> ## 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. # Single page of a classify job result > Get classify job result, containing the predictions for a given page. ## OpenAPI ````yaml /.assets/openapi.yaml get /api/{projectId}/classify/all/result/page 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}/classify/all/result/page: get: tags: - Classify summary: Single page of a classify job result description: Get classify job result, containing the predictions for a given page. operationId: getClassifyJobResultPage parameters: - $ref: '#/components/parameters/ProjectIdParameter' - $ref: '#/components/parameters/LimitResultsParameter' - $ref: '#/components/parameters/OffsetResultsParameter' - $ref: '#/components/parameters/ModelVariantParameter' - $ref: '#/components/parameters/OptionalImpulseIdParameter' - $ref: '#/components/parameters/TruncateStructuredLabelsParameter' - $ref: '#/components/parameters/FiltersLabelsParameter' - $ref: '#/components/parameters/FiltersFilenameParameter' - $ref: '#/components/parameters/FiltersMaxLengthParameter' - $ref: '#/components/parameters/FiltersMinLengthParameter' - $ref: '#/components/parameters/FiltersMinFrequencyParameter' - $ref: '#/components/parameters/FiltersMaxFrequencyParameter' - $ref: '#/components/parameters/FiltersSignatureParameter' - $ref: '#/components/parameters/FiltersMinLabelParameter' - $ref: '#/components/parameters/FiltersMaxLabelParameter' - $ref: '#/components/parameters/SearchQueryParameter' - $ref: '#/components/parameters/FiltersDataTypeParameter' - $ref: '#/components/parameters/FiltersMinIdParameter' - $ref: '#/components/parameters/FiltersMaxIdParameter' - $ref: '#/components/parameters/FiltersMetadataParameter' - $ref: '#/components/parameters/FiltersMinDateParameter' - $ref: '#/components/parameters/FiltersMaxDateParameter' responses: '200': description: OK content: application/json: schema: $ref: '#/components/schemas/ClassifyJobResponsePage' components: parameters: ProjectIdParameter: name: projectId in: path required: true description: Project ID schema: type: integer LimitResultsParameter: name: limit in: query required: false description: Maximum number of results schema: type: integer OffsetResultsParameter: name: offset in: query required: false description: >- Offset in results, can be used in conjunction with LimitResultsParameter to implement paging. schema: type: integer ModelVariantParameter: name: variant in: query required: false description: Keras model variant schema: $ref: '#/components/schemas/KerasModelVariantEnum' OptionalImpulseIdParameter: name: impulseId in: query required: false description: Impulse ID. If this is unset then the default impulse is used. schema: type: integer TruncateStructuredLabelsParameter: name: truncateStructuredLabels in: query required: false description: >- If true, only a slice of labels will be returned for samples with multiple labels. schema: type: boolean FiltersLabelsParