// 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.
syntax = "proto2";
package mediapipe;
import "mediapipe/framework/calculator.proto";
message TfLiteTensorsToSegmentationCalculatorOptions {
extend mediapipe.CalculatorOptions {
optional TfLiteTensorsToSegmentationCalculatorOptions ext = 252526026;
}
// Dimensions of input segmentation tensor to process.
optional int32 tensor_width = 1; // required
optional int32 tensor_height = 2; // required
optional int32 tensor_channels = 3; // required
// How much to use previous mask when computing current one; range [0-1].
// This is a tradeoff between responsiveness (0.0) and accuracy (1.0).
optional float combine_with_previous_ratio = 4 [default = 1.0];
// Model specific: Channel to use for processing tensor.
optional int32 output_layer_index = 5 [default = 1];
// Flip result image mask along y-axis.
optional bool flip_vertically = 6;
}