formatting

luxonis_ml/data/datasets/annotation.py

@@ -77,7 +77,7 @@ class Annotation(ABC, BaseModelExtraForbid):
     @ivar instance_id: The instance id of the annotation. This
         determines the order in which individual instances are loaded in
         L{luxonis_ml.data.LuxonisLoader}.
-    @type _label_type: ClassVar[L{LabelType}]
+    @type _label_type: ClassVar[LabelType]
     @ivar _label_type: The label type of the annotation.
     """
 
@@ -110,7 +110,17 @@ def combine_to_numpy(
         width: int,
     ) -> np.ndarray:
         """Combines multiple instance annotations into a single numpy
-        array."""
+        array.
+
+        @type annotations: List[Annotation]
+        @param annotations: List of annotations to combine.
+        @type class_mapping: Dict[str, int]
+        @param class_mapping: Mapping of class names to class indices.
+        @type height: int
+        @param height: The height of the image.
+        @type width: int
+        @param width: The width of the image.
+        """
         pass
 
 
@@ -138,14 +148,14 @@ class BBoxAnnotation(Annotation):
 
     @type x: float
     @ivar x: The top-left x coordinate of the bounding box. Normalized
-        to [0, 1].
+        to M{[0, 1]}.
     @type y: float
     @ivar y: The top-left y coordinate of the bounding box. Normalized
-        to [0, 1].
+        to M{[0, 1]}.
     @type w: float
-    @ivar w: The width of the bounding box. Normalized to [0, 1].
+    @ivar w: The width of the bounding box. Normalized to M{[0, 1]}.
     @type h: float
-    @ivar h: The height of the bounding box. Normalized to [0, 1].
+    @ivar h: The height of the bounding box. Normalized to M{[0, 1]}.
     """
 
     type_: Literal["boundingbox"] = Field("boundingbox", alias="type")
@@ -211,11 +221,11 @@ def combine_to_numpy(
 class KeypointAnnotation(Annotation):
     """Keypoint annotation.
 
-    Values are normalized to [0, 1] based on the image size.
+    Values are normalized to M{[0, 1]} based on the image size.
 
     @type keypoints: List[Tuple[float, float, L{KeypointVisibility}]]
     @ivar keypoints: List of keypoints. Each keypoint is a tuple of (x, y, visibility).
-        x and y are normalized to [0, 1]. visibility is one of {0, 1, 2} where:
+        x and y are normalized to M{[0, 1]}. visibility is one of M{0}, M{1}, or M{2} where:
             - 0: Not visible / not labeled
             - 1: Occluded
             - 2: Visible
@@ -430,8 +440,8 @@ class PolylineSegmentationAnnotation(SegmentationAnnotation):
 
     @type points: List[Tuple[float, float]]
     @ivar points: List of points that define the polyline. Each point is
-        a tuple of (x, y). x and y are normalized to [0, 1] based on the
-        image size.
+        a tuple of (x, y). x and y are normalized to M{[0, 1]} based on
+        the image size.
     """
 
     type_: Literal["polyline"] = Field("polyline", alias="type")

luxonis_ml/data/datasets/base_dataset.py

@@ -44,7 +44,7 @@ def update_source(self, source: LuxonisSource) -> None:
         LuxonisSource.
 
         @type source: L{LuxonisSource}
-        @param source: The new L{LuxonisSource} to replace the old one.
+        @param source: The new C{LuxonisSource} to replace the old one.
         """
         pass
 
