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Release notes for 0.8.0 (#260)
* Check in release notes for next version * 0.8.0 Co-authored-by: Ubuntu <diego.ardila@scale.com>
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CHANGELOG.md

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The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
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and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
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## [0.8.0](https://github.com/scaleapi/nucleus-python-client/releases/tag/v0.8.0) - 2022-03-16
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### Added
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- mask_url can now be a local file for segmentation annotations or predictions, meaning local upload is now supported for segmentations
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- Camera params for sensor fusion ingest now support additional camera params to accommodate fisheye camera, etc.
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- More detailed parameters to control for upload in case of timeouts (see dataset.upload_predictions, dataset.append, and dataset.upload_predictions)
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### Fixed
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- Artificially low concurrency for local uploads (all local uploads should be faster now)
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- Client no longer uses the deprecated (and now removed) segmentation-specific server endpoints
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- Fixed a bug where retries for local uploads were not working properly: should improve local upload robustness
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### Removed
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- client.predict, client.annotate, which have been marked as deprecated for several months.
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## [0.7.0](https://github.com/scaleapi/nucleus-python-client/releases/tag/v0.7.0) - 2022-03-09
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### Added

nucleus/annotation.py

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Parameters:
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mask_url (str): A URL pointing to the segmentation prediction mask which is
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accessible to Scale. The mask is an HxW int8 array saved in PNG format,
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accessible to Scale, or a local path. The mask is an HxW int8 array saved in PNG format,
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with each pixel value ranging from [0, N), where N is the number of
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possible classes (for semantic segmentation) or instances (for instance
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segmentation).

nucleus/prediction.py

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Parameters:
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mask_url (str): A URL pointing to the segmentation prediction mask which is
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accessible to Scale. The mask is an HxW int8 array saved in PNG format,
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accessible to Scale. This URL can be a path to a local file.
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The mask is an HxW int8 array saved in PNG format,
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with each pixel value ranging from [0, N), where N is the number of
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possible classes (for semantic segmentation) or instances (for instance
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segmentation).

pyproject.toml

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[tool.poetry]
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name = "scale-nucleus"
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version = "0.7.0"
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version = "0.8.0"
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description = "The official Python client library for Nucleus, the Data Platform for AI"
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license = "MIT"
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authors = ["Scale AI Nucleus Team <nucleusapi@scaleapi.com>"]

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