add tests

sleap/io/format/deeplabcut.py

@@ -203,7 +203,7 @@ def read_frames(
                             Instance(
                                 skeleton=skeleton,
                                 points=instance_points,
-                                track=tracks.get(animal_name, None),
+                                track=tracks[animal_name],
                             )
                         )
             else:
@@ -312,22 +312,23 @@ def read(
 
                 shortname = os.path.split(data_subdir)[-1]
                 video_path = None
-                with os.scandir(videos_dir) as file_iterator:
-                    for file in file_iterator:
-                        if not file.is_file():
-                            continue
-                        if os.path.splitext(file.name)[0] != shortname:
-                            continue
-                        video_path = os.path.join(videos_dir, file.name)
-                        break
+                if os.path.exists(videos_dir):
+                    with os.scandir(videos_dir) as file_iterator:
+                        for file in file_iterator:
+                            if not file.is_file():
+                                continue
+                            if os.path.splitext(file.name)[0] != shortname:
+                                continue
+                            video_path = os.path.join(videos_dir, file.name)
+                            break
 
                 if video_path is not None and os.path.exists(video_path):
                     video = Video.from_filename(video_path)
                 else:
                     # When no video is found, the individual frame images
                     # stored in the labeled data subdir will be used.
                     if video_path is None:
-                        video_path = os.path.join(videos_dir, f"{shortname}.[EXT]")
+                        video_path = os.path.join(videos_dir, f"{shortname}.mp4")
                     print(
                         f"Unable to find {video_path} so using individual frame images."
                     )

tests/data/dlc/labeled-data/video/CollectedData_LM.csv

@@ -1,8 +1,8 @@
-scorer,,,LM,LM,LM,LM,LM,LM,LM,LM,LM,LM,LM,LM
-individuals,,,individual1,individual1,individual1,individual1,individual1,individual1,individual2,individual2,individual2,individual2,individual2,individual2
-bodyparts,,,A,A,B,B,C,C,A,A,B,B,C,C
-coords,,,x,y,x,y,x,y,x,y,x,y,x,y
-labeled-data,video,img000.png,0,1,2,3,4,5,6,7,8,9,10,11
-labeled-data,video,img001.png,12,13,,,15,16,17,18,,,20,21
+scorer,,,Scorer,Scorer,Scorer,Scorer,Scorer,Scorer,Scorer,Scorer,Scorer,Scorer,Scorer,Scorer,Scorer,Scorer,Scorer,Scorer
+individuals,,,Animal1,Animal1,Animal1,Animal1,Animal1,Animal1,Animal2,Animal2,Animal2,Animal2,Animal2,Animal2,single,single,single,single
+bodyparts,,,A,A,B,B,C,C,A,A,B,B,C,C,D,D,E,E
+coords,,,x,y,x,y,x,y,x,y,x,y,x,y,x,y,x,y
+labeled-data,video,img000.png,0,1,2,3,4,5,6,7,8,9,10,11,,,,
+labeled-data,video,img001.png,12,13,,,15,16,17,18,,,20,21,22,23,24,25
 labeled-data,video,img002.png,,,,,,,,,,,,
-labeled-data,video,img003.png,22,23,24,25,26,27,,,,,,
+labeled-data,video,img003.png,26,27,28,29,30,31,,,,,,,32,33,34,35

tests/data/dlc/madlc_230_config.yaml

@@ -1,12 +1,12 @@
     # Project definitions (do not edit)
-Task: madlc_2.3.0
+Task: maudlc_2.3.0
 scorer: LM
 date: Mar1
 multianimalproject: true
 identity: false
 
     # Project path (change when moving around)
-project_path: D:\social-leap-estimates-animal-poses\pull-requests\sleap\tests\data\dlc\madlc_testdata_v3
+project_path: D:\social-leap-estimates-animal-poses\pull-requests\sleap\tests\data\dlc\maudlc_testdata_v3
 
     # Annotation data set configuration (and individual video cropping parameters)
 video_sets:
@@ -16,7 +16,9 @@ individuals:
 - individual1
 - individual2
 - individual3
-uniquebodyparts: []
+uniquebodyparts:
+- D
+- E
 multianimalbodyparts:
 - A
 - B

tests/io/test_formats.py

@@ -198,7 +198,6 @@ def test_matching_adaptor(centered_pair_predictions_hdf5_path):
     [
         "tests/data/dlc/labeled-data/video/madlc_testdata.csv",
         "tests/data/dlc/labeled-data/video/madlc_testdata_v2.csv",
-        "tests/data/dlc/madlc_230_config.yaml",
     ],
 )
 def test_madlc(test_data):
@@ -237,7 +236,7 @@ def test_madlc(test_data):
     [
         "tests/data/dlc/labeled-data/video/maudlc_testdata.csv",
         "tests/data/dlc/labeled-data/video/maudlc_testdata_v2.csv",
-        "tests/data/dlc/maudlc_230_config.yaml",
+        "tests/data/dlc/madlc_230_config.yaml",
     ],
 )
 def test_maudlc(test_data):
@@ -288,14 +287,14 @@ def test_maudlc(test_data):
         [[26, 27], [28, 29], [30, 31], [np.nan, np.nan], [np.nan, np.nan]],
     )
     assert_array_equal(
-        labels[2][0].numpy(),
+        labels[2][1].numpy(),
         [[np.nan, np.nan], [np.nan, np.nan], [np.nan, np.nan], [32, 33], [34, 35]],
     )
     assert labels[2].frame_idx == 3
 
     # Assert tracks are correct
     assert len(labels.tracks) == 3
-    assert set(t.name for t in labels.tracks) == set(["Animal1", "Animal1", "single"])
+    assert sorted([t.name for t in labels.tracks]) == sorted(["Animal1", "Animal2", "single"])
     for t in labels.tracks:
         if t.name == "single":
             assert t.spawned_on == 1