pinning in our setup.py
- 404 not found for registry url from recent mlhub version HOT 2
- improve projection metadata for sen12floods and other stacs so they can be used more easily with stackstac HOT 4
- Data download Error with collection_filter option HOT 2
- Provide new release to allow more recent `shapely`
- Able to update pystac pin?
- Include LICENSE file in package distribution
- Additional dataset attributes break Dataset.collections HOT 1
- Human-readable Collection info HOT 3
- When using api_key parameter, some class properties cannot be accessed HOT 1
- Move to One Flow branching strategy instead of Git Flow HOT 3
- Using `api_key` in `Dataset.download(...)` raises an exception HOT 4
- Drop support for Python 3.6 HOT 1
- Dataset organisation of SpaceNet 2: Vegas collection HOT 1
- Nothing is happening when I start a download HOT 2
- Continuous 104 exception trying to download the data for "dlr_fusion_competition_germany" HOT 3
- SpaceNet missing collections HOT 6
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from radiant-mlhub.