Classify job result

Classify job result

get

Get classify job result, containing the result for the complete testing dataset.

Authorizations
Path parameters
projectIdintegerRequired

Project ID

Query parameters
featureExplorerOnlybooleanOptional

Whether to get only the classification results relevant to the feature explorer.

variantstring · enumOptional

Keras model variant

Possible values:
impulseIdintegerOptional

Impulse ID. If this is unset then the default impulse is used.

truncateStructuredLabelsbooleanOptional

If true, only a slice of labels will be returned for samples with multiple labels.

Responses
200
OK
application/json
Responseall of
get
GET /v1/api/{projectId}/classify/all/result HTTP/1.1
Host: studio.edgeimpulse.com
x-api-key: YOUR_API_KEY
Accept: */*
200

OK

{
  "success": true,
  "error": "text",
  "result": [
    {
      "sampleId": 1,
      "sample": {
        "id": 2,
        "filename": "idle01.d8Ae",
        "signatureValidate": true,
        "signatureMethod": "HS256",
        "signatureKey": "text",
        "created": "2025-07-12T03:24:16.659Z",
        "lastModified": "2025-07-12T03:24:16.659Z",
        "category": "training",
        "coldstorageFilename": "text",
        "label": "healthy-machine",
        "intervalMs": 16,
        "frequency": 62.5,
        "originalIntervalMs": 16,
        "originalFrequency": 62.5,
        "deviceName": "text",
        "deviceType": "text",
        "sensors": [
          {
            "name": "accX",
            "units": "text"
          }
        ],
        "valuesCount": 1,
        "totalLengthMs": 1,
        "added": "2025-07-12T03:24:16.659Z",
        "boundingBoxes": [
          {
            "label": "text",
            "x": 1,
            "y": 1,
            "width": 1,
            "height": 1
          }
        ],
        "boundingBoxesType": "object_detection",
        "chartType": "chart",
        "thumbnailVideo": "text",
        "thumbnailVideoFull": "text",
        "isDisabled": true,
        "isProcessing": true,
        "processingJobId": 1,
        "processingError": true,
        "processingErrorString": "text",
        "isCropped": true,
        "metadata": {
          "ANY_ADDITIONAL_PROPERTY": "text"
        },
        "projectId": 1,
        "projectOwnerName": "text",
        "projectName": "text",
        "projectLabelingMethod": "single_label",
        "sha256Hash": "text",
        "structuredLabels": [
          {
            "startIndex": 1,
            "endIndex": 1,
            "label": "text"
          }
        ],
        "structuredLabelsList": [
          "text"
        ],
        "createdBySyntheticDataJobId": 1,
        "imageDimensions": {
          "width": 1,
          "height": 1
        },
        "videoUrl": "text",
        "videoUrlFull": "text"
      },
      "classifications": [
        {
          "learnBlock": {
            "id": 1,
            "type": "anomaly",
            "name": "NN Classifier",
            "dsp": [
              27
            ],
            "title": "Classification (Keras)",
            "createdBy": "createImpulse",
            "createdAt": "2025-07-12T03:24:16.659Z"
          },
          "result": [
            {
              "idle": 0.0002,
              "wave": 0.9998,
              "anomaly": -0.42
            }
          ],
          "anomalyResult": [
            {
              "boxes": [
                {
                  "label": "text",
                  "x": 1,
                  "y": 1,
                  "width": 1,
                  "height": 1,
                  "score": 1
                }
              ],
              "scores": [
                [
                  1
                ]
              ],
              "meanScore": 1,
              "maxScore": 1
            }
          ],
          "structuredResult": [
            {
              "boxes": [
                [
                  1
                ]
              ],
              "labels": [
                "text"
              ],
              "scores": [
                1
              ],
              "mAP": 1,
              "f1": 1,
              "precision": 1,
              "recall": 1,
              "debugInfoJson": "{\n    \"y_trues\": [\n        {\"x\": 0.854, \"y\": 0.453125, \"label\": 1},\n        {\"x\": 0.197, \"y\": 0.53125, \"label\": 2}\n    ],\n    \"y_preds\": [\n        {\"x\": 0.916, \"y\": 0.875, \"label\": 1},\n        {\"x\": 0.25, \"y\": 0.541, \"label\": 2}\n    ],\n    \"assignments\": [\n        {\"yp\": 1, \"yt\": 1, \"label\": 2, \"distance\": 0.053}\n    ],\n    \"normalised_min_distance\": 0.2,\n    \"all_pairwise_distances\": [\n        [0, 0, 0.426],\n        [1, 1, 0.053]\n    ],\n    \"unassigned_y_true_idxs\": [0],\n    \"unassigned_y_pred_idxs\": [0]\n}\n"
            }
          ],
          "minimumConfidenceRating": 1,
          "details": [
            {
              "boxes": [
                [
                  1
                ]
              ],
              "labels": [
                1
              ],
              "scores": [
                1
              ],
              "mAP": 1,
              "f1": 1
            }
          ],
          "objectDetectionLastLayer": "mobilenet-ssd",
          "expectedLabels": [
            {
              "startIndex": 1,
              "endIndex": 1,
              "label": "text"
            }
          ],
          "thresholds": [
            {
              "key": "min_score",
              "description": "Score threshold",
              "helpText": "Threshold score for bounding boxes. If the score for a bounding box is below this the box will be discarded.",
              "suggestedValue": 1,
              "suggestedValueText": "text",
              "value": 0.5
            }
          ]
        }
      ]
    }
  ],
  "predictions": [
    {
      "sampleId": 1,
      "startMs": 1,
      "endMs": 1,
      "label": "text",
      "prediction": "text",
      "predictionCorrect": true,
      "f1Score": 1,
      "anomalyScores": [
        [
          1
        ]
      ]
    }
  ],
  "accuracy": {
    "totalSummary": {
      "good": 1,
      "bad": 1
    },
    "summaryPerClass": {
      "ANY_ADDITIONAL_PROPERTY": {
        "good": 1,
        "bad": 1
      }
    },
    "confusionMatrixValues": {
      "ANY_ADDITIONAL_PROPERTY": {
        "ANY_ADDITIONAL_PROPERTY": 1
      }
    },
    "allLabels": [
      "text"
    ],
    "accuracyScore": 1,
    "balancedAccuracyScore": 1,
    "anomalyAccuracyScore": 1,
    "noAnomalyAccuracyScore": 1,
    "mseScore": 1
  },
  "additionalMetricsByLearnBlock": [
    {
      "learnBlockId": 1,
      "learnBlockName": "text",
      "additionalMetrics": [
        {
          "name": "text",
          "value": "text",
          "fullPrecisionValue": 1,
          "tooltipText": "text",
          "link": "text"
        }
      ]
    }
  ],
  "availableVariants": [
    "int8"
  ],
  "noResultsBecauseThresholdsChanged": "can_regenerate_model_summary"
}

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