chromium/third_party/mediapipe/src/mediapipe/calculators/tensor/tensors_to_classification_calculator.proto

// Copyright 2019 The MediaPipe Authors.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//      http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

// The option proto for the TensorsToClassificationCalculator.

syntax = "proto2";

package mediapipe;

import "mediapipe/framework/calculator.proto";
import "mediapipe/util/label_map.proto";

message TensorsToClassificationCalculatorOptions {
  extend .mediapipe.CalculatorOptions {
    optional TensorsToClassificationCalculatorOptions ext = 335742638;
  }

  message LabelMap {
    message Entry {
      optional int32 id = 1;
      optional string label = 2;
    }
    repeated Entry entries = 1;
  }

  // Score threshold for preserving the class.
  optional float min_score_threshold = 1;
  // Number of highest scoring labels to output.  If top_k is not positive then
  // all labels are used.
  optional int32 top_k = 2;
  // Whether results should be sorted by descending score. By default, results
  // may or may not be sorted: setting this to true guarantees that the returned
  // results will be sorted by descending score.
  optional bool sort_by_descending_score = 9;
  // Path to a label map file for getting the actual name of class ids.
  optional string label_map_path = 3;
  // Label map. (Can be used instead of label_map_path.)
  // NOTE: either "label_map_path" or "label_items", if specified, takes
  // precedence over "label_map".
  // Deprecated: please use `label_items` instead.
  optional LabelMap label_map = 5;

  // Label items. (Can be used instead of label_map_path.)
  // NOTE: "label_map_path", if specified, takes precedence over "label_items".
  map<int64, LabelMapItem> label_items = 6;

  // Whether the input is a single float for binary classification.
  // When true, only a single float is expected in the input tensor and the
  // label map, if provided, is expected to have exactly two labels.
  // The single score(float) represent the probability of first label, and
  // 1 - score is the probabilility of the second label.
  optional bool binary_classification = 4;

  // The ids of classes that should be ignored during decoding the score for
  // each classification. If `ignore_classes` is specified, all the other
  // classes that are not in the `ignore_class` field will be considered during
  // decoding. `ignore_classes` and `allow_classes` are mutually  exclusive.
  repeated int32 ignore_classes = 7 [packed = true];
  // The ids of classes that will be allowed during decoding the score for
  // each classification. If `allow_classes` is specified, all the other classes
  // that are not in the `allow_classes` field will be completely ignored.
  // `ignore_classes` and `allow_classes` are mutually exclusive.
  repeated int32 allow_classes = 8 [packed = true];
}