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0bd93c14bb
...
d36fb2fc9f
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@ -3,6 +3,7 @@ using FFmpeg.NET;
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using VideoAnalysisCore.AICore.SherpaOnnx;
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using VideoAnalysisCore.Common;
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using System.Threading.Tasks;
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using static System.Runtime.InteropServices.JavaScript.JSType;
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using System.Xml.Linq;
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using System.Runtime.InteropServices;
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using SqlSugar.IOC;
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@ -40,7 +41,6 @@ namespace VideoAnalysisCore.AICore.FFMPGE
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//间隔秒
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var intervalSec = 5;
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var threshold = 8.15;
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var ssimThreshold = 0.9;
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var PPTVideoCode = await DbScoped.Sugar
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.Queryable<VideoTask>()
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.Where(s => s.Id == long.Parse(task))
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@ -65,37 +65,38 @@ namespace VideoAnalysisCore.AICore.FFMPGE
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var frameFiles = Directory.GetFiles(localPath, "*.jpg")
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.OrderBy(f => f)
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.ToList();
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RedisExpand.SetTaskProgress(task, "Frame=>50%");
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Image<Rgb24> prevFrame = null;
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var keyFrames = new List<int>(10) { 5};
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var keyFrames = new List<int>(5);
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foreach (var frameFile in frameFiles)
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{
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using (var currFrame = Image.Load<Rgb24>(frameFile))
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{
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if (prevFrame != null)
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{
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double ssim = SSIMCalculator.CalculateFrameSSIM(prevFrame, currFrame);
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//double diff = CalculateFrameDifference(prevFrame, currFrame);
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double diff = CalculateFrameDifference(prevFrame, currFrame);
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double timestamp = GetTimestampFromFileName(frameFile) * intervalSec;
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//if (diff > threshold)
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if (ssim < ssimThreshold)
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if (diff > threshold)
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{
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keyFrames.Add((int)timestamp);
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//string outputPath = Path.Combine(outputDir, $"change_{timestamp:0000}.jpg");
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//currFrame.Save(outputPath);
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Console.WriteLine($"变化帧: {timestamp}秒,差异值: {ssim:F2}");
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Console.WriteLine($"变化帧: {timestamp}秒,差异值: {diff:F2}");
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}
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//Console.WriteLine($"帧: {timestamp}秒,SSIM{ssim:F2} 差异值: {ssim:F2} ");
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//else
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//Console.WriteLine($"帧: {timestamp}秒,差异值: {diff:F2}");
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}
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prevFrame?.Dispose();
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prevFrame = currFrame.Clone();
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}
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}
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// 去掉相邻的重复图片
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// 遍历数组
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for (int i = 1; i < keyFrames.Count(); i++)
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{
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keyFrames[i] += 5;//ppt与课堂视频时间修正
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if (keyFrames[i] - keyFrames[i - 1] < 10)
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keyFrames[i] = -1;
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}
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@ -108,7 +109,6 @@ namespace VideoAnalysisCore.AICore.FFMPGE
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.ExecuteCommandAsync();
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}
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/// <summary>
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/// 计算帧差异
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/// </summary>
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@ -22,11 +22,5 @@ namespace VideoAnalysisCore.AICore.GPT
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/// <param name="task">任务id</param>
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/// <returns></returns>
