Changelog

Features:

• Allow passing pipeline configs as JSON files to the rastervision run CLI cmd (#2136)
  • (as an alternative to the traditional method of passing a .py file with a get_config() function)

Fixes:

• Add rastervision_aws_sagemaker to API reference on RTD (#2117)
• Let RasterSource.get_chip_by_map_window() take all RasterSource.get_chip() args (#2136)
• Make repr more concise for some configs (#2136)
• Misc config serialization fixes and improvements (#2136)
• Avoid double-wrapping model in DistributedDataParallel (#2136)
• Make S3FileSystem.list_paths() only list direct children (#2136)
• Add missing RequestPayer arg to some s3-related boto3 API calls (#2136)
• Fix incorrect path in RV pipeline examples doc (#2138)

Maintenance:

• Update docker dependencies (#2116, #2122)
• Tweak coverage report generation (#2136)

Changelog

• Full changelog: https://docs.rastervision.io/en/0.30/changelog.html#raster-vision-0-30
• Migration guide: https://docs.rastervision.io/en/0.30/migration/v0-21_to_v0-30.html

Highlights

• Easier installation: Raster Vision no longer requires exact versions of dependencies, which means it can more easily be installed alongside other packages.
• AWS SageMaker support: you can now run Raster Vision jobs on SageMaker via

  rastervision run sagemaker ...
  

  You can even run training over multiple instances with multiple GPUs. See Running on AWS SageMaker for more details.
• Distributed training support: Raster Vision Learners now support distributed training (both multi-node and multi-GPU) via PyTorch DDP. If your machine has multiple GPUs, Raster Vision will now automatically use them all during training.
• New CLI command, predict_scene, that allows greater configurability than the predict command.

  rastervision predict_scene <model_bundle_uri> <scene_config_uri> [--predict_options_uri <predict_options_uri>]
  

• New tutorial: Predicting with an ONNX model.

PyPI

pip install rastervision==0.30.0

https://pypi.org/project/rastervision/0.30.0/

Docker image

docker pull quay.io/azavea/raster-vision:pytorch-0.30

Changelog

Full changelog: https://docs.rastervision.io/en/0.21/changelog.html#raster-vision-0-21-3

Highlights

• Features:
  • Allow reading pre-chipped datasets with non-RGB TIFF chips (#1932)
• Bug fixes:
  • Normalize pixel values in the Spacenet Vegas examples (#1930)
  • Account for bbox when saving predictions (#1931)
  • Bug fix: ensure SS datasets always return label array with correct dtype (#1954)
  • Fix bug in Visualizer when plotting temporal data w/ batch size 1 (#1958)
  • Allow specifying chip_sz in StatsTransform.from_raster_sources() (#1933)
  • Misc. minor fixes (#1933)
• Docs:
  • Update release instructions to simplify patch release process (#1934)
• Maintenance:
  • Bump pillow to address CVE-2023-4863 (#1952)
  • Update CI and release workflows to free up disk space before building docker image (#1953, #1959)

Pypi

pip install rastervision==0.21.3

https://pypi.org/project/rastervision/0.21.3/

Notes

• The pip installation is only guaranteed to work with Python 3.10.

Docker image

docker pull quay.io/azavea/raster-vision:pytorch-0.21

Changelog

Full changelog: https://docs.rastervision.io/en/0.21/changelog.html#raster-vision-0-21-2

Highlights

• Features:
  • Save model weights for each epoch (#1921) (@mmcs-work)
• Bug fixes:
  • Do not require every plugin recorded in the model bundle to be installed when using it (#1916)
  • Fix rastervision.core dependencies (#1920)

Pypi

pip install rastervision==0.21.2

https://pypi.org/project/rastervision/0.21.2/

Notes

• The pip installation is only guaranteed to work with Python 3.10.

Docker image

docker pull quay.io/azavea/raster-vision:pytorch-0.21

Changelog

https://docs.rastervision.io/en/0.21/changelog.html#raster-vision-0-21-1

Pypi

pip install rastervision==0.21.1

https://pypi.org/project/rastervision/0.21.1/

Notes

• The pip installation is only guaranteed to work with Python 3.10.

Docker image

docker pull quay.io/azavea/raster-vision:pytorch-0.21

Highlights

• Raster Vision can now consume imagery from STAC APIs
  • Tutorial: Imagery from STAC API + labels from OSM
• Raster Vision can now work with temporal data
  • Tutorial: Working with time-series of images
• Raster Vision can now export and use models in ONNX format

Changelog

https://docs.rastervision.io/en/0.21/changelog.html#raster-vision-0-21

Pypi

pip install rastervision==0.21

https://pypi.org/project/rastervision/0.21/

Notes

• The pip installation is only guaranteed to work with Python 3.10. Anaconda is highly recommended.

Docker image

docker pull quay.io/azavea/raster-vision:pytorch-0.21

This is a dummy release to trigger the generation of a DOI on Zenodo.

Changelog

https://docs.rastervision.io/en/0.20/changelog.html#raster-vision-0-20-2

Pypi

pip install rastervision==0.20.2

https://pypi.org/project/rastervision/0.20.2/

Notes

• The pip installation is only guaranteed to work with Python 3.9. Anaconda is highly recommended.

Docker image

docker pull quay.io/azavea/raster-vision:pytorch-0.20

Changelog

https://docs.rastervision.io/en/0.20/changelog.html#raster-vision-0-20-1

Pypi

pip install rastervision==0.20.1

https://pypi.org/project/rastervision/0.20.1/

Notes

• The pip installation is only guaranteed to work with Python 3.9. Anaconda is highly recommended.

Docker image

docker pull quay.io/azavea/raster-vision:pytorch-0.20

Changelog

https://docs.rastervision.io/en/0.20/changelog.html#raster-vision-0-20-0

Pypi

pip install rastervision==0.20

https://pypi.org/project/rastervision/0.20/

Notes

• The pip installation is only guaranteed to work with Python 3.9. Anaconda is highly recommended.
• If you encounter problems with gdal installation while installing rastervision_gdal_vsi, you can
  • try installing gdal via conda install -c conda-forge gdal==3.5.2
  • install all Raster Vision plugins except rastervision_gdal_vsi

    pip install \
        rastervision_pipeline==0.20 \
        rastervision_aws_s3==0.20 \
        rastervision_aws_batch==0.20 \
        rastervision_core==0.20 \
        rastervision_pytorch_learner==0.20 \
        rastervision_pytorch_backend==0.20
    

Docker image

docker pull quay.io/azavea/raster-vision:pytorch-0.20