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docs fixes (#337)
* docs fixes * bump semver and changelog * bump semver and changelog
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CHANGELOG.md

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@@ -5,7 +5,12 @@ All notable changes to the [Nucleus Python Client](https://github.com/scaleapi/n
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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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## [0.14.9](https://github.com/scaleapi/nucleus-python-client/releases/tag/v0.14.9) - 2022-07-14
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## [0.14.11](https://github.com/scaleapi/nucleus-python-client/releases/tag/v0.14.11) - 2022-07-20
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### Fixed
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- Various docstring and typing updates
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## [0.14.10](https://github.com/scaleapi/nucleus-python-client/releases/tag/v0.14.10) - 2022-07-20
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### Added
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- `Dataset.items_and_annotation_generator()`

nucleus/__init__.py

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@@ -441,7 +441,8 @@ def delete_dataset(self, dataset_id: str) -> dict:
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Deletes a dataset by ID.
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All items, annotations, and predictions associated with the dataset will
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be deleted as well.
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be deleted as well. Note that if this dataset is linked to a Scale or Rapid
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labeling project, the project itself will not be deleted.
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Parameters:
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dataset_id: The ID of the dataset to delete.

nucleus/annotation.py

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@@ -105,7 +105,7 @@ class BoxAnnotation(Annotation): # pylint: disable=R0902
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reference_id="image_1",
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annotation_id="image_1_car_box_1",
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metadata={"vehicle_color": "red"},
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embedding_vector=[0.1423, 1.432, ...3.829],
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embedding_vector=[0.1423, 1.432, ..., 3.829],
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)
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Parameters:
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reference_id="image_2",
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annotation_id="image_2_bus_polygon_1",
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metadata={"vehicle_color": "yellow"},
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embedding_vector=[0.1423, 1.432, ...3.829],
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embedding_vector=[0.1423, 1.432, ..., 3.829],
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)
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Parameters:
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from nucleus import SegmentationAnnotation
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segmentation = SegmentationAnnotation(
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mask_url="s3://your-bucket-name/segmentation-masks/image_2_mask_id1.png",
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mask_url="s3://your-bucket-name/segmentation-masks/image_2_mask_id_1.png",
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annotations=[
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Segment(label="grass", index="1"),
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Segment(label="road", index="2"),
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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, or a local path. The mask is an HxW int8 array saved in PNG format,
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accessible to Scale. This "URL" can also 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).

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