Passing attributes through during label coercions

fiftyone/utils/data/exporters.py

@@ -741,6 +741,7 @@ def _classification_to_detections(label):
                 label=label.label,
                 bounding_box=[0, 0, 1, 1],
                 confidence=label.confidence,
+                **dict(label.iter_attributes()),
             )
         ]
     )

fiftyone/utils/data/parsers.py

@@ -915,8 +915,12 @@ class ImageClassificationSampleParser(LabeledImageTupleSampleParser):
                     {
                         "label": <label-or-target>,
                         "confidence": <confidence>,
+                        "attributes": <optional-attributes>,
                     }
 
+            -   a :class:`fiftyone.core.labels.Classification` or
+                :class:`fiftyone.core.labels.Classifications` instance
+
     Args:
         classes (None): an optional list of class label strings. If provided,
             it is assumed that ``target`` contains class ID that should be
@@ -947,6 +951,9 @@ def _parse_label(self, target):
         if target is None:
             return None
 
+        if isinstance(target, (fol.Classification, fol.Classifications)):
+            return target
+
         is_list = isinstance(target, (list, tuple))
 
         if not is_list:
@@ -989,36 +996,38 @@ class ImageDetectionSampleParser(LabeledImageTupleSampleParser):
         - ``image_or_path`` is either an image that can be converted to numpy
           format via ``np.asarray()`` or the path to an image on disk
 
-        - ``detections_or_path`` is either a list of detections in the
-          following format::
-
-            [
-                {
-                    "<label_field>": <label-or-target>,
-                    "<bounding_box_field>": [
-                        <top-left-x>, <top-left-y>, <width>, <height>
-                    ],
-                    "<confidence_field>": <optional-confidence>,
-                    "<attributes_field>": {
-                        <optional-name>: <optional-value>,
+        - ``detections_or_path`` can be any of the following:
+
+            -   None, for unlabeled images
+            -   a list of detections in the following format::
+
+                    [
+                        {
+                            "<label_field>": <label-or-target>,
+                            "<bounding_box_field>": [
+                                <top-left-x>, <top-left-y>, <width>, <height>
+                            ],
+                            "<confidence_field>": <optional-confidence>,
+                            "<attributes_field>": {
+                                <optional-name>: <optional-value>,
+                                ...
+                            }
+                        },
                         ...
-                    }
-                },
-                ...
-            ]
+                    ]
 
-          or the path to such a file on disk. For unlabeled images,
-          ``detections_or_path`` can be ``None``.
+                In the above, ``label-or-target`` is either a class ID
+                (if ``classes`` is provided) or a label string, and the bounding
+                box coordinates can either be relative coordinates in ``[0, 1]``
+                (if ``normalized == True``) or absolute pixels coordinates
+                (if ``normalized == False``). The confidence and attributes
+                fields are optional for each sample.
 
-          In the above, ``label-or-target`` is either a class ID
-          (if ``classes`` is provided) or a label string, and the bounding box
-          coordinates can either be relative coordinates in ``[0, 1]``
-          (if ``normalized == True``) or absolute pixels coordinates
-          (if ``normalized == False``). The confidence and attributes fields
-          are optional for each sample.
+                The input field names can be configured as necessary when
+                instantiating the parser.
 
-          The input field names can be configured as necessary when
-          instantiating the parser.
+            -   the path on disk to a file in the above format
+            -   a :class:`fiftyone.core.labels.Detections` instance
 
     Args:
         label_field ("label"): the name of the object label field in the
@@ -1079,6 +1088,9 @@ def _parse_label(self, target, img=None):
         if target is None:
             return None
 
+        if isinstance(target, fol.Detections):
+            return target
+
         if etau.is_str(target):
             target = etas.read_json(target)
 
@@ -1257,6 +1269,9 @@ def get_label(self):
         if labels is None:
             return None
 
+        if isinstance(labels, fol.TemporalDetections):
+            return labels
+
         detections = []
         for label_dict in labels:
             label = label_dict["label"]

fiftyone/utils/patches.py

@@ -80,7 +80,7 @@ def __iter__(self):
                         alpha=self.alpha,
                     )
                     if self.include_labels:
-                        yield patch, detection.label
+                        yield patch, _to_classification(detection)
                     else:
                         yield patch
 
@@ -167,3 +167,14 @@ def _load_image(image_path, force_rgb=False):
     # pylint: disable=no-member
     flag = cv2.IMREAD_COLOR if force_rgb else cv2.IMREAD_UNCHANGED
     return etai.read(image_path, flag=flag)
+
+
+def _to_classification(label):
+    if label is None:
+        return label
+
+    return fol.Classification(
+        label=label.label,
+        confidence=label.confidence,
+        **dict(label.iter_attributes()),
+    )