// 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 TfLiteTensorsToClassificationCalculator.
syntax = "proto2";
package mediapipe;
import "mediapipe/framework/calculator.proto";
message TfLiteTensorsToClassificationCalculatorOptions {
extend .mediapipe.CalculatorOptions {
optional TfLiteTensorsToClassificationCalculatorOptions ext = 266399463;
}
// 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;
// Path to a label map file for getting the actual name of class ids.
optional string label_map_path = 3;
// 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;
}