docs fixes (#337)

* docs fixes

* bump semver and changelog

* bump semver and changelog

Author: drakejwong

CHANGELOG.md

@@ -5,7 +5,12 @@ All notable changes to the [Nucleus Python Client](https://github.com/scaleapi/n
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
-## [0.14.9](https://github.com/scaleapi/nucleus-python-client/releases/tag/v0.14.9) - 2022-07-14
+## [0.14.11](https://github.com/scaleapi/nucleus-python-client/releases/tag/v0.14.11) - 2022-07-20
+
+### Fixed
+- Various docstring and typing updates
+
+## [0.14.10](https://github.com/scaleapi/nucleus-python-client/releases/tag/v0.14.10) - 2022-07-20
 
 ### Added
 - `Dataset.items_and_annotation_generator()`

nucleus/__init__.py

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

nucleus/annotation.py

@@ -105,7 +105,7 @@ class BoxAnnotation(Annotation):  # pylint: disable=R0902
             reference_id="image_1",
             annotation_id="image_1_car_box_1",
             metadata={"vehicle_color": "red"},
-            embedding_vector=[0.1423, 1.432, ...3.829],
+            embedding_vector=[0.1423, 1.432, ..., 3.829],
         )
 
     Parameters:
@@ -310,7 +310,7 @@ class PolygonAnnotation(Annotation):
             reference_id="image_2",
             annotation_id="image_2_bus_polygon_1",
             metadata={"vehicle_color": "yellow"},
-            embedding_vector=[0.1423, 1.432, ...3.829],
+            embedding_vector=[0.1423, 1.432, ..., 3.829],
         )
 
     Parameters:
@@ -691,7 +691,7 @@ class SegmentationAnnotation(Annotation):
         from nucleus import SegmentationAnnotation
 
         segmentation = SegmentationAnnotation(
-            mask_url="s3://your-bucket-name/segmentation-masks/image_2_mask_id1.png",
+            mask_url="s3://your-bucket-name/segmentation-masks/image_2_mask_id_1.png",
             annotations=[
                 Segment(label="grass", index="1"),
                 Segment(label="road", index="2"),
@@ -704,7 +704,8 @@ class SegmentationAnnotation(Annotation):
 
     Parameters:
         mask_url (str): A URL pointing to the segmentation prediction mask which is
-          accessible to Scale, or a local path. The mask is an HxW int8 array saved in PNG format,
+          accessible to Scale. This "URL" can also be a path to a local file.
+          The mask is an HxW int8 array saved in PNG format,
           with each pixel value ranging from [0, N), where N is the number of
           possible classes (for semantic segmentation) or instances (for instance
           segmentation).