47 lines
1.9 KiB
Protocol Buffer
47 lines
1.9 KiB
Protocol Buffer
/* Copyright 2022 The MediaPipe Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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syntax = "proto2";
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package mediapipe.tasks.components;
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import "mediapipe/calculators/tensor/tensors_to_classification_calculator.proto";
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import "mediapipe/framework/calculator.proto";
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import "mediapipe/tasks/cc/components/calculators/classification_aggregation_calculator.proto";
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import "mediapipe/tasks/cc/components/calculators/score_calibration_calculator.proto";
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message ClassificationPostprocessingOptions {
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extend mediapipe.CalculatorOptions {
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optional ClassificationPostprocessingOptions ext = 460416950;
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}
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// Optional mapping between output tensor index and corresponding score
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// calibration options.
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map<int32, ScoreCalibrationCalculatorOptions> score_calibration_options = 4;
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// Options for the TensorsToClassification calculators (one per classification
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// head) encapsulated by the ClassificationPostprocessing subgraph.
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repeated mediapipe.TensorsToClassificationCalculatorOptions
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tensors_to_classifications_options = 1;
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// Options for the ClassificationAggregationCalculator encapsulated by the
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// ClassificationPostprocessing subgraph.
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optional ClassificationAggregationCalculatorOptions
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classification_aggregation_options = 2;
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// Whether output tensors are quantized (kTfLiteUint8) or not (kFloat32).
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optional bool has_quantized_outputs = 3;
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}
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