@@ -122,8 +122,8 @@ def add(
 
         @type generator: L{DatasetIterator}
         @param generator: A Python iterator that yields either instances
-            of L{DatasetRecord} or a dictionary that can be converted to
-            L{DatasetRecord}.
+            of C{DatasetRecord} or a dictionary that can be converted to
+            C{DatasetRecord}.
         @type batch_size: int
         @param batch_size: The number of annotations generated before
             processing. This can be set to a lower value to reduce

luxonis_ml/data/datasets/luxonis_dataset.py

@@ -64,8 +64,8 @@ def __init__(
         @type bucket_type: BucketType
         @param bucket_type: Whether to use external cloud buckets
         @type bucket_storage: BucketStorage
-        @param bucket_storage: Underlying bucket storage from local, S3,
-            or GCS
+        @param bucket_storage: Underlying bucket storage. Can be one of
+            C{local}, C{S3}, or C{GCS}.
         @type delete_existing: bool
         @param delete_existing: Whether to delete a dataset with the
             same name if it exists
@@ -283,8 +283,8 @@ def update_source(self, source: LuxonisSource) -> None:
         """Updates underlying source of the dataset with a new
         L{LuxonisSource}.
 
-        @type source: L{LuxonisSource}
-        @param source: The new L{LuxonisSource} to replace the old one.
+        @type source: LuxonisSource
+        @param source: The new C{LuxonisSource} to replace the old one.
         """
 
         self.metadata["source"] = source.to_document()
@@ -826,7 +826,7 @@ def exists(
         @type bucket: Optional[str]
         @param bucket: Name of the bucket. Default is C{None}.
         @rtype: bool
-        @return: Whether the dataset exists
+        @return: Whether the dataset exists.
         """
         return dataset_name in LuxonisDataset.list_datasets(
             team_id, bucket_storage, bucket
@@ -840,8 +840,15 @@ def list_datasets(
     ) -> List[str]:
         """Returns a dictionary of all datasets.
 
-        @rtype: Dict
-        @return: Dictionary of all datasets
+        @type team_id: Optional[str]
+        @param team_id: Optional team identifier
+        @type bucket_storage: BucketStorage
+        @param bucket_storage: Underlying bucket storage from C{local},
+            C{S3}, or C{GCS}. Default is C{local}.
+        @type bucket: Optional[str]
+        @param bucket: Name of the bucket. Default is C{None}.
+        @rtype: List[str]
+        @return: List of all dataset names.
         """
         base_path = environ.LUXONISML_BASE_PATH
 

luxonis_ml/data/loaders/base_loader.py

@@ -45,7 +45,7 @@ def __getitem__(self, idx: int) -> LuxonisLoaderOutput:
         @type idx: int
         @param idx: Index of the sample to load.
         @rtype: L{LuxonisLoaderOutput}
-        @return: Sample's data in L{LuxonisLoaderOutput} format.
+        @return: Sample's data in C{LuxonisLoaderOutput} format.
         """
         pass
 

luxonis_ml/data/loaders/luxonis_loader.py

@@ -30,10 +30,10 @@ def __init__(
         """A loader class used for loading data from L{LuxonisDataset}.
 
         @type dataset: LuxonisDataset
-        @param dataset: LuxonisDataset to use
+        @param dataset: Instance of C{LuxonisDataset} to use.
         @type view: Union[str, List[str]]
         @param view: What splits to use. Can be either a single split or
-            a list of splits. Defaults to "train".
+            a list of splits. Defaults to C{"train"}.
         @type stream: bool
         @param stream: Flag for data streaming. Defaults to C{False}.
         @type augmentations: Optional[luxonis_ml.loader.Augmentations]
@@ -141,7 +141,7 @@ def __len__(self) -> int:
         """Returns length of the dataset.
 
         @rtype: int
-        @return: Length of dataset.
+        @return: Length of the loader.
         """
         return len(self.instances)
 
@@ -150,9 +150,8 @@ def __getitem__(self, idx: int) -> LuxonisLoaderOutput:
         annotations.
 
         @type idx: int
-        @param idx: The (often random) integer index to retrieve a
-            sample from the dataset.
-        @rtype: LuxonisLoaderOutput
+        @param idx: The integer index of the sample to retrieve.
+        @rtype: L{LuxonisLoaderOutput}
         @return: The loader ouput consisting of the image and a
             dictionary defining its annotations.
         """