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# 访问模型摘要文件
<a name="im-summary-file-api"></a>

摘要文件包含有关整个模型的评估结果信息以及每个标签的指标。这些指标包括精度、召回率、F1 分数。此外，还提供了模型的阈值。可从 `DescribeProjectVersions` 返回的 `EvaluationResult` 对象获取摘要文件的位置。有关更多信息，请参阅 [参考：训练结果摘要文件](im-summary-file.md)。

下面是一个示例摘要文件。

```
{
  "Version": 1,
  "AggregatedEvaluationResults": {
    "ConfusionMatrix": [
      {
        "GroundTruthLabel": "CAP",
        "PredictedLabel": "CAP",
        "Value": 0.9948717948717949
      },
      {
        "GroundTruthLabel": "CAP",
        "PredictedLabel": "WATCH",
        "Value": 0.008547008547008548
      },
      {
        "GroundTruthLabel": "WATCH",
        "PredictedLabel": "CAP",
        "Value": 0.1794871794871795
      },
      {
        "GroundTruthLabel": "WATCH",
        "PredictedLabel": "WATCH",
        "Value": 0.7008547008547008
      }
    ],
    "F1Score": 0.9726959470546408,
    "Precision": 0.9719115848331294,
    "Recall": 0.9735042735042735
  },
  "EvaluationDetails": {
    "EvaluationEndTimestamp": "2019-11-21T07:30:23.910943",
    "Labels": [
      "CAP",
      "WATCH"
    ],
    "NumberOfTestingImages": 624,
    "NumberOfTrainingImages": 5216,
    "ProjectVersionArn": "arn:aws:rekognition:us-east-1:nnnnnnnnn:project/my-project/version/v0/1574317227432"
  },
  "LabelEvaluationResults": [
    {
      "Label": "CAP",
      "Metrics": {
        "F1Score": 0.9794344473007711,
        "Precision": 0.9819587628865979,
        "Recall": 0.9769230769230769,
        "Threshold": 0.9879502058029175
      },
      "NumberOfTestingImages": 390
    },
    {
      "Label": "WATCH",
      "Metrics": {
        "F1Score": 0.9659574468085106,
        "Precision": 0.961864406779661,
        "Recall": 0.9700854700854701,
        "Threshold": 0.014450683258473873
      },
      "NumberOfTestingImages": 234
    }
  ]
}
```