/* Copyright 2022 The MediaPipe Authors. All Rights Reserved.

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.tasks.vision.hand_landmarker.proto;

import "mediapipe/framework/calculator.proto";
import "mediapipe/tasks/cc/core/proto/base_options.proto";

option java_package = "com.google.mediapipe.tasks.vision.handlandmarker.proto";
option java_outer_classname = "HandLandmarksDetectorGraphOptionsProto";

message HandLandmarksDetectorGraphOptions {
  extend mediapipe.CalculatorOptions {
    optional HandLandmarksDetectorGraphOptions ext = 474472470;
  }
  // Base options for configuring MediaPipe Tasks, such as specifying the TfLite
  // model file with metadata, accelerator options, etc.
  optional core.proto.BaseOptions base_options = 1;

  // Minimum confidence value ([0.0, 1.0]) for hand presence score to be
  // considered successfully detecting a hand in the image.
  optional float min_detection_confidence = 2 [default = 0.5];
}
