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.

get

/api/{projectId}/classify/{sampleId}

Authorizations

ApiKeyAuthenticationJWTAuthenticationJWTHttpHeaderAuthentication

Path parameters

projectIdintegerrequired

Project ID

sampleIdintegerrequired

Sample ID

Query parameters

includeDebugInfoboolean

Whether to return the debug information from FOMO classification.

impulseIdinteger

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

Responses

application/json

cURL

JavaScript

Python

HTTP

cURL

curl -L \
  --url 'https://studio.edgeimpulse.com/v1/api/{projectId}/classify/{sampleId}' \
  --header 'x-api-key: YOUR_API_KEY'

200

200

{
  "success": true,
  "error": "text",
  "sample": {
    "sample": {
      "id": 2,
      "filename": "idle01.d8Ae",
      "signatureValidate": true,
      "signatureMethod": "HS256",
      "signatureKey": "text",
      "created": "2025-02-21T18:03:05.655Z",
      "lastModified": "2025-02-21T18:03:05.655Z",
      "category": "training",
      "coldstorageFilename": "text",
      "label": "healthy-machine",
      "intervalMs": 16,
      "frequency": 62.5,
      "originalIntervalMs": 16,
      "originalFrequency": 62.5,
      "deviceName": "text",
      "deviceType": "text",
      "valuesCount": 1,
      "totalLengthMs": 1,
      "added": "2025-02-21T18:03:05.655Z",
      "thumbnailVideo": "text",
      "thumbnailVideoFull": "text",
      "isDisabled": true,
      "isProcessing": true,
      "processingJobId": 1,
      "processingError": true,
      "processingErrorString": "text",
      "isCropped": true,
      "projectId": 1,
      "projectOwnerName": "text",
      "projectName": "text",
      "sha256Hash": "text",
      "createdBySyntheticDataJobId": 1,
      "boundingBoxesType": "object_detection",
      "chartType": "chart",
      "projectLabelingMethod": "single_label",
      "sensors": [
        {
          "name": "accX",
          "units": "text"
        }
      ],
      "boundingBoxes": [
        {
          "label": "text",
          "x": 1,
          "y": 1,
          "width": 1,
          "height": 1
        }
      ],
      "metadata": {
        "ANY_ADDITIONAL_PROPERTY": "text"
      },
      "structuredLabels": [
        {
          "startIndex": 1,
          "endIndex": 1,
          "label": "text"
        }
      ],
      "structuredLabelsList": [
        "text"
      ],
      "imageDimensions": {
        "width": 1,
        "height": 1
      }
    },
    "payload": {
      "device_name": "ac:87:a3:0a:2d:1b",
      "device_type": "DISCO-L475VG-IOT01A",
      "cropStart": 0,
      "cropEnd": 128,
      "sensors": [
        {
          "name": "accX",
          "units": "text"
        }
      ],
      "values": [
        [
          1
        ]
      ]
    },
    "totalPayloadLength": 1
  },
  "windowSizeMs": 2996,
  "windowIncreaseMs": 10,
  "alreadyInDatabase": true,
  "warning": "text",
  "classifications": [
    {
      "learnBlock": {
        "id": 1,
        "type": "anomaly",
        "name": "NN Classifier",
        "title": "Classification (Keras)",
        "description": "Reduced learning rate and more layers",
        "createdBy": "createImpulse",
        "createdAt": "2025-02-21T18:03:05.655Z",
        "dsp": [
          27
        ]
      },
      "minimumConfidenceRating": 1,
      "objectDetectionLastLayer": "mobilenet-ssd",
      "anomalyResult": [
        {
          "meanScore": 1,
          "maxScore": 1,
          "boxes": [
            {
              "label": "text",
              "x": 1,
              "y": 1,
              "width": 1,
              "height": 1,
              "score": 1
            }
          ],
          "scores": [
            [
              1
            ]
          ]
        }
      ],
      "structuredResult": [
        {
          "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",
          "labels": [
            "text"
          ],
          "scores": [
            1
          ],
          "boxes": [
            [
              1
            ]
          ]
        }
      ],
      "details": [
        {
          "mAP": 1,
          "f1": 1,
          "labels": [
            1
          ],
          "scores": [
            1
          ],
          "boxes": [
            [
              1
            ]
          ]
        }
      ],
      "expectedLabels": [
        {
          "startIndex": 1,
          "endIndex": 1,
          "label": "text"
        }
      ],
      "result": [
        {
          "idle": 0.0002,
          "wave": 0.9998,
          "anomaly": -0.42
        }
      ]
    }
  ]
}

OK