Classify sample (deprecated)

Classify sample (deprecated)

This API is deprecated, use classifySampleV2 instead (/v1/api/{projectId}/classify/v2/{sampleId}). Classify a complete file against the current impulse. This will move the sliding window (dependent on the sliding window length and the sliding window increase parameters in the impulse) over the complete file, and classify for every window that is extracted.

GEThttps://studio.edgeimpulse.com/v1/api/{projectId}/classify/{sampleId}

Path parameters

projectId*integer

Project ID

sampleId*integer

Sample ID

Query parameters

Response

200

OK

Body

application/json

success*boolean

Whether the operation succeeded

errorstring

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

classifications*array of ClassifySampleResponseClassification (object)

sample*RawSampleData (object)

windowSizeMs*integer

Size of the sliding window (as set by the impulse) in milliseconds.

Example: 2996

windowIncreaseMs*integer

Number of milliseconds that the sliding window increased with (as set by the impulse)

Example: 10

alreadyInDatabase*boolean

Whether this sample is already in the training database

warningstring

Request

JavaScriptCurl

const response = await fetch('https://studio.edgeimpulse.com/v1/api/{projectId}/classify/{sampleId}', {
    method: 'GET',
    headers: {},
});
const data = await response.json();

Response

{
  "success": false,
  "error": "text",
  "classifications": [
    {
      "learnBlock": {
        "type": "anomaly",
        "name": "NN Classifier",
        "dsp": [
          27
        ],
        "title": "Classification (Keras)",
        "primaryVersion": false,
        "tunerPrimary": false,
        "mutated": false,
        "enabled": false,
        "db": false,
        "description": "Reduced learning rate and more layers",
        "createdBy": "createImpulse",
        "createdAt": "2024-07-04T18:27:33.804Z"
      },
      "result": [
        {
          "idle": 0.0002,
          "wave": 0.9998,
          "anomaly": -0.42
        }
      ],
      "anomalyResult": [
        {
          "boxes": [
            {
              "label": "text",
              "x": 0,
              "y": 0,
              "width": 0,
              "height": 0,
              "score": 0
            }
          ],
          "scores": [
            [
              0
            ]
          ],
          "meanScore": 0,
          "maxScore": 0
        }
      ],
      "structuredResult": [
        {
          "boxes": [
            [
              0
            ]
          ],
          "labels": [
            "text"
          ],
          "scores": [
            0
          ],
          "mAP": 0,
          "f1": 0,
          "precision": 0,
          "recall": 0,
          "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": 0,
      "details": [
        {
          "boxes": [
            [
              0
            ]
          ],
          "labels": [
            0
          ],
          "scores": [
            0
          ],
          "mAP": 0,
          "f1": 0
        }
      ],
      "objectDetectionLastLayer": "mobilenet-ssd",
      "expectedLabels": [
        {
          "label": "text"
        }
      ]
    }
  ],
  "sample": {
    "sample": {
      "id": 2,
      "filename": "idle01.d8Ae",
      "signatureValidate": true,
      "signatureMethod": "HS256",
      "signatureKey": "text",
      "created": "2024-07-04T18:27:33.804Z",
      "lastModified": "2024-07-04T18:27:33.804Z",
      "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"
        }
      ],
      "totalLengthMs": 0,
      "added": "2024-07-04T18:27:33.804Z",
      "boundingBoxes": [
        {
          "label": "text"
        }
      ],
      "boundingBoxesType": "object_detection",
      "chartType": "chart",
      "thumbnailVideo": "text",
      "thumbnailVideoFull": "text",
      "isDisabled": false,
      "isProcessing": false,
      "processingError": false,
      "processingErrorString": "text",
      "isCropped": false,
      "projectOwnerName": "text",
      "projectName": "text",
      "projectLabelingMethod": "single_label",
      "sha256Hash": "text",
      "structuredLabels": [
        {
          "label": "text"
        }
      ],
      "structuredLabelsList": [
        "text"
      ]
    },
    "payload": {
      "device_name": "ac:87:a3:0a:2d:1b",
      "device_type": "DISCO-L475VG-IOT01A",
      "sensors": [
        {
          "name": "accX",
          "units": "text"
        }
      ],
      "values": [
        [
          0
        ]
      ],
      "cropEnd": 128
    }
  },
  "windowSizeMs": 2996,
  "windowIncreaseMs": 10,
  "alreadyInDatabase": false,
  "warning": "text"
}