运用AI搭建中间服务层（四）

MiddlewareService文件夹

在这个文件夹中，我们需要添加以下文件：

• 名人服务.cs

• 名人服务.cs

• 名人结果.cs

• ILandmarkService.cs

• 地标服务 .cs

• 地标结果 .cs

ICelebrityService.cs – 包装多个串行的认知服务来实现名人识别的中间服务层的接口定义，需要依赖注入

using System.Threading.Tasks;

namespace CognitiveMiddlewareService.MiddlewareService
{
    public interface ICelebrityService
    {
        Task Do(byte[] imgData);
    }
}

CelebrityService.cs – 包装多个串行的认知服务来实现名人识别中间服务层的逻辑代码

using CognitiveMiddlewareService.CognitiveServices;
using Newtonsoft.Json;
using System.Threading.Tasks;

namespace CognitiveMiddlewareService.MiddlewareService
{
    public class CelebrityService : ICelebrityService
    {
        private readonly IVisionService visionService;
        private readonly IEntitySearchService entityService;

        public CelebrityService(IVisionService vs, IEntitySearchService ess)
        {
            this.visionService = vs;
            this.entityService = ess;
        }

        public async Task Do(byte[] imgData)
        {
            // get original recognized result
            var stream = Helper.GetStream(imgData);
            Celebrity celebrity = await this.visionService.RecognizeCelebrityAsync(stream);
            if (celebrity != null)
            {
                // get entity search result
                string entityName = celebrity.name;
                string jsonResult = await this.entityService.SearchEntityAsync(entityName);
                EntityResult er = JsonConvert.DeserializeObject(jsonResult);
                if (er?.entities?.value.Length > 0)
                {
                    // isolation layer: decouple data structure then return abstract result
                    CelebrityResult cr = new CelebrityResult()
                    {
                        Name = er.entities.value[0].name,
                        Description = er.entities.value[0].description,
                        Url = er.entities.value[0].url,
                        ThumbnailUrl = er.entities.value[0].image.thumbnailUrl,
                        Confidence = celebrity.confidence
                    };
                    return cr;
                }
            }
            return null;
        }
    }
}

小提示：上面的代码中，用CelebrityResult接管了实体搜索结果和名人识别结果的部分有效字段，以达到解耦/隔离的作用，后面的代码只关心CelebrityResult如何定义的即可。

CelebrityResult.cs – 抽象出来的名人识别服务的返回结果

namespace CognitiveMiddlewareService.MiddlewareService
{
    public class CelebrityResult
    {
        public string Name { get; set; }
        public double Confidence { get; set; }
        public string Url { get; set; }
        public string Description { get; set; }
        public string ThumbnailUrl { get; set; }
    }
}

ILandmarkService.cs – 包装多个串行的认知服务来实现地标识别的中间服务层的接口定义，需要依赖注入

using CognitiveMiddlewareService.CognitiveServices;
using System;
using System.Collections.Generic;
using System.Linq;
using System.Threading.Tasks;

namespace CognitiveMiddlewareService.MiddlewareService
{
    public interface ILandmarkService
    {
        Task Do(byte[] imgData);
    }
}

LandmarkService.cs – 包装多个串行的认知服务来实现地标识别的中间服务层的逻辑代码

using CognitiveMiddlewareService.CognitiveServices;
using Newtonsoft.Json;
using System;
using System.Collections.Generic;
using System.Linq;
using System.Threading.Tasks;

namespace CognitiveMiddlewareService.MiddlewareService
{
    public class LandmarkService : ILandmarkService
    {
        private readonly IVisionService visionService;
        private readonly IEntitySearchService entityService;

        public LandmarkService(IVisionService vs, IEntitySearchService ess)
        {
            this.visionService = vs;
            this.entityService = ess;
        }

        public async Task Do(byte[] imgData)
        {
            // get original recognized result
            var streamLandmark = Helper.GetStream(imgData);
            Landmark landmark = await this.visionService.RecognizeLandmarkAsync(streamLandmark);
            if (landmark != null)
            {
                // get entity search result
                string entityName = landmark.name;
                string jsonResult = await this.entityService.SearchEntityAsync(entityName);
                EntityResult er = JsonConvert.DeserializeObject(jsonResult);
                // isolation layer: decouple data structure then return abstract result
                LandmarkResult lr = new LandmarkResult()
                {
                    Name = er.entities.value[0].name,
                    Description = er.entities.value[0].description,
                    Url = er.entities.value[0].url,
                    ThumbnailUrl = er.entities.value[0].image.thumbnailUrl,
                    Confidence = landmark.confidence
                };
                return lr;
            }
            return null;
        }
    }
}

小提示：上面的代码中，用LandmarkResult接管了实体搜索结果和地标识别结果的部分有效字段，以达到解耦/隔离的作用，后面的代码只关心LandmarkResult如何定义的即可。

LandmarkResult.cs – 抽象出来的地标识别服务的返回结果

namespace CognitiveMiddlewareService.MiddlewareService
{
    public class LandmarkResult
    {
        public string Name { get; set; }
        public double Confidence { get; set; }
        public string Url { get; set; }
        public string Description { get; set; }
        public string ThumbnailUrl { get; set; }
    }
}

Processors文件夹

在这个文件夹中，我们需要添加以下文件：

• IProcessService.cs

• 进程服务 .cs

• 聚合结果.cs

IProcessService.cs – 任务调度层服务的接口定义，需要依赖注入

using System.Threading.Tasks;

namespace CognitiveMiddlewareService.Processors
{
    public interface IProcessService
    {
        Task Process(byte[] imgData);
    }
}

ProcessService.cs – 任务调度层服务的逻辑代码

using CognitiveMiddlewareService.MiddlewareService;
using System.Collections.Generic;
using System.Threading.Tasks;

namespace CognitiveMiddlewareService.Processors
{
    public class ProcessService : IProcessService
    {
        private readonly ILandmarkService landmarkService;
        private readonly ICelebrityService celebrityService;

        public ProcessService(ILandmarkService ls, ICelebrityService cs)
        {
            this.landmarkService = ls;
            this.celebrityService = cs;
        }

        public async Task Process(byte[] imgData)
        {
            // preprocess
            // todo: create screening image classifier to get a rough category, then decide call which service

            // task dispatcher: parallelized run 'Do'
            // todo: put this logic into Dispatcher service
            List listTask = new List();

            var taskLandmark = this.landmarkService.Do(imgData);
            listTask.Add(taskLandmark);
            var taskCelebrity = this.celebrityService.Do(imgData);
            listTask.Add(taskCelebrity);
            await Task.WhenAll(listTask);
            LandmarkResult lmResult = taskLandmark.Result;
            CelebrityResult cbResult = taskCelebrity.Result;

            // aggregator
            // todo: put this logic into Aggregator service
            AggregatedResult ar = new AggregatedResult()
            {
                Landmark = lmResult,
                Celebrity = cbResult
            };

            return ar;
  

            // ranker
            // todo: if there have more than one result in AgregatedResult, need give them a ranking

            // output generator
            // todo: generate specified JSON data, such as Adptive Card
        }
    }
}

小提示：大家可以看到上面这个文件中有很多绿色的注释，带有todo文字的，对于一个更复杂的系统，可以用这些todo中的描述来设计独立的模块。

AggregatedResult.cs – 任务调度层服务的最终聚合结果定义

using CognitiveMiddlewareService.MiddlewareService;

namespace CognitiveMiddlewareService.Processors
{
    public class AggregatedResult
    {
        public LandmarkResult Landmark { get; set; }

        public CelebrityResult Celebrity { get; set; }
    }
}