Add tests and functionality for loading provenance data

sleap_io/io/slp.py

@@ -246,6 +246,8 @@ def read_labels(labels_path: str) -> Labels:
     instances = read_instances(
         labels_path, skeletons, tracks, points, pred_points, format_id
     )
+    metadata = read_metadata(labels_path)
+    provenance = metadata.get("provenance", dict())
 
     frames = read_hdf5_dataset(labels_path, "frames")
     labeled_frames = []
@@ -259,7 +261,11 @@ def read_labels(labels_path: str) -> Labels:
         )
 
     labels = Labels(
-        labeled_frames=labeled_frames, videos=videos, skeletons=skeletons, tracks=tracks
+        labeled_frames=labeled_frames,
+        videos=videos,
+        skeletons=skeletons,
+        tracks=tracks,
+        provenance=provenance,
     )
 
     return labels

tests/fixtures/slp.py

@@ -24,3 +24,9 @@ def slp_minimal():
 def slp_predictions():
     """A more complex example containing predicted instances from multiple tracks and a single video"""
     return "tests/data/slp/centered_pair_predictions.slp"
+
+
+@pytest.fixture
+def slp_predictions_with_provenance():
+    """The slp file generated with the collab tutorial and sleap version 1.27"""
+    return "tests/data/slp/tutorial_predictions_version_1.2.7_with_provenance.slp"

tests/io/test_slp.py

@@ -36,3 +36,10 @@ def test_read_labels(slp_typical, slp_simple_skel, slp_minimal):
 
     labels = read_labels(slp_minimal)
     assert type(labels) == Labels
+
+
+def test_load_lsp_with_provenance(slp_predictions_with_provenance):
+    labels = read_labels(slp_predictions_with_provenance)
+    provenance = labels.provenance
+    assert type(provenance) == dict
+    assert provenance["sleap_version"] == "1.2.7"