Single page of a classify job result
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Last updated
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Get classify job result, containing the predictions for a given page.
Project ID
Maximum number of results
Offset in results, can be used in conjunction with LimitResultsParameter to implement paging.
Keras model variant
Impulse ID. If this is unset then the default impulse is used.
If true, only a slice of labels will be returned for samples with multiple labels.
GET /v1/api/{projectId}/classify/all/result/page HTTP/1.1
Host: studio.edgeimpulse.com
x-api-key: YOUR_API_KEY
Accept: */*
OK
{
"success": true,
"error": "text",
"result": [
{
"sampleId": 1,
"sample": {
"id": 2,
"filename": "idle01.d8Ae",
"signatureValidate": true,
"signatureMethod": "HS256",
"signatureKey": "text",
"created": "2025-04-16T14:29:41.772Z",
"lastModified": "2025-04-16T14:29:41.772Z",
"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": "2025-04-16T14:29:41.772Z",
"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
}
},
"classifications": [
{
"learnBlock": {
"id": 1,
"type": "anomaly",
"name": "NN Classifier",
"dsp": [
27
],
"title": "Classification (Keras)",
"description": "Reduced learning rate and more layers",
"createdBy": "createImpulse",
"createdAt": "2025-04-16T14:29:41.772Z"
},
"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
]
]
}
]
}