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public Task GetVideoQuestion(string task);
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/// <summary>
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/// 获取视频类型
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/// </summary>
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/// <param name="task"></param>
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/// <returns></returns>
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public Task GetVideoType(string task);
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}
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}
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@ -423,10 +423,5 @@ namespace VideoAnalysisCore.AICore.GPT.ChatGPT
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{
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throw new NotImplementedException();
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}
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Task IBserGPT.GetVideoType(string task)
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{
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throw new NotImplementedException();
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}
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}
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}
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@ -49,7 +49,6 @@ namespace VideoAnalysisCore.AICore.GPT.DeepSeek
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{
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//chatReq.model = "deepseek-r1";
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if (chatReq.stream) return await ChatSSE(chatReq);
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postStar:
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var requestBody = chatReq.ToJson();
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HttpResponseMessage chatResp = PostJsonStream(Path, requestBody);
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@ -58,6 +57,7 @@ namespace VideoAnalysisCore.AICore.GPT.DeepSeek
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{
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Console.WriteLine(DateTime.Now + $"=>GPT请求失败重试 Code = {chatResp.StatusCode} Res={res1}");
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goto postStar;
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}
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//throw new Exception($" GPT模型返回异常 返回参数: " +
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// $" {System.Text.Json.JsonSerializer.Serialize(res1)}");
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@ -20,7 +20,6 @@ using Aliyun.OSS;
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using Yitter.IdGenerator;
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using VideoAnalysisCore.Common.Expand;
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using System.Collections.Generic;
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using UserCenter.Model.Enum;
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namespace VideoAnalysisCore.AICore.GPT.DeepSeek
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{
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@ -347,7 +346,7 @@ namespace VideoAnalysisCore.AICore.GPT.DeepSeek
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if (max_tokens != -1)
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chatRep.max_tokens = max_tokens;
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var tryCount = 10;
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while (tryCount-- > 0)
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while (--tryCount > 0)
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{
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try
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{
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@ -393,8 +392,8 @@ namespace VideoAnalysisCore.AICore.GPT.DeepSeek
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}
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catch (Exception ex)
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{
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Console.WriteLine(ex.Message);
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Console.WriteLine(DateTime.Now + $"=>ChatGPT结果解析错误 重试剩余{tryCount}");
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Console.WriteLine(ex.Message);
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}
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}
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throw new Exception(DateTime.Now + "=>ChatGPT请求失败次数过多!!!");
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@ -402,7 +401,6 @@ namespace VideoAnalysisCore.AICore.GPT.DeepSeek
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/// <summary>
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/// 提取试题
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/// </summary>
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@ -424,9 +422,9 @@ namespace VideoAnalysisCore.AICore.GPT.DeepSeek
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foreach (var item in farmeArr)
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{
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var knowInfoArr = videoKnowArr
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.Where(s => item + 20 >= s.StartTime && item < s.EndTime)
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.FirstOrDefault();
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if (knowInfoArr is null)
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.Where(s => item + 20 >= s.StartTime && item <= s.EndTime)
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.ToArray();
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if (knowInfoArr is null || knowInfoArr.Count() == 0)
