Main-Repo/SourceCode/OnGoingTasks/Bline/Demo/AutoBlineCalculationDemo/AutoBlineCalculationLib/InferNetOnnxAutoBlineSeg.cs

using System.Collections.Generic;

using AI.Common;
using AI.Common.InferenceNetworks;
using Microsoft.ML.OnnxRuntime;

namespace AutoBlineCalculationLib
{
    public class InferNetOnnxAutoBlineSeg : InferNetOnnxSemanticSegBasic
    {

        #region override
        /// <summary>
        /// 哈希值
        /// </summary>
        public override string HashCode => "e4cb7203d35e5a42fc313ba37ea112ab";

        /// <summary>
        /// 网络名
        /// </summary>
        public override string NetworkName => "BlineSegment.emd";

        /// <summary>
        /// 复制
        /// </summary>
        /// <param name="cloneMethod"></param>
        /// <returns></returns>
        public override IInferenceNetwork Clone(EnumCloneMethod cloneMethod)
        {
            if (!_modelLoaded)
            {
                return new InferNetOnnxAutoBlineSeg();
            }

            return new InferNetOnnxAutoBlineSeg(_trainedModel, _sessionOption);
        }
        #endregion

        #region constructor
        public InferNetOnnxAutoBlineSeg()
        {
            ModelParamsAssign();
            ConstructIntermediateVariables();
        }

        public InferNetOnnxAutoBlineSeg(byte[] trainedModel, SessionOptions sessionOption)
        {
            ModelParamsAssign();
            ConstructIntermediateVariables();
            ConstructClonedModelRelatedVariables(trainedModel, sessionOption);
        }

        #endregion

        #region private
        private void ModelParamsAssign()
        {
            _inputVariableName = "input.1";
            _inputAxisOrder = EnumAxisOrder.CHW;
            _modelInputH = 256;
            _modelInputW = 256;
            _modelInputC = 3;
            _outputVariableName = "575";
            _outputAxisOrder = EnumAxisOrder.CHW;
            _modelOutputC = 5;
            _modelOutputH = 256;
            _modelOutputW = 256;
            _resizeMode = EnumResizeMode.Warp;
            _meanValueType = EnumMeanValueType.None;
            _scaleType = EnumScaleValueType.ConstantScale;
            _scaleR = 1.0f;
            _scaleG = 1.0f;
            _scaleB = 1.0f;
            _normType = EnumNormalizationType.None;
            _reverseInputChannels = true;
            _segPostProcessParam = new Dictionary<int, SemanticSegmentationPostProcessParams>
            {
                // 1为胸膜线；2为B线；3为A线；4为肺实变
                { 1, new SemanticSegmentationPostProcessParams( new List<LesionAreaSelectInfo>(){new LesionAreaSelectInfo(EnumLesionAreaThresholdType.PixelInMask, 20, -1)}, 20)},
                { 2, new SemanticSegmentationPostProcessParams( new List<LesionAreaSelectInfo>(){new LesionAreaSelectInfo(EnumLesionAreaThresholdType.PixelInMask, 20, -1)}, 20)},
                { 3, new SemanticSegmentationPostProcessParams( new List<LesionAreaSelectInfo>(){new LesionAreaSelectInfo(EnumLesionAreaThresholdType.PixelInMask, 20, -1)}, 20)},
                { 4, new SemanticSegmentationPostProcessParams( new List<LesionAreaSelectInfo>(){new LesionAreaSelectInfo(EnumLesionAreaThresholdType.PixelInMask, 20, -1)}, 20)},
            };
        }
        #endregion

    }
}