Main-Repo/SourceCode/OnGoingTasks/Nerve/Demo/NerveIdentification/NerveIdentificationLib/InferNetOnnxNerveSeg.cs

using AI.Common;
using AI.Common.InferenceNetworks;
using Microsoft.ML.OnnxRuntime;
using System.Collections.Generic;

namespace NerveIdentificationLib
{
    /// <summary>
    /// 分割神经
    /// </summary>
    public class InferNetOnnxNerveSeg: InferNetOnnxSemanticSegBasic
    {
        #region override

        /// <summary>
        /// 哈希值
        /// </summary>
        public override string HashCode => "283f7ec736b2570d9a09fc79264d76f7";

        /// <summary>
        /// 网络名
        /// </summary>
        public override string NetworkName => "Nerve-ContourSeg.emd";

        /// <summary>
        /// 后处理
        /// </summary>
        /// <param name="image"></param>
        /// <returns></returns>
        public override IDetectedObject[] PostProcess(InferenceNetworkInputImage image)
        {
            // 调用基类的Process
            var results = base.PostProcess(image);
            return results;
        }

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

        #endregion

        #region constructor

        public InferNetOnnxNerveSeg()
        {
            ModelParamsAssign();
            ConstructIntermediateVariables();
        }

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

        #endregion

        #region private funcs

        private void ModelParamsAssign()
        {
            _inputVariableName = "input.1";
            _inputAxisOrder = EnumAxisOrder.CHW;
            _modelInputC = 3;
            _modelInputH = 256;
            _modelInputW = 256;
            _outputVariableName = "755";
            _outputAxisOrder = EnumAxisOrder.CHW;
            _modelOutputC = 4;
            _modelOutputH = 256;
            _modelOutputW = 256;
            _resizeMode = EnumResizeMode.Warp;
            _meanValueType = EnumMeanValueType.None;
            _scaleType = EnumScaleValueType.ConstantScale;
            _scaleR = 255;
            _scaleG = 255;
            _scaleB = 255;
            _normType = EnumNormalizationType.None;
            _reverseInputChannels = true;

            _segPostProcessParam = new Dictionary<int, SemanticSegmentationPostProcessParams>
            {
                // 神经
                { 1, new SemanticSegmentationPostProcessParams(new List<LesionAreaSelectInfo>(){new LesionAreaSelectInfo(EnumLesionAreaThresholdType.RatioInMask, 1.0f/100, 1.0f)}, 5)},
                // 动脉
                { 2, new SemanticSegmentationPostProcessParams(new List<LesionAreaSelectInfo>(){new LesionAreaSelectInfo(EnumLesionAreaThresholdType.RatioInMask, 1.0f/100, 1.0f)}, 2)},
                // 静脉
                { 3, new SemanticSegmentationPostProcessParams(new List<LesionAreaSelectInfo>(){new LesionAreaSelectInfo(EnumLesionAreaThresholdType.RatioInMask, 1.0f/100, 1.0f)}, 2)},
            };
        }

        #endregion
    }
}