如何汇总csv中的置信度？

Question

我的程序当前循环通过 pdf/image 文件的目录并使用 Azure computer vision REST API 生成 json 文件。使用下面的JsonToCsv()，我将这些文件中的特定 json 元素导出到 csv 文件中，因此输出如下所示：

file.csv 输出：

page,text,words,confidence
1,The quick brown fox jumps,The,0.958
1,The quick brown fox jumps,quick,0.57
1,The quick brown fox jumps,brown,0.799
1,The quick brown fox jumps,fox,0.442
1,The quick brown fox jumps,jumps,0.878
1,over,over,0.37
1,the lazy dog!,the,0.909
1,the lazy dog!,lazy,0.853
1,the lazy dog!,dog!,0.41

我想做的是合并单词，以便它们用逗号而不是单独的行分隔，因此，对包含这些单词的整个文本的置信度进行平均。例如，新文件如下：

page,text,words,confidence
1,The quick brown fox jumps,The,quick,brown,fox,jumps,0.729
1,over,over,0.37
1,the lazy dog!,the,lazy,dog!,0.724

其中第一个文本中的0.729 是相关置信水平组合和划分的结果/平均值：例如(0.958+0.57+0.799+0.442+0.878)/5。对最后一个文本也执行了相同的操作。

我如何更新下面的函数来完成这个？

JsonToCsv()代码：

private static void JsonToCsv(string jsonFile, string csvfFile) {   
    using (var p = new ChoJSONReader(jsonFile)
        .WithJSONPath("$..readResults")
        )
    {
        using (var w = new ChoCSVWriter(csvfFile).WithFirstLineHeader())
        {
            w.Write(p
                .SelectMany(r1 => ((dynamic[])r1.lines).SelectMany(r2 => ((dynamic[])r2.words).Select(r3 => new
                {
                    r1.page,
                    r2.text,
                    words = r3.text,
                    r3.confidence
                }))));
        }
    }
}

示例 JSON 文件：

{
  "status": "succeeded",
  "createdDateTime": "2020-05-28T05:13:21Z",
  "lastUpdatedDateTime": "2020-05-28T05:13:22Z",
  "analyzeResult": {
    "version": "3.1.0",
    "readResults": [
      {
        "page": 1,
        "language": "en",
        "angle": 0.8551,
        "width": 2661,
        "height": 1901,
        "unit": "pixel",
        "lines": [
          {
            "boundingBox": [
              67,
              646,
              2582,
              713,
              2580,
              876,
              67,
              821
            ],
            "text": "The quick brown fox jumps",
            "words": [
              {
                "boundingBox": [
                  143,
                  650,
                  435,
                  661,
                  436,
                  823,
                  144,
                  824
                ],
                "text": "The",
                "confidence": 0.958
              },
              {
                "boundingBox": [
                  540,
                  665,
                  926,
                  679,
                  926,
                  825,
                  541,
                  823
                ],
                "text": "quick",
                "confidence": 0.57
              },
              {
                "boundingBox": [
                  1125,
                  686,
                  1569,
                  700,
                  1569,
                  838,
                  1125,
                  828
                ],
                "text": "brown",
                "confidence": 0.799
              },
              {
                "boundingBox": [
                  1674,
                  703,
                  1966,
                  711,
                  1966,
                  851,
                  1674,
                  841
                ],
                "text": "fox",
                "confidence": 0.442
              },
              {
                "boundingBox": [
                  2083,
                  714,
                  2580,
                  725,
                  2579,
                  876,
                  2083,
                  855
                ],
                "text": "jumps",
                "confidence": 0.878
              }
            ]
          },
          {
            "boundingBox": [
              187,
              1062,
              485,
              1056,
              486,
              1120,
              189,
              1126
            ],
            "text": "over",
            "words": [
              {
                "boundingBox": [
                  190,
                  1064,
                  439,
                  1059,
                  441,
                  1122,
                  192,
                  1126
                ],
                "text": "over",
                "confidence": 0.37
              }
            ]
          },
          {
            "boundingBox": [
              664,
              1008,
              1973,
              1023,
              1969,
              1178,
              664,
              1154
            ],
            "text": "the lazy dog!",
            "words": [
              {
                "boundingBox": [
                  668,
                  1008,
                  923,
                  1015,
                  923,
                  1146,
                  669,
                  1117
                ],
                "text": "the",
                "confidence": 0.909
              },
              {
                "boundingBox": [
                  1107,
                  1018,
                  1447,
                  1023,
                  1445,
                  1178,
                  1107,
                  1162
                ],
                "text": "lazy",
                "confidence": 0.853
              },
              {
                "boundingBox": [
                  1639,
                  1024,
                  1974,
                  1023,
                  1971,
                  1170,
                  1636,
                  1178
                ],
                "text": "dog!",
                "confidence": 0.41
              }
            ]
          }
        ]
      }
    ]
  }
}

Answer 1

使用Linq，您可以生成预期格式的 CSV。下面的示例显示了如何

StringBuilder csv = new StringBuilder();
using (var p = new ChoJSONReader("*** YOUR JSON PATH ***")
    .WithJSONPath("$..readResults")
    )
{
    using (var w = new ChoCSVWriter(csv)
        .WithFirstLineHeader()
        )
    {
        w.Write(p
            .SelectMany(r1 => ((dynamic[])r1.lines)
            .Select(r2 => new
            {
                r1.page,
                r2.text,
                words = String.Join(",", ((dynamic[])r2.words).Select(s1 => s1.text)),
                confidence = ((dynamic[])r2.words).Select(s1 => (double)s1.confidence).Average()
            })));
    }
}

Console.WriteLine(csv.ToString());