def _create_image_with_prefix(name, prefix):
"""Create multiple accessors for image based data."""
msu.create_bytes_context_feature(name + "_format",
IMAGE_FORMAT_KEY,
prefix=prefix,
module_dict=globals())
msu.create_bytes_context_feature(name + "_colorspace",
IMAGE_COLORSPACE_KEY,
prefix=prefix,
module_dict=globals())
msu.create_int_context_feature(name + "_channels",
IMAGE_CHANNELS_KEY,
prefix=prefix,
module_dict=globals())
msu.create_int_context_feature(name + "_height",
IMAGE_HEIGHT_KEY,
prefix=prefix,
module_dict=globals())
msu.create_int_context_feature(name + "_width",
IMAGE_WIDTH_KEY,
prefix=prefix,
module_dict=globals())
msu.create_bytes_feature_list(name + "_encoded",
IMAGE_ENCODED_KEY,
prefix=prefix,
module_dict=globals())
msu.create_float_context_feature(name + "_frame_rate",
IMAGE_FRAME_RATE_KEY,
prefix=prefix,
module_dict=globals())
msu.create_bytes_list_context_feature(name + "_class_label_string",
IMAGE_CLASS_LABEL_STRING_KEY,
prefix=prefix,
module_dict=globals())
msu.create_int_list_context_feature(name + "_class_label_index",
IMAGE_CLASS_LABEL_INDEX_KEY,
prefix=prefix,
module_dict=globals())
msu.create_int_list_context_feature(name + "_object_class_index",
IMAGE_OBJECT_CLASS_INDEX_KEY,
prefix=prefix,
module_dict=globals())
msu.create_bytes_context_feature(name + "_data_path",
IMAGE_DATA_PATH_KEY,
prefix=prefix,
module_dict=globals())
msu.create_int_feature_list(name + "_timestamp",
IMAGE_TIMESTAMP_KEY,
prefix=prefix,
module_dict=globals())
msu.create_bytes_list_feature_list(name + "_multi_encoded",
IMAGE_MULTI_ENCODED_KEY,
prefix=prefix,
module_dict=globals())
# The feature as a list of ints.
FEATURE_INTS_KEY = "feature/ints"
# The timestamp, in microseconds, of the feature.
FEATURE_TIMESTAMP_KEY = "feature/timestamp"
# It is occasionally useful to indicate that a feature applies to a given range.
# This should be used for features only and annotations should be provided as
# segments.
FEATURE_DURATION_KEY = "feature/duration"
# Encodes an optional confidence score for the generated features.
FEATURE_CONFIDENCE_KEY = "feature/confidence"
msu.create_int_list_context_feature("feature_dimensions",
FEATURE_DIMENSIONS_KEY,
module_dict=globals())
msu.create_float_context_feature("feature_rate",
FEATURE_RATE_KEY,
module_dict=globals())
msu.create_bytes_context_feature("feature_bytes_format",
FEATURE_BYTES_FORMAT_KEY,
module_dict=globals())
msu.create_float_context_feature("feature_sample_rate",
FEATURE_SAMPLE_RATE_KEY,
module_dict=globals())
msu.create_int_context_feature("feature_num_channels",
FEATURE_NUM_CHANNELS_KEY,
module_dict=globals())
msu.create_int_context_feature("feature_num_samples",
FEATURE_NUM_SAMPLES_KEY,
module_dict=globals())
msu.create_float_context_feature("feature_packet_rate",
FEATURE_PACKET_RATE_KEY,
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import tensorflow as tf
from mediapipe.util.sequence import media_sequence_util as msu
# run this code at the module level to procedurally define functions for test
# cases.
msu.create_bytes_context_feature("string_context",
"string_feature",
module_dict=msu.__dict__)
msu.create_float_context_feature("float_context",
"float_feature",
module_dict=msu.__dict__)
msu.create_int_context_feature("int64_context",
"int64_feature",
module_dict=msu.__dict__)
msu.create_bytes_list_context_feature("string_list_context",
"string_vector_feature",
module_dict=msu.__dict__)
msu.create_float_list_context_feature("float_list_context",
"float_vector_feature",
module_dict=msu.__dict__)
msu.create_int_list_context_feature("int64_list_context",
"int64_vector_feature",
module_dict=msu.__dict__)
msu.create_bytes_feature_list("string_feature_list",
"string_feature_list",