POST
/
api
/
{projectId}
/
classify
/
v2
/
{sampleId}
Classify sample
curl --request POST \
  --url https://studio.edgeimpulse.com/v1/api/{projectId}/classify/v2/{sampleId} \
  --header 'x-api-key: <api-key>'
{
  "success": true,
  "error": "<string>",
  "classifications": [
    {
      "learnBlock": {
        "id": 2,
        "type": "anomaly",
        "name": "NN Classifier",
        "dsp": [
          27
        ],
        "title": "Classification (Keras)",
        "createdBy": "createImpulse",
        "createdAt": "2023-11-07T05:31:56Z"
      },
      "result": [
        {
          "idle": 0.0002,
          "wave": 0.9998,
          "anomaly": -0.42
        }
      ],
      "anomalyResult": [
        {
          "boxes": [
            {
              "label": "<string>",
              "x": 123,
              "y": 123,
              "width": 123,
              "height": 123,
              "score": 123
            }
          ],
          "scores": [
            [
              123
            ]
          ],
          "meanScore": 123,
          "maxScore": 123
        }
      ],
      "structuredResult": [
        {
          "boxes": [
            [
              123
            ]
          ],
          "labels": [
            "<string>"
          ],
          "scores": [
            123
          ],
          "mAP": 123,
          "f1": 123,
          "precision": 123,
          "recall": 123,
          "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": 123,
      "details": [
        {
          "boxes": [
            [
              123
            ]
          ],
          "labels": [
            123
          ],
          "scores": [
            123
          ],
          "mAP": 123,
          "f1": 123
        }
      ],
      "objectDetectionLastLayer": "mobilenet-ssd",
      "expectedLabels": [
        {
          "startIndex": 123,
          "endIndex": 123,
          "label": "<string>"
        }
      ],
      "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": 123,
          "suggestedValueText": "<string>",
          "value": 0.5
        }
      ]
    }
  ],
  "sample": {
    "sample": {
      "id": 2,
      "filename": "idle01.d8Ae",
      "signatureValidate": true,
      "signatureMethod": "HS256",
      "signatureKey": "<string>",
      "created": "2023-11-07T05:31:56Z",
      "lastModified": "2023-11-07T05:31:56Z",
      "category": "training",
      "coldstorageFilename": "<string>",
      "label": "healthy-machine",
      "intervalMs": 16,
      "frequency": 62.5,
      "originalIntervalMs": 16,
      "originalFrequency": 62.5,
      "deviceName": "<string>",
      "deviceType": "<string>",
      "sensors": [
        {
          "name": "accX",
          "units": "<string>"
        }
      ],
      "valuesCount": 123,
      "totalLengthMs": 123,
      "added": "2023-11-07T05:31:56Z",
      "boundingBoxes": [
        {
          "label": "<string>",
          "x": 123,
          "y": 123,
          "width": 123,
          "height": 123
        }
      ],
      "boundingBoxesType": "object_detection",
      "chartType": "chart",
      "thumbnailVideo": "<string>",
      "thumbnailVideoFull": "<string>",
      "isDisabled": true,
      "isProcessing": true,
      "processingJobId": 123,
      "processingError": true,
      "processingErrorString": "<string>",
      "isCropped": true,
      "metadata": {},
      "projectId": 123,
      "projectOwnerName": "<string>",
      "projectName": "<string>",
      "projectLabelingMethod": "single_label",
      "sha256Hash": "<string>",
      "structuredLabels": [
        {
          "startIndex": 123,
          "endIndex": 123,
          "label": "<string>"
        }
      ],
      "structuredLabelsList": [
        "<string>"
      ],
      "createdBySyntheticDataJobId": 123,
      "imageDimensions": {
        "width": 123,
        "height": 123
      },
      "videoUrl": "<string>",
      "videoUrlFull": "<string>"
    },
    "payload": {
      "device_name": "ac:87:a3:0a:2d:1b",
      "device_type": "DISCO-L475VG-IOT01A",
      "sensors": [
        {
          "name": "accX",
          "units": "<string>"
        }
      ],
      "values": [
        [
          123
        ]
      ],
      "cropStart": 0,
      "cropEnd": 128
    },
    "totalPayloadLength": 123
  },
  "windowSizeMs": 2996,
  "windowIncreaseMs": 10,
  "alreadyInDatabase": true,
  "warning": "<string>"
}

Authorizations

x-api-key
string
header
required

Path Parameters

projectId
integer
required

Project ID

sampleId
integer
required

Sample ID

Query Parameters

includeDebugInfo
boolean

Whether to return the debug information from FOMO classification.

variant
enum<string>

Keras model variant

Available options:
int8,
float32,
akida
impulseId
integer

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

truncateStructuredLabels
boolean

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

Response

200 - application/json

OK

The response is of type object.