syntax = "proto2"; | |
package object_detection.protos; | |
import "object_detection/protos/image_resizer.proto"; | |
// Configuration proto for defining input readers that generate Object Detection | |
// Examples from input sources. Input readers are expected to generate a | |
// dictionary of tensors, with the following fields populated: | |
// | |
// 'image': an [image_height, image_width, channels] image tensor that detection | |
// will be run on. | |
// 'groundtruth_classes': a [num_boxes] int32 tensor storing the class | |
// labels of detected boxes in the image. | |
// 'groundtruth_boxes': a [num_boxes, 4] float tensor storing the coordinates of | |
// detected boxes in the image. | |
// 'groundtruth_instance_masks': (Optional), a [num_boxes, image_height, | |
// image_width] float tensor storing binary mask of the objects in boxes. | |
// Instance mask format. Note that PNG masks are much more space efficient. | |
enum InstanceMaskType { | |
DEFAULT = 0; // Default implementation, currently NUMERICAL_MASKS | |
NUMERICAL_MASKS = 1; // [num_masks, H, W] float32 binary masks. | |
PNG_MASKS = 2; // Encoded PNG masks. | |
} | |
// Input type format: whether inputs are TfExamples or TfSequenceExamples. | |
enum InputType { | |
INPUT_DEFAULT = 0; // Default implementation, currently TF_EXAMPLE | |
TF_EXAMPLE = 1; // TfExample input | |
TF_SEQUENCE_EXAMPLE = 2; // TfSequenceExample Input | |
} | |
// Next id: 31 | |
message InputReader { | |
// Name of input reader. Typically used to describe the dataset that is read | |
// by this input reader. | |
optional string name = 23 [default = ""]; | |
// Path to StringIntLabelMap pbtxt file specifying the mapping from string | |
// labels to integer ids. | |
optional string label_map_path = 1 [default = ""]; | |
// Whether data should be processed in the order they are read in, or | |
// shuffled randomly. | |
optional bool shuffle = 2 [default = true]; | |
// Buffer size to be used when shuffling. | |
optional uint32 shuffle_buffer_size = 11 [default = 2048]; | |
// Buffer size to be used when shuffling file names. | |
optional uint32 filenames_shuffle_buffer_size = 12 [default = 100]; | |
// The number of times a data source is read. If set to zero, the data source | |
// will be reused indefinitely. | |
optional uint32 num_epochs = 5 [default = 0]; | |
// Integer representing how often an example should be sampled. To feed | |
// only 1/3 of your data into your model, set `sample_1_of_n_examples` to 3. | |
// This is particularly useful for evaluation, where you might not prefer to | |
// evaluate all of your samples. | |
optional uint32 sample_1_of_n_examples = 22 [default = 1]; | |
// Number of file shards to read in parallel. | |
optional uint32 num_readers = 6 [default = 64]; | |
// Number of batches to produce in parallel. If this is run on a 2x2 TPU set | |
// this to 8. | |
optional uint32 num_parallel_batches = 19 [default = 8]; | |
// Number of batches to prefetch. Prefetch decouples input pipeline and | |
// model so they can be pipelined resulting in higher throughput. Set this | |
// to a small constant and increment linearly until the improvements become | |
// marginal or you exceed your cpu memory budget. Setting this to -1, | |
// automatically tunes this value for you. | |
optional int32 num_prefetch_batches = 20 [default = 2]; | |
// Maximum number of records to keep in reader queue. | |
optional uint32 queue_capacity = 3 [default = 2000, deprecated = true]; | |
// Minimum number of records to keep in reader queue. A large value is needed | |
// to generate a good random shuffle. | |
optional uint32 min_after_dequeue = 4 [default = 1000, deprecated = true]; | |
// Number of records to read from each reader at once. | |
optional uint32 read_block_length = 15 [default = 32]; | |
// Number of decoded records to prefetch before batching. | |
optional uint32 prefetch_size = 13 [default = 512, deprecated = true]; | |
// Number of parallel decode ops to apply. | |
optional uint32 num_parallel_map_calls = 14 [default = 64, deprecated = true]; | |
// If positive, TfExampleDecoder will try to decode rasters of additional | |
// channels from tf.Examples. | |
optional int32 num_additional_channels = 18 [default = 0]; | |
// Number of groundtruth keypoints per object. | |
optional uint32 num_keypoints = 16 [default = 0]; | |
// Keypoint weights. These weights can be used to apply per-keypoint loss | |
// multipliers. The size of this field should agree with `num_keypoints`. | |
repeated float keypoint_type_weight = 26; | |
// Maximum number of boxes to pad to during training / evaluation. | |
// Set this to at least the maximum amount of boxes in the input data, | |
// otherwise some groundtruth boxes may be clipped. | |
optional int32 max_number_of_boxes = 21 [default = 100]; | |
// Whether to load multiclass scores from the dataset. | |
optional bool load_multiclass_scores = 24 [default = false]; | |
// Whether to load context features from the dataset. | |
optional bool load_context_features = 25 [default = false]; | |
// Whether to load groundtruth instance masks. | |
optional bool load_instance_masks = 7 [default = false]; | |
// Type of instance mask. | |
optional InstanceMaskType mask_type = 10 [default = NUMERICAL_MASKS]; | |
// Whether to use the display name when decoding examples. This is only used | |
// when mapping class text strings to integers. | |
optional bool use_display_name = 17 [default = false]; | |
// Whether to include the source_id string in the input features. | |
optional bool include_source_id = 27 [default = false]; | |
// Whether input data type is tf.Examples or tf.SequenceExamples | |
optional InputType input_type = 30 [default = TF_EXAMPLE]; | |
oneof input_reader { | |
TFRecordInputReader tf_record_input_reader = 8; | |
ExternalInputReader external_input_reader = 9; | |
} | |
// Expand labels to ancestors or descendants in the hierarchy for | |
// for positive and negative labels, respectively. | |
optional bool expand_labels_hierarchy = 29 [default = false]; | |
} | |
// An input reader that reads TF Example or TF Sequence Example protos from | |
// local TFRecord files. | |
message TFRecordInputReader { | |
// Path(s) to `TFRecordFile`s. | |
repeated string input_path = 1; | |
} | |
// An externally defined input reader. Users may define an extension to this | |
// proto to interface their own input readers. | |
message ExternalInputReader { | |
extensions 1 to 999; | |
} | |