Classify job result

Classify job result

get

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

Authorizations

ApiKeyAuthenticationJWTAuthenticationJWTHttpHeaderAuthenticationOAuth2

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

HTTPcURLJavaScriptPython

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": "2025-07-09T12:14:09.633Z",
        "lastModified": "2025-07-09T12:14:09.633Z",
        "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": "2025-07-09T12:14:09.633Z",
        "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": "2025-07-09T12:14:09.633Z"
          },
          "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"
}