> ## Documentation Index > Fetch the complete documentation index at: https://docs.edgeimpulse.com/llms.txt > Use this file to discover all available pages before exploring further. # Anomaly metadata > Get metadata about a trained anomaly block. Use the impulse blocks to find the learnId. ## OpenAPI ````yaml /.assets/openapi.yaml get /api/{projectId}/training/anomaly/{learnId}/metadata openapi: 3.0.0 info: title: Edge Impulse API version: 1.0.0 servers: - url: https://studio.edgeimpulse.com/v1 security: - ApiKeyAuthentication: [] - JWTAuthentication: [] - JWTHttpHeaderAuthentication: [] - OAuth2: [] paths: /api/{projectId}/training/anomaly/{learnId}/metadata: get: tags: - Learn summary: Anomaly metadata description: >- Get metadata about a trained anomaly block. Use the impulse blocks to find the learnId. operationId: getAnomalyMetadata parameters: - $ref: '#/components/parameters/ProjectIdParameter' - $ref: '#/components/parameters/LearnIdParameter' responses: '200': description: OK content: application/json: schema: $ref: '#/components/schemas/AnomalyModelMetadataResponse' components: parameters: ProjectIdParameter: name: projectId in: path required: true description: Project ID schema: type: integer LearnIdParameter: name: learnId in: path required: true description: Learn Block ID, use the impulse functions to retrieve the ID schema: type: integer schemas: AnomalyModelMetadataResponse: allOf: - $ref: '#/components/schemas/GenericApiResponse' - $ref: '#/components/schemas/AnomalyModelMetadata' GenericApiResponse: type: object required: - success properties: success: type: boolean description: Whether the operation succeeded error: type: string description: Optional error description (set if 'success' was false) AnomalyModelMetadata: type: object required: - created - scale - mean - clusters - axes - defaultMinimumConfidenceRating - thresholds properties: created: type: string format: date-time description: Date when the model was trained scale: type: array description: >- Scale input for StandardScaler. Values are scaled like this (where `ix` is axis index): `input[ix] = (input[ix] - mean[ix]) / scale[ix];` items: type: number mean: type: array description: >- Mean input for StandardScaler. Values are scaled like this (where `ix` is axis index): `input[ix] = (input[ix] - mean[ix]) / scale[ix];` items: type: number clusters: type: array description: Trained K-means clusters items: type: object required: - center - maxError properties: center: type: array description: Center of each cluster (one value per axis) items: type: number maxError: type: number description: Size of the cluster axes: type: array description: Which axes were included during training (by index) example: '`[ 0, 11, 22 ]`' items: type: integer defaultMinimumConfidenceRating: type: number description: >- DEPRECATED, see "thresholds" instead. Default minimum confidence rating required before tagging as anomaly, based on scores of training data (GMM only). availableModelTypes: type: array description: The types of model that are available items: $ref: '#/components/schemas/KerasModelTypeEnum' recommendedModelType: $ref: '#/components/schemas/KerasModelTypeEnum' description: The model type that is recommended for use modelValidationMetrics: type: array description: Metrics for each of the available model types items: $ref: '#/components/schemas/KerasModelMetadataMetrics' hasTrainedModel: type: boolean thresholds: type: array description: List of configurable thresholds for this block. items: $ref: '#/components/schemas/BlockThreshold' KerasModelTypeEnum: type: string enum: - int8 - float32 - akida - requiresRetrain KerasModelMetadataMetrics: type: object required: - type - loss - confusionMatrix - report - onDevicePerformance - visualization - isSupportedOnMcu - additionalMetrics properties: type: $ref: '#/components/schemas/KerasModelTypeEnum' description: The type of model loss: type: number description: The model's loss on the validation set after training accuracy: type: number description: The model's accuracy on the validation set after training confusionMatrix: type: array example: - - 31 - 1 - 0 - - 2 - 27 - 3 - - 1 - 0 - 39 items: type: array items: type: number report: type: object description: Precision, recall, F1 and support scores onDevicePerformance: type: array items: type: object required: - mcu - name - isDefault - latency - tflite - eon - hasPerformance properties: mcu: type: string name: type: string isDefault: type: boolean latency: type: number tflite: type: object required: - ramRequired - romRequired - arenaSize - modelSize properties: ramRequired: type: integer romRequired: type: integer arenaSize: type: integer modelSize: type: integer eon: type: object required: - ramRequired - romRequired - arenaSize - modelSize properties: ramRequired: type: integer romRequired: type: integer arenaSize: type: integer modelSize: type: integer eon_ram_optimized: type: object required: - ramRequired - romRequired - arenaSize - modelSize properties: ramRequired: type: integer romRequired: type: integer arenaSize: type: integer modelSize: type: integer customMetrics: description: Custom, device-specific performance metrics type: array items: $ref: '#/components/schemas/KerasCustomMetric' hasPerformance: description: If false, then no metrics are available for this target type: boolean profilingError: description: Specific error during profiling (e.g. model not supported) type: string predictions: type: array items: $ref: '#/components/schemas/ModelPrediction' visualization: type: string enum: - featureExplorer - dataExplorer - none isSupportedOnMcu: type: boolean mcuSupportError: type: string profilingJobId: description: >- If this is set, then we're still profiling this model. Subscribe to job updates to see when it's done (afterward the metadata will be updated). type: integer profilingJobFailed: description: >- If this is set, then the profiling job failed (get the status by getting the job logs for 'profilingJobId'). type: boolean additionalMetrics: type: array items: $ref: '#/components/schemas/AdditionalMetric' BlockThreshold: type: object description: >- Configurable threshold for this block (e.g. minimum score before tagging as an anomaly, or the min. score to save bounding boxes) required: - key - description - helpText - value properties: key: type: string description: >- Identifier to reference the threshold. You'll need to refer to the threshold by this key when you set the threshold). example: min_score description: type: string description: User-friendly description of the threshold. example: Score threshold helpText: type: string description: Additional help text (shown in the UI under a "?" icon) example: >- Threshold score for bounding boxes. If the score for a bounding box is below this the box will be discarded. suggestedValue: type: number description: >- If the threshold has a suggested value, e.g. a max. absolute error for regression projects; or the min. anomaly score for visual anomaly detection, then this is the numeric value of that threshold. suggestedValueText: type: string description: >- If the threshold has a suggested value, e.g. a max. absolute error for regression projects; or the min. anomaly score for visual anomaly detection, then this is the stringified value of that threshold. value: description: Current value of the threshold example: 0.5 oneOf: - type: number - type: string dropdownOptions: description: Optional list of options, will be shown in a dropdown. type: array items: type: object required: - description - value properties: description: type: string description: Full description of the value value: type: string description: Value, maps back to "BlockThreshold#value" KerasCustomMetric: type: object required: - name - value properties: name: description: The name of the metric type: string value: description: The value of this metric for this model type type: string ModelPrediction: type: object required: - sampleId - startMs - endMs - prediction properties: sampleId: type: integer startMs: type: number endMs: type: number label: type: string prediction: type: string predictionCorrect: type: boolean f1Score: type: number description: Only set for object detection projects anomalyScores: type: array description: >- Only set for visual anomaly projects. 2D array of shape (n, n) with raw anomaly scores, where n varies based on the image input size and the specific visual anomaly algorithm used. The scores corresponds to each grid cell in the image's spatial matrix. items: type: array items: type: number boundingBoxes: type: array description: >- Only set for object detection projects. Coordinates are scaled 0..1, not absolute values. items: $ref: '#/components/schemas/BoundingBoxWithScore' labelMapPredictions: type: object description: >- For samples with structured labels (in the form of a key/value label map), this object will contain per-key prediction info for the sample. additionalProperties: type: string AdditionalMetric: type: object required: - name - value - fullPrecisionValue properties: name: type: string value: type: string fullPrecisionValue: type: number tooltipText: type: string link: type: string BoundingBoxWithScore: type: object description: This has the _ratio_ for x/y/w/h (so 0..1) required: - label - x - 'y' - width - height - score properties: label: type: string x: type: number 'y': type: number width: type: number height: type: number score: type: number securitySchemes: ApiKeyAuthentication: type: apiKey in: header name: x-api-key JWTAuthentication: type: apiKey in: cookie name: jwt JWTHttpHeaderAuthentication: type: apiKey in: header name: x-jwt-token OAuth2: type: oauth2 flows: authorizationCode: authorizationUrl: /v1/oauth/authorize tokenUrl: /v1/oauth/token scopes: openid: Access to basic profile information email: Access to email address profile: Access to full profile information implicit: authorizationUrl: /v1/oauth/authorize scopes: openid: Access to basic profile information email: Access to email address profile: Access to full profile information password: tokenUrl: /v1/oauth/token scopes: openid: Access to basic profile information email: Access to email address profile: Access to full profile information clientCredentials: tokenUrl: /v1/oauth/token scopes: openid: Access to basic profile information email: Access to email address profile: Access to full profile information ````