EDedgeimpulse
Classify

Classify job result

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

get/api/{projectId}/classify/all/result

Request

Path parameters

projectIdinteger required

Project ID

Query parameters

featureExplorerOnlyboolean

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

variant'int8' | 'float32' | 'akida'

Keras model variant

impulseIdinteger

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

truncateStructuredLabelsboolean

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

category'training' | 'testing'

Category to run model testing, or to retrieve results. If not provided, this will default to 'testing'.

Response

OK

successboolean required

Whether the operation succeeded

errorstring

Optional error description (set if 'success' was false)

availableVariantsKerasModelVariantEnum[] required

List of all model variants for which classification results exist

noResultsBecauseThresholdsChanged'can_regenerate_model_summary' | 'should_rerun_full_job'

If set to true, there are currently no results because thresholds were changed (e.g. on live classification); and what action you can run to get new results the quickest. If the value is "can_regenerate_model_summary" you can run 'regenerateModelTestingSummary'. If the value is "should_rerun_full_job", you need to run 'startClassifyJob' or 'startEvaluateJob'.

Example response

{
  "result": [
    {
      "sample": {
        "id": 2,
        "filename": "idle01.d8Ae",
        "signatureValidate": true,
        "signatureMethod": "HS256",
        "label": "healthy-machine",
        "intervalMs": 16,
        "frequency": 62.5,
        "originalIntervalMs": 16,
        "originalFrequency": 62.5,
        "sensors": [
          {
            "name": "accX"
          }
        ],
        "datastreams": [
          {
            "sensors": [
              {
                "name": "accX"
              }
            ]
          }
        ]
      },
      "classifications": [
        {
          "learnBlock": {
            "name": "NN Classifier",
            "dsp": [
              27
            ],
            "title": "Classification (Keras)",
            "createdBy": "createImpulse"
          },
          "result": [
            {
              "idle": 0.0002,
              "wave": 0.9998,
              "anomaly": -0.42
            }
          ],
          "structuredResult": [
            {
              "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"
            }
          ],
          "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."
            }
          ]
        }
      ]
    }
  ]
}

Changes

No recorded changes to this operation across all 1 revision of this API.