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continue;
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var tryCount = 50;
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while (tryCount > 1)
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@ -441,7 +439,7 @@ namespace VideoAnalysisCore.AICore.GPT.DeepSeek
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continue;
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if (sRes.Result.res.value.Trim().Length < 10)//总试题内容长度小于10 视为无效题目
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break;
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Console.WriteLine(DateTime.Now + $"=>{taskInfo.Id} 提取{knowInfoArr.StartTime}秒试题的试题内容");
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Console.WriteLine(DateTime.Now + $"=>{taskInfo.Id} 提取{knowInfoArr.First().StartTime}秒试题的试题内容");
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Console.WriteLine(sRes.Result.res.value);
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//var knowArr=JsonSerializer.Serialize(knowInfoArr.Select(s => new { s.KnowPointId, s.KnowPoint }));
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var resFormat = """[{"Type":string(试题类型),"TopicStem":string(试题题干),"QuestionArr":[{"Question":string(子问题),"KnowPointId":(string)知识点ID}]}]""";
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@ -471,7 +469,7 @@ namespace VideoAnalysisCore.AICore.GPT.DeepSeek
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vq.StartTime = item;
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vq.FilePath = filePath;
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vq.VideoTaskId = taskInfo.Id;
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vq.StageId = knowInfoArr.StageId;
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vq.StageId = knowInfoArr.First().StageId;
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vq.Question = qt.Question;
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vq.TopicId = TopicId;
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vq.Type = q.Type;
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@ -498,7 +496,7 @@ namespace VideoAnalysisCore.AICore.GPT.DeepSeek
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}
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catch (Exception ex)
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{
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Console.WriteLine(DateTime.Now + $"=>{taskInfo.Id} 提取{knowInfoArr.StartTime}秒试题出现错误 {ex.Message}");
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Console.WriteLine(DateTime.Now + $"=>{taskInfo.Id} 提取{knowInfoArr.First().StartTime}秒试题出现错误 {ex.Message}");
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}
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}
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}
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@ -618,6 +616,7 @@ namespace VideoAnalysisCore.AICore.GPT.DeepSeek
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var subject = taskInfo.Subject.ToString();
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var Course_Id = taskInfo.CourseId;
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var captionsArr = JsonSerializer.Deserialize<SenseVoiceRes[]>(taskInfo.Captions);
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//处理视频授课章节
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var sections = await GetSections(taskInfo, Course_Id);
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var know = await knowledgeInfoDB.GetFirstAsync(s => s.Course_Id == Course_Id && s.Name == sections);
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@ -631,51 +630,5 @@ namespace VideoAnalysisCore.AICore.GPT.DeepSeek
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return;
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}
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/// <summary>
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/// 分析视频是否为复习课
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/// </summary>
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/// <param name="task"></param>
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/// <returns></returns>
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public async Task GetVideoType(string task)
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{
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var taskId = long.Parse(task);
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var taskInfo = await videoTaskDB.AsQueryable()
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.Where(s => s.Id == taskId)
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.FirstAsync();
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var subject = taskInfo.Subject.ToString();
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var Course_Id = taskInfo.CourseId;
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var videoTypeStr = string.Join(',', Enum.GetNames(typeof(AttachmentsInfoType)));
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//处理视频授课章节
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var sections = await GetSections(taskInfo, Course_Id);
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var captionsArr = JsonSerializer.Deserialize<SenseVoiceRes[]>(taskInfo.Captions);
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captionsArr = await OptimizeSubtitles(taskInfo, captionsArr, sections);
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//合并字幕
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var captions = ExpandFunction.GetSpeakerCaptions(captionsArr);
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var resFormat = """{ "VideoType":string(课程类型),"Reason":string(分析原因)}""";
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var postMessages =
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$"我将提供一段视频的字幕内容,请你帮我分析这堂课的课程类型是什么。" +
