本文為英文版的機器翻譯版本,如內容有任何歧義或不一致之處,概以英文版為準。
解譯評估資訊清單快照集
評估清單檔案快照會包含測試結果的詳細資訊。快照會包括每個預測的可信度評分。它還會包括和影像實際分類相比的預測分類 (相符、不相符、誤報或漏報)。
由於只包含可用於測試和訓練的影像,因此這些檔案會是快照。無法驗證的影像 (例如格式錯誤的影像) 不會包含在清單檔案中。測試快照位置可從由 DescribeProjectVersions
傳回的 TestingDataResult
物件存取。訓練快照位置可從由 DescribeProjectVersions
傳回的 TrainingDataResult
物件存取。
快照集採用 SageMaker Ground Truth 資訊清單輸出格式,並新增欄位以提供其他資訊,例如偵測的二進位分類結果。下列程式碼片段會顯示其他欄位。
"rekognition-custom-labels-evaluation-details": { "version": 1, "is-true-positive": true, "is-true-negative": false, "is-false-positive": false, "is-false-negative": false, "is-present-in-ground-truth": true "ground-truth-labelling-jobs": ["rekognition-custom-labels-training-job"] }
version — 清單檔案快照中的
rekognition-custom-labels-evaluation-details
欄位格式的版本。is-true-positive... — 根據可信度分數與標籤最小閾值比較結果的預測二進制分類。
is-present-in-ground-truth — 如果模型所做的預測存在於用於培訓的地面真相信息,則為真,否則為假。此值的根據並非可信度分數是否超過模型所計算的最小閾值。
ground-truth-labeling-jobs— 清單行中用於訓練的地面真值欄位清單清單清單。
如需有關 SageMaker Ground Truth 資訊清單格式的資訊,請參閱輸出。
以下是測試清單檔案快照的範例,其中會顯示影像分類和物件偵測的指標。
// For image classification { "source-ref": "s3://test-bucket/dataset/beckham.jpeg", "rekognition-custom-labels-training-0": 1, "rekognition-custom-labels-training-0-metadata": { "confidence": 1.0, "job-name": "rekognition-custom-labels-training-job", "class-name": "Football", "human-annotated": "yes", "creation-date": "2019-09-06T00:07:25.488243", "type": "groundtruth/image-classification" }, "rekognition-custom-labels-evaluation-0": 1, "rekognition-custom-labels-evaluation-0-metadata": { "confidence": 0.95, "job-name": "rekognition-custom-labels-evaluation-job", "class-name": "Football", "human-annotated": "no", "creation-date": "2019-09-06T00:07:25.488243", "type": "groundtruth/image-classification", "rekognition-custom-labels-evaluation-details": { "version": 1, "ground-truth-labelling-jobs": ["rekognition-custom-labels-training-job"], "is-true-positive": true, "is-true-negative": false, "is-false-positive": false, "is-false-negative": false, "is-present-in-ground-truth": true } } } // For object detection { "source-ref": "s3://test-bucket/dataset/beckham.jpeg", "rekognition-custom-labels-training-0": { "annotations": [ { "class_id": 0, "width": 39, "top": 409, "height": 63, "left": 712 }, ... ], "image_size": [ { "width": 1024, "depth": 3, "height": 768 } ] }, "rekognition-custom-labels-training-0-metadata": { "job-name": "rekognition-custom-labels-training-job", "class-map": { "0": "Cap", ... }, "human-annotated": "yes", "objects": [ { "confidence": 1.0 }, ... ], "creation-date": "2019-10-21T22:02:18.432644", "type": "groundtruth/object-detection" }, "rekognition-custom-labels-evaluation": { "annotations": [ { "class_id": 0, "width": 39, "top": 409, "height": 63, "left": 712 }, ... ], "image_size": [ { "width": 1024, "depth": 3, "height": 768 } ] }, "rekognition-custom-labels-evaluation-metadata": { "confidence": 0.95, "job-name": "rekognition-custom-labels-evaluation-job", "class-map": { "0": "Cap", ... }, "human-annotated": "no", "objects": [ { "confidence": 0.95, "rekognition-custom-labels-evaluation-details": { "version": 1, "ground-truth-labelling-jobs": ["rekognition-custom-labels-training-job"], "is-true-positive": true, "is-true-negative": false, "is-false-positive": false, "is-false-negative": false, "is-present-in-ground-truth": true } }, ... ], "creation-date": "2019-10-21T22:02:18.432644", "type": "groundtruth/object-detection" } }