curl --request GET \
--url https://studio.edgeimpulse.com/v1/api/{projectId}/training/anomaly/{learnId}/metadata \
--header 'x-api-key: <api-key>'
{
"success": true,
"error": "<string>",
"created": "2023-11-07T05:31:56Z",
"scale": [
123
],
"mean": [
123
],
"clusters": [
{
"center": [
123
],
"maxError": 123
}
],
"axes": "`[ 0, 11, 22 ]`",
"defaultMinimumConfidenceRating": 123,
"availableModelTypes": [
"int8"
],
"recommendedModelType": "int8",
"modelValidationMetrics": [
{
"type": "int8",
"loss": 123,
"accuracy": 123,
"confusionMatrix": [
[
31,
1,
0
],
[
2,
27,
3
],
[
1,
0,
39
]
],
"report": {},
"onDevicePerformance": [
{
"mcu": "<string>",
"name": "<string>",
"isDefault": true,
"latency": 123,
"tflite": {
"ramRequired": 123,
"romRequired": 123,
"arenaSize": 123,
"modelSize": 123
},
"eon": {
"ramRequired": 123,
"romRequired": 123,
"arenaSize": 123,
"modelSize": 123
},
"eon_ram_optimized": {
"ramRequired": 123,
"romRequired": 123,
"arenaSize": 123,
"modelSize": 123
},
"customMetrics": [
{
"name": "<string>",
"value": "<string>"
}
],
"hasPerformance": true,
"profilingError": "<string>"
}
],
"predictions": [
{
"sampleId": 123,
"startMs": 123,
"endMs": 123,
"label": "<string>",
"prediction": "<string>",
"predictionCorrect": true,
"f1Score": 123,
"anomalyScores": [
[
123
]
]
}
],
"visualization": "featureExplorer",
"isSupportedOnMcu": true,
"mcuSupportError": "<string>",
"profilingJobId": 123,
"profilingJobFailed": true,
"additionalMetrics": [
{
"name": "<string>",
"value": "<string>",
"fullPrecisionValue": 123,
"tooltipText": "<string>",
"link": "<string>"
}
]
}
],
"hasTrainedModel": true,
"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
}
]
}
Get metadata about a trained anomaly block. Use the impulse blocks to find the learnId.
curl --request GET \
--url https://studio.edgeimpulse.com/v1/api/{projectId}/training/anomaly/{learnId}/metadata \
--header 'x-api-key: <api-key>'
{
"success": true,
"error": "<string>",
"created": "2023-11-07T05:31:56Z",
"scale": [
123
],
"mean": [
123
],
"clusters": [
{
"center": [
123
],
"maxError": 123
}
],
"axes": "`[ 0, 11, 22 ]`",
"defaultMinimumConfidenceRating": 123,
"availableModelTypes": [
"int8"
],
"recommendedModelType": "int8",
"modelValidationMetrics": [
{
"type": "int8",
"loss": 123,
"accuracy": 123,
"confusionMatrix": [
[
31,
1,
0
],
[
2,
27,
3
],
[
1,
0,
39
]
],
"report": {},
"onDevicePerformance": [
{
"mcu": "<string>",
"name": "<string>",
"isDefault": true,
"latency": 123,
"tflite": {
"ramRequired": 123,
"romRequired": 123,
"arenaSize": 123,
"modelSize": 123
},
"eon": {
"ramRequired": 123,
"romRequired": 123,
"arenaSize": 123,
"modelSize": 123
},
"eon_ram_optimized": {
"ramRequired": 123,
"romRequired": 123,
"arenaSize": 123,
"modelSize": 123
},
"customMetrics": [
{
"name": "<string>",
"value": "<string>"
}
],
"hasPerformance": true,
"profilingError": "<string>"
}
],
"predictions": [
{
"sampleId": 123,
"startMs": 123,
"endMs": 123,
"label": "<string>",
"prediction": "<string>",
"predictionCorrect": true,
"f1Score": 123,
"anomalyScores": [
[
123
]
]
}
],
"visualization": "featureExplorer",
"isSupportedOnMcu": true,
"mcuSupportError": "<string>",
"profilingJobId": 123,
"profilingJobFailed": true,
"additionalMetrics": [
{
"name": "<string>",
"value": "<string>",
"fullPrecisionValue": 123,
"tooltipText": "<string>",
"link": "<string>"
}
]
}
],
"hasTrainedModel": true,
"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
}
]
}
Project ID
Learn Block ID, use the impulse functions to retrieve the ID
OK
The response is of type object
.