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$"授课类型限定在我提供的范围内 [{videoTypeStr}]" +
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$"其中如果是[习题课/长篇幅的试题讲解课程]那么课程类型视为'复习'" +
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$"请简介的说明分析出课程类型的原因,如果分析出的课程类型与限定条件不匹配则返回NULL" +
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$"输出内容只返回json格式为({resFormat})" +
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$"以下是字幕内容" +
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$"`{captions.Captions}`";
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var resData = await ChatAsync<AIVideoTypeDto?>(taskInfo.Id.ToString(), postMessages, "视频类型", "deepseek-chat");
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var res = resData.VideoType.ToEnum<AttachmentsInfoType>();
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if (res != null)
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{
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await videoTaskDB.AsUpdateable()
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.SetColumns(it => it.VideoType == res)
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.Where(it => it.Id == taskInfo.Id)
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.ExecuteCommandAsync();
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}
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}
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}
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}
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@ -1,18 +0,0 @@
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using System;
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using System.Collections.Generic;
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using System.Linq;
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using System.Text;
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using System.Threading.Tasks;
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using VideoAnalysisCore.Model.Enum;
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namespace VideoAnalysisCore.AICore.GPT.Dto
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{
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public class AIVideoTypeDto
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{
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public string? VideoType { get; set; }
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/// <summary>
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/// 分析结果原因
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/// </summary>
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public string Reason { get; set; }
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}
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}
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@ -132,6 +132,10 @@ namespace VideoAnalysisCore.Common
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var fileUrl = taskInfo.MediaUrl;
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if (string.IsNullOrEmpty(fileUrl))
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{
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switch (taskInfo.VideoType)
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{
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case AttachmentsInfoType.新课:
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case AttachmentsInfoType.复习:
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var videoInfo = await vodClient.GetPlayInfoAsync(new AlibabaCloud.SDK.Vod20170321.Models.GetPlayInfoRequest()
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{
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VideoId = taskInfo.TagId,
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@ -142,6 +146,10 @@ namespace VideoAnalysisCore.Common
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if (videoInfo is null || videoInfo.StatusCode != 200 && !videoInfo.Body.PlayInfoList.PlayInfo.Any())
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throw new Exception($"{DateTime.Now} 视频订阅=>获取阿里云视频信息失败 VideoCode {taskInfo.TagId} StatusCode {videoInfo?.StatusCode}");
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fileUrl = videoInfo.Body.PlayInfoList.PlayInfo.First().PlayURL;
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break;
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default:
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break;
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}
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}
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if (string.IsNullOrEmpty(fileUrl))
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throw new Exception($"任务id[{task}] 资源地址无效 {fileUrl}");
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|
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@ -174,8 +174,7 @@ namespace VideoAnalysisCore.Common
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Redis.HMSet(RedisExpandKey.Task(taskId), "StartTime", startTime);
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await TouchChannel(@enum, tId, SubscribeList[@enum]);
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//await SubscribeList[@enum](tId);
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await SubscribeList[@enum](tId);
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var e = @enum.NextEnum();
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if (e is null)
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break;
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@ -234,43 +233,44 @@ namespace VideoAnalysisCore.Common
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{
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if (Redis is null) throw new Exception("redis未初始化");
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SubscribeList.Add(RedisChannelEnum.下载文件, (task) =>
