Raster Vision 0.30 is released

[AdeelH]

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