Fix commits that were added due to merge conflict

Author: Kevin Kim

tests/integration/annotation_import/conftest.py

@@ -468,16 +468,6 @@ def dataset_pdf_entity(client, rand_gen, document_data_row):
     dataset.delete()
 
 
-@pytest.fixture
-def video_data(client, rand_gen, video_data_row):
-    dataset = client.create_dataset(name=rand_gen(str))
-    data_row_ids = []
-    data_row = dataset.create_data_row(video_data_row)
-    data_row_ids.append(data_row.uid)
-    yield dataset, data_row_ids
-    dataset.delete()
-
-
 @pytest.fixture
 def dataset_conversation_entity(client, rand_gen, conversation_entity_data_row):
     dataset = client.create_dataset(name=rand_gen(str))

tests/integration/annotation_import/test_data_types.py

@@ -68,106 +68,6 @@ def get_annotation_comparison_dicts_from_labels(labels):
     return labels_ndjson
 
 
-def get_annotation_comparison_dicts_from_export(export_result, data_row_id,
-                                                project_id):
-    exported_data_row = [
-        dr for dr in export_result if dr['data_row']['id'] == data_row_id
-    ][0]
-    exported_label = exported_data_row['projects'][project_id]['labels'][0]
-    exported_annotations = exported_label['annotations']
-    converted_annotations = []
-    if exported_label['label_kind'] == 'Video':
-        frames = []
-        instances = []
-        for frame_id, frame in exported_annotations['frames'].items():
-            frames.append({'index': int(frame_id)})
-            for object in frame['objects'].values():
-                instances.append({'name': object['name']})
-        converted_annotations.append(
-            {'masks': {
-                'frames': frames,
-                'instances': instances,
-            }})
-    else:
-        exported_annotations = list(
-            itertools.chain(*exported_annotations.values()))
-        for annotation in exported_annotations:
-            if annotation['name'] == 'radio':
-                converted_annotations.append({
-                    'name': annotation['name'],
-                    'answer': {
-                        'name': annotation['radio_answer']['name']
-                    }
-                })
-            elif annotation['name'] == 'checklist':
-                converted_annotations.append({
-                    'name':
-                        annotation['name'],
-                    'answer': [{
-                        'name': answer['name']
-                    } for answer in annotation['checklist_answers']]
-                })
-            elif annotation['name'] == 'text':
-                converted_annotations.append({
-                    'name': annotation['name'],
-                    'answer': annotation['text_answer']['content']
-                })
-    return converted_annotations
-
-radio_annotation = lb_types.ClassificationAnnotation(
-    name="radio",
-    value=lb_types.Radio(answer=lb_types.ClassificationAnswer(
-        name="second_radio_answer")))
-checklist_annotation = lb_types.ClassificationAnnotation(
-    name="checklist",
-    value=lb_types.Checklist(answer=[
-        lb_types.ClassificationAnswer(name="option1"),
-        lb_types.ClassificationAnswer(name="option2")
-    ]))
-text_annotation = lb_types.ClassificationAnnotation(
-    name="text", value=lb_types.Text(answer="sample text"))
-
-video_mask_annotation = lb_types.VideoMaskAnnotation(frames=[
-    lb_types.MaskFrame(
-        index=10,
-        instance_uri=
-        "https://storage.googleapis.com/labelbox-datasets/video-sample-data/mask_example.png"
-    )
-],
-                                                     instances=[
-                                                         lb_types.MaskInstance(
-                                                             color_rgb=(255,
-                                                                        255,
-                                                                        255),
-                                                             name=
-                                                             "segmentation_mask"
-                                                         )
-                                                     ])
-
-test_params = [[
-    'html', lb_types.HTMLData,
-    [radio_annotation, checklist_annotation, text_annotation]
-],
-               [
-                   'audio', lb_types.AudioData,
-                   [radio_annotation, checklist_annotation, text_annotation]
-               ], ['video', lb_types.VideoData, [video_mask_annotation]]]
-
-
-def get_annotation_comparison_dicts_from_labels(labels):
-    labels_ndjson = list(NDJsonConverter.serialize(labels))
-    for annotation in labels_ndjson:
-        annotation.pop('uuid')
-        annotation.pop('dataRow')
-
-        if 'masks' in annotation:
-            for frame in annotation['masks']['frames']:
-                frame.pop('instanceURI')
-            for instance in annotation['masks']['instances']:
-                instance.pop('colorRGB')
-    return labels_ndjson
-
-
 def get_annotation_comparison_dicts_from_export(export_result, data_row_id,
                                                 project_id):
     exported_data_row = [