def _generate_metadata(self,
key,
download_output,
video_path_format_string=None):
"""For each row in the annotation CSV, generates the corresponding metadata.
Args:
key: which split to process.
download_output: the tuple output of _download_data containing
- annotations_files: dict of keys to CSV annotation paths.
- label_map: dict mapping from label strings to numeric indices.
video_path_format_string: The format string for the path to local files.
Yields:
Each tf.SequenceExample of metadata, ready to pass to MediaPipe.
"""
annotations_files, label_map = download_output
with open(annotations_files[key], "r") as annotations:
reader = csv.reader(annotations)
for i, csv_row in enumerate(reader):
if i == 0: # the first row is the header
continue
# rename the row with a constitent set of names.
if len(csv_row) == 5:
row = dict(
list(
zip([
"label_name", "video", "start", "end", "split"
], csv_row)))
else:
row = dict(
list(zip(["video", "start", "end", "split"], csv_row)))
metadata = tf.train.SequenceExample()
ms.set_example_id(bytes23(row["video"] + "_" + row["start"]),
metadata)
ms.set_clip_media_id(bytes23(row["video"]), metadata)
ms.set_clip_alternative_media_id(bytes23(row["split"]),
metadata)
if video_path_format_string:
filepath = video_path_format_string.format(**row)
ms.set_clip_data_path(bytes23(filepath), metadata)
assert row["start"].isdigit(), "Invalid row: %s" % str(row)
assert row["end"].isdigit(), "Invalid row: %s" % str(row)
if "label_name" in row:
ms.set_clip_label_string([bytes23(row["label_name"])],
metadata)
if label_map:
ms.set_clip_label_index([label_map[row["label_name"]]],
metadata)
yield metadata
def test_expected_functions_are_defined(self):
# The code from media_sequence_util is already tested, but this test ensures
# that we actually generate the expected methods. We only test one per
# feature and the only test is to not crash with undefined attributes. By
# passing in a value, we also ensure that the types are correct because the
# underlying code crashes with a type mismatch.
example = tf.train.SequenceExample()
# context
ms.set_example_id(b"string", example)
ms.set_example_dataset_name(b"string", example)
ms.set_clip_media_id(b"string", example)
ms.set_clip_alternative_media_id(b"string", example)
ms.set_clip_encoded_media_bytes(b"string", example)
ms.set_clip_encoded_media_start_timestamp(47, example)
ms.set_clip_data_path(b"string", example)
ms.set_clip_start_timestamp(47, example)
ms.set_clip_end_timestamp(47, example)
ms.set_clip_label_string((b"string", b"test"), example)
ms.set_clip_label_index((47, 49), example)
ms.set_clip_label_confidence((0.47, 0.49), example)
ms.set_segment_start_timestamp((47, 49), example)
ms.set_segment_start_index((47, 49), example)
ms.set_segment_end_timestamp((47, 49), example)
ms.set_segment_end_index((47, 49), example)
ms.set_segment_label_index((47, 49), example)
ms.set_segment_label_string((b"test", b"strings"), example)
ms.set_segment_label_confidence((0.47, 0.49), example)
ms.set_image_format(b"test", example)
ms.set_image_channels(47, example)
ms.set_image_colorspace(b"test", example)
ms.set_image_height(47, example)
ms.set_image_width(47, example)
ms.set_image_frame_rate(0.47, example)
ms.set_image_data_path(b"test", example)
ms.set_forward_flow_format(b"test", example)
ms.set_forward_flow_channels(47, example)
ms.set_forward_flow_colorspace(b"test", example)
ms.set_forward_flow_height(47, example)
ms.set_forward_flow_width(47, example)
ms.set_forward_flow_frame_rate(0.47, example)
ms.set_class_segmentation_format(b"test", example)
ms.set_class_segmentation_height(47, example)
ms.set_class_segmentation_width(47, example)
ms.set_class_segmentation_class_label_string((b"test", b"strings"),
example)
ms.set_class_segmentation_class_label_index((47, 49), example)
ms.set_instance_segmentation_format(b"test", example)
ms.set_instance_segmentation_height(47, example)
ms.set_instance_segmentation_width(47, example)
ms.set_instance_segmentation_object_class_index((47, 49), example)
ms.set_bbox_parts((b"HEAD", b"TOE"), example)
# feature lists
ms.add_image_encoded(b"test", example)
ms.add_image_multi_encoded([b"test", b"test"], example)
ms.add_image_timestamp(47, example)
ms.add_forward_flow_encoded(b"test", example)
ms.add_forward_flow_multi_encoded([b"test", b"test"], example)
ms.add_forward_flow_timestamp(47, example)
ms.add_bbox_ymin((0.47, 0.49), example)
ms.add_bbox_xmin((0.47, 0.49), example)
ms.add_bbox_ymax((0.47, 0.49), example)
ms.add_bbox_xmax((0.47, 0.49), example)
ms.add_bbox_point_x((0.47, 0.49), example)
ms.add_bbox_point_y((0.47, 0.49), example)
ms.add_predicted_bbox_ymin((0.47, 0.49), example)
ms.add_predicted_bbox_xmin((0.47, 0.49), example)
ms.add_predicted_bbox_ymax((0.47, 0.49), example)
ms.add_predicted_bbox_xmax((0.47, 0.49), example)
ms.add_bbox_num_regions(47, example)
ms.add_bbox_is_annotated(47, example)
ms.add_bbox_is_generated((47, 49), example)
ms.add_bbox_is_occluded((47, 49), example)
ms.add_bbox_label_index((47, 49), example)
ms.add_bbox_label_string((b"test", b"strings"), example)
ms.add_bbox_label_confidence((0.47, 0.49), example)
ms.add_bbox_class_index((47, 49), example)
ms.add_bbox_class_string((b"test", b"strings"), example)
ms.add_bbox_class_confidence((0.47, 0.49), example)
ms.add_bbox_track_index((47, 49), example)
ms.add_bbox_track_string((b"test", b"strings"), example)
ms.add_bbox_track_confidence((0.47, 0.49), example)
ms.add_bbox_timestamp(47, example)
ms.add_predicted_bbox_class_index((47, 49), example)
ms.add_predicted_bbox_class_string((b"test", b"strings"), example)
ms.add_predicted_bbox_timestamp(47, example)
ms.add_class_segmentation_encoded(b"test", example)
ms.add_class_segmentation_multi_encoded([b"test", b"test"], example)
ms.add_instance_segmentation_encoded(b"test", example)
ms.add_instance_segmentation_multi_encoded([b"test", b"test"], example)
ms.add_class_segmentation_timestamp(47, example)
ms.set_bbox_embedding_dimensions_per_region((47, 49), example)
ms.set_bbox_embedding_format(b"test", example)
ms.add_bbox_embedding_floats((0.47, 0.49), example)
ms.add_bbox_embedding_encoded((b"text", b"stings"), example)
ms.add_bbox_embedding_confidence((0.47, 0.49), example)
