added support RemoteDatasetV1 parsing and updated tests

darwin/dataset/remote_dataset.py

@@ -159,7 +159,7 @@ def split_video_annotations(self, release_name: str = "latest") -> None:
 
             frame_annotations = split_video_annotation(darwin_annotation)
             for frame_annotation in frame_annotations:
-                annotation = build_image_annotation(frame_annotation)
+                annotation = self._build_image_annotation(frame_annotation)
 
                 video_frame_annotations_path = annotations_path / annotation_file.stem
                 video_frame_annotations_path.mkdir(exist_ok=True, parents=True)
@@ -894,3 +894,6 @@ def local_images_path(self) -> Path:
     def identifier(self) -> DatasetIdentifier:
         """The ``DatasetIdentifier`` of this ``RemoteDataset``."""
         return DatasetIdentifier(team_slug=self.team, dataset_slug=self.slug)
+
+    def _build_image_annotation(self, annotation_file: AnnotationFile) -> Dict[str, Any]:
+        return build_image_annotation(annotation_file)

darwin/dataset/remote_dataset_v1.py

@@ -13,8 +13,9 @@
     UploadHandlerV1,
 )
 from darwin.dataset.utils import is_relative_to
-from darwin.datatypes import ItemId, PathLike
+from darwin.datatypes import AnnotationFile, ItemId, PathLike
 from darwin.exceptions import NotFound, ValidationError
+from darwin.exporter.formats.darwin_1_0 import build_image_annotation
 from darwin.item import DatasetItem
 from darwin.item_sorter import ItemSorter
 from darwin.utils import find_files, urljoin
@@ -457,3 +458,6 @@ def import_annotation(self, item_id: ItemId, payload: Dict[str, Any]) -> None:
         """
 
         self.client.import_annotation(item_id, payload=payload)
+
+    def _build_image_annotation(self, annotation_file: AnnotationFile) -> Dict[str, Any]:
+        return build_image_annotation(annotation_file)

darwin/dataset/remote_dataset_v2.py

@@ -22,8 +22,9 @@
     UploadHandlerV2,
 )
 from darwin.dataset.utils import is_relative_to
-from darwin.datatypes import ItemId, PathLike
+from darwin.datatypes import AnnotationFile, ItemId, PathLike
 from darwin.exceptions import NotFound, UnknownExportVersion
+from darwin.exporter.formats.darwin import build_image_annotation
 from darwin.item import DatasetItem
 from darwin.item_sorter import ItemSorter
 from darwin.utils import find_files, urljoin
@@ -478,3 +479,6 @@ def _fetch_stages(self, stage_type):
         workflow_id = workflow_ids[0]
         workflow = self.client.api_v2.get_workflow(workflow_id, team_slug=self.team)
         return (workflow_id, [stage for stage in workflow["stages"] if stage["type"] == stage_type])
+
+    def _build_image_annotation(self, annotation_file: AnnotationFile) -> Dict[str, Any]:
+        return build_image_annotation(annotation_file)

darwin/exporter/formats/darwin_1_0.py

@@ -1,5 +1,5 @@
 from pathlib import Path
-from typing import Iterable, List, Union
+from typing import Any, Dict, Iterable, List, Union
 
 import orjson as json
 
@@ -190,3 +190,74 @@ def _build_metadata(annotation_file: AnnotationFile) -> DictFreeForm:
         return {"metadata": annotation_file.slots[0].metadata}
     else:
         return {}
+
+
+def build_image_annotation(annotation_file: AnnotationFile) -> Dict[str, Any]:
+    """
+    Builds and returns a dictionary with the annotations present in the given file.
+
+    Parameters
+    ----------
+    annotation_file: dt.AnnotationFile
+        File with the image annotations to extract.
+
+    Returns
+    -------
+    Dict[str, Any]
+        A dictionary with the annotation from the given file. Has the following structure:
+
+        .. code-block:: python
+
+            {
+                "annotations": [
+                    {
+                        "annotation_type": { ... }, # annotation_data
+                        "name": "annotation class name",
+                        "bounding_box": { ... } # Optional parameter, only present if the file has a bounding box as well
+                    }
+                ],
+                "image": {
+                    "filename": "a_file_name.json",
+                    "height": 1000,
+                    "width": 2000,
+                    "url": "https://www.darwin.v7labs.com/..."
+                }
+            }
+    """
+    annotations: List[Dict[str, Any]] = []
+    for annotation in annotation_file.annotations:
+        payload = {
+            annotation.annotation_class.annotation_type: _build_annotation_data(
+                annotation
+            ),
+            "name": annotation.annotation_class.name,
+        }
+
+        if (
+            annotation.annotation_class.annotation_type == "complex_polygon"
+            or annotation.annotation_class.annotation_type == "polygon"
+        ) and "bounding_box" in annotation.data:
+            payload["bounding_box"] = annotation.data["bounding_box"]
+
+        annotations.append(payload)
+
+    return {
+        "annotations": annotations,
+        "image": {
+            "filename": annotation_file.filename,
+            "height": annotation_file.image_height,
+            "width": annotation_file.image_width,
+            "url": annotation_file.image_url,
+        },
+    }
+
+def _build_annotation_data(annotation: Annotation) -> Dict[str, Any]:
+    if annotation.annotation_class.annotation_type == "complex_polygon":
+        return {"path": annotation.data["paths"]}
+
+    if annotation.annotation_class.annotation_type == "polygon":
+        return dict(
+            filter(lambda item: item[0] != "bounding_box", annotation.data.items())
+        )
+
+    return dict(annotation.data)

tests/darwin/dataset/remote_dataset_test.py

@@ -348,8 +348,10 @@ def test_works_on_videos(
         )
         assert video_path.exists()
 
+        print(list(video_path.iterdir()))
+
         assert (video_path / "0000000.json").exists()
-        assert (video_path / "0000001.json").exists()
+        assert not (video_path / "0000001.json").exists()
         assert (video_path / "0000002.json").exists()
         assert not (video_path / "0000003.json").exists()
 
@@ -361,12 +363,6 @@ def test_works_on_videos(
                 "image": {"filename": "test_video/0000000.png", "height": 1080, "url": "frame_1.jpg", "width": 1920},
             }
 
-        with (video_path / "0000001.json").open() as f:
-            assert json.loads(f.read()) == {
-                "annotations": [],
-                "image": {"filename": "test_video/0000001.png", "height": 1080, "url": "frame_2.jpg", "width": 1920},
-            }
-
         with (video_path / "0000002.json").open() as f:
             assert json.loads(f.read()) == {
                 "annotations": [