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",