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SubscribeList.Add(RedisChannelEnum.下载文件,
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async (msg) => await TouchChannel(RedisChannelEnum.下载文件, msg,
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(task) =>
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{
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using var scope = AppCommon.Services?.CreateScope();
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if (scope is null || scope.ServiceProvider.GetService<DownloadFile>() is null)
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throw new Exception("DownloadFile 未注入");
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else
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return scope.ServiceProvider.GetService<DownloadFile>()?.RunTask(task) ?? Task.CompletedTask;
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});
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SubscribeList.Add(RedisChannelEnum.分离音频, FFMPGEHandle.RunAsync);
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SubscribeList.Add(RedisChannelEnum.解析字幕, SenseVoice.RunTask);
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//SubscribeList.Add(RedisChannelEnum.解析说话人,Speaker.Run);
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SubscribeList.Add(RedisChannelEnum.AI课程类型,
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}));
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SubscribeList.Add(RedisChannelEnum.分离音频,
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async (msg) => await TouchChannel(RedisChannelEnum.分离音频, msg, FFMPGEHandle.RunAsync));
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SubscribeList.Add(RedisChannelEnum.解析字幕,
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async (msg) => await TouchChannel(RedisChannelEnum.解析字幕, msg, SenseVoice.RunTask));
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//SubscribeList.Add(RedisChannelEnum.解析说话人,
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// async (msg) => await TouchChannel(RedisChannelEnum.解析说话人, msg, Speaker.Run));
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SubscribeList.Add(RedisChannelEnum.AI模型分析,
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async (msg) => await TouchChannel(RedisChannelEnum.AI模型分析, msg,
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(task) =>
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{
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using var scope = AppCommon.Services?.CreateScope();
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if (scope is null || scope.ServiceProvider.GetService<IBserGPT>() is null)
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throw new Exception("IBserGPT 未注入");
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else
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return scope.ServiceProvider.GetService<IBserGPT>()?.GetVideoType(task) ?? Task.CompletedTask;
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});
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SubscribeList.Add(RedisChannelEnum.AI模型分析, (task) =>
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{
|
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using var scope = AppCommon.Services?.CreateScope();
|
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if (scope is null || scope.ServiceProvider.GetService<IBserGPT>() is null)
|
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throw new Exception("IBserGPT 未注入");
|
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else
|
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return scope.ServiceProvider.GetService<IBserGPT>()?.GetKnow(task) ?? Task.CompletedTask;
|
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});
|
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SubscribeList.Add(RedisChannelEnum.AI分析试题, (task) =>
|
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}));
|
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SubscribeList.Add(RedisChannelEnum.AI分析试题,
|
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async (msg) => await TouchChannel(RedisChannelEnum.AI分析试题, msg,
|
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(task) =>
|
||||
{
|
||||
using var scope = AppCommon.Services?.CreateScope();
|
||||
if (scope is null || scope.ServiceProvider.GetService<IBserGPT>() is null)
|
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throw new Exception("IBserGPT 未注入");
|
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else
|
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return scope.ServiceProvider.GetService<IBserGPT>()?.GetVideoQuestion(task) ?? Task.CompletedTask;
|
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});
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SubscribeList.Add(RedisChannelEnum.结束任务, TaskEnd);
|
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}));
|
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SubscribeList.Add(RedisChannelEnum.结束任务,
|
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async (msg) => await TouchChannel(RedisChannelEnum.结束任务, msg, TaskEnd));
|
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|
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ReceivingTaskAsync();
|
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|
||||
|
|
|
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|
|
@ -1,97 +0,0 @@
|
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using SixLabors.ImageSharp;
|
||||
using SixLabors.ImageSharp.PixelFormats;
|
||||
using System;
|
||||
using System.Collections.Generic;
|
||||
using System.Linq;
|
||||
using System.Text;
|
||||
using System.Threading.Tasks;
|
||||
using SixLabors.ImageSharp.Processing;
|
||||
|
||||
namespace VideoAnalysisCore.Common
|
||||
{
|
||||
/// <summary>
|
||||
/// Ssim计算器
|
||||
/// </summary>
|
||||
public class SSIMCalculator
|
||||
{
|
||||
// SSIM计算常量 (基于8-bit图像范围0-255)
|
||||
private const double C1 = (0.01 * 255) * (0.01 * 255);
|
||||
private const double C2 = (0.03 * 255) * (0.03 * 255);
|
||||
|
||||
/// <summary>
|
||||
/// 计算连续帧的SSIM 值
|
||||
/// </summary>
|
||||
/// <param name="img1"></param>
|
||||
/// <param name="img2"></param>
|
||||
/// <returns>返回阈值 0-1 越小变化越大<para>清晰视频:阈值 0.90-0.95 </para> <para>低质量视频:阈值 0.85-0.90</para></returns>
|
||||
public static double CalculateFrameSSIM(Image<Rgb24> img1, Image<Rgb24> img2)
|
||||
{
|
||||
// 转换为灰度图
|
||||
var gray1 = CreateResizedGrayImage(img1);
|
||||
var gray2 = CreateResizedGrayImage(img2);
|
||||
|
||||
// 计算全局统计量
|
||||
CalculateStats(gray1, gray2, out double mean1, out double mean2,
|
||||
out double var1, out double var2, out double covar);
|
||||
|
||||
// 计算SSIM分量
|
||||
double luminance = (2 * mean1 * mean2 + C1) / (mean1 * mean1 + mean2 * mean2 + C1);
|
||||
double contrast = (2 * Math.Sqrt(var1) * Math.Sqrt(var2) + C2) / (var1 + var2 + C2);
|
||||
double structure = (covar + C2 / 2) / (Math.Sqrt(var1) * Math.Sqrt(var2) + C2 / 2);
|
||||
|
||||
// 返回SSIM值 (值越接近1表示越相似)
|
||||
return luminance * contrast * structure;
|
||||
}
|
||||
|
||||
private static Image<L8> CreateResizedGrayImage(Image<Rgb24> image)
|
||||
{
|
||||
return image
|
||||
.Clone(x => x.Grayscale())
|
||||
.CloneAs<L8>(); // 转换为8位灰度格式
|
||||
}
|
||||
|
||||
private static void CalculateStats(
|
||||
Image<L8> img1,
|
||||
Image<L8> img2,
|
||||
out double mean1,
|
||||
out double mean2,
|
||||
out double var1,
|
||||
out double var2,
|
||||
out double covar)
|
||||
{
|
||||
int width = img1.Width;
|
||||
int height = img1.Height;
|
||||
int totalPixels = width * height;
|
||||
|
||||
double sum1 = 0, sum2 = 0;
|
||||
double sum1Sq = 0, sum2Sq = 0, sumProduct = 0;
|
||||
|
||||
// 单次遍历计算所有统计量
|
||||
for (int y = 0; y < height; y++)
|
||||
{
|
||||
for (int x = 0; x < width; x++)
|
||||
{
|
||||
double val1 = img1[x, y].PackedValue;
|
||||
double val2 = img2[x, y].PackedValue;
|
||||
|
||||
sum1 += val1;
|
||||
sum2 += val2;
|
||||
sum1Sq += val1 * val1;
|
||||
sum2Sq += val2 * val2;
|
||||
sumProduct += val1 * val2;
|
||||
}
|
||||
}
|
||||
|
||||
// 计算均值
|
||||
mean1 = sum1 / totalPixels;
|
||||
mean2 = sum2 / totalPixels;
|
||||
|
||||
// 计算方差: Var(X) = E[X²] - E[X]²
|
||||
var1 = (sum1Sq / totalPixels) - (mean1 * mean1);
|
||||
var2 = (sum2Sq / totalPixels) - (mean2 * mean2);
|
||||
|
||||
// 计算协方差: Cov(X,Y) = E[XY] - E[X]E[Y]
|
||||
covar = (sumProduct / totalPixels) - (mean1 * mean2);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
@ -16,8 +16,6 @@ using Microsoft.AspNetCore.Http;
|
|||
using VideoAnalysisCore.Model.Dto;
|
||||
using VideoAnalysisCore.Controllers.Dto;
|
||||
using VideoAnalysisCore.Common.Expand;
|
||||
using Microsoft.Extensions.DependencyInjection;
|
||||
using System.Threading.Tasks;
|
||||
|
||||
namespace VideoAnalysisCore.Controllers
|
||||
{
|
||||
|
|
@ -70,22 +68,6 @@ namespace VideoAnalysisCore.Controllers
|
|||
#endif
|
||||
|
||||
|
||||
/// <summary>
|
||||
/// 初始化主库表
|
||||
/// </summary>
|
||||
/// <param name="url">文件流</param>
|
||||
/// <returns></returns>
|
||||
[HttpGet(Name = "tets1")]
|
||||
public IActionResult tets1(string task)
|
||||
{
|
||||
|
||||
using var scope = AppCommon.Services?.CreateScope();
|
||||
if (scope is null || scope.ServiceProvider.GetService<IBserGPT>() is null)
|
||||
throw new Exception("IBserGPT 未注入");
|
||||
else
|
||||
scope.ServiceProvider.GetService<IBserGPT>()?.GetVideoType(task);
|
||||
return Ok();
|
||||
}
|
||||
/// <summary>
|
||||
/// ÓïÒôʶ±ð
|
||||
/// </summary>
|
||||
|
|
|
|||
|
|
@ -141,6 +141,7 @@ namespace VideoAnalysisCore.Controllers
|
|||
/// <summary>
|
||||
/// 获取视频知识点片段<para>taskId/tagId二选一</para>
|
||||
/// </summary>
|
||||
/// <param name="taskId"></param>
|
||||
/// <param name="tagId">自定义id</param>
|
||||
/// <returns></returns>
|
||||
[HttpGet(Name = "TaskKnowInfo")]
|
||||
|
|
|
|||
|
|
@ -47,19 +47,10 @@ namespace VideoAnalysisCore.Job
|
|||
var taskArr = await nodePackageInfoDB.AsQueryable()
|
||||
.Where(s => s.SuccessTime == null)
|
||||
.ToArrayAsync();
|
||||
var videoArr = await videoTaskDB.AsQueryable()
|
||||
var videoIdArr = await videoTaskDB.AsQueryable()
|
||||
.Where(s => s.EndTime != null)
|
||||
.Select(s =>new VideoTask {
|
||||
Id = s.Id,
|
||||
TagId = s.TagId,
|
||||
VideoType=s.VideoType
|
||||
})
|
||||
.Select(s => s.TagId)
|
||||
.ToArrayAsync();
|
||||
var videoDic = videoArr
|
||||
.Where(s=>s.TagId != null)
|
||||
.GroupBy(s => s.TagId!)
|
||||
.ToDictionary(s => s.Key,s=>s.First());
|
||||
var videoIdArr = videoArr.Select(s => s.TagId).ToArray();
|
||||
|
||||
var videoPPTArr = await videoTaskDB.AsQueryable()
|
||||
.Where(s => s.EndTime != null)
|
||||
|
|
@ -70,13 +61,6 @@ namespace VideoAnalysisCore.Job
|
|||
{
|
||||
if (videoIdArr.Contains(item.VideoCode)|| videoPPTArr.Contains(item.VideoCode))
|
||||
{
|
||||
if (videoDic.ContainsKey(item.VideoCode))
|
||||
{
|
||||
var v = videoDic[item.VideoCode];
|
||||
if (v.VideoType!=null && v.VideoType != item.CourseType)
|
||||
item.CourseType = v.VideoType.Value;//额外同步课程类型[新课 复习课]
|
||||
}
|
||||
|
||||
postData.Add(item);
|
||||
item.SuccessTime = DateTime.Now;
|
||||
}
|
||||
|
|
|
|||
|
|
@ -25,11 +25,6 @@
|
|||
///// 解析说话人
|
||||
///// </summary>
|
||||
//解析说话人 = 30,
|
||||
|
||||
/// <summary>
|
||||
/// AI课程类型
|
||||
/// </summary>
|
||||
AI课程类型 = 31,
|
||||
/// <summary>
|
||||
/// Chat模型分析
|
||||
/// </summary>
|
||||
|
|
|
|||
|
|
@ -75,7 +75,7 @@ namespace VideoAnalysisCore.Model
|
|||
/// <summary>
|
||||
/// 通知回调地址
|
||||
/// </summary>
|
||||
[SugarColumn(IsNullable = true,Length = 500)]
|
||||
[SugarColumn(Length = 500)]
|
||||
public string CallBackUrl { get; set; }
|
||||
/// <summary>
|
||||
/// 请求区域
|
||||
|
|
|
|||
Loading…
Reference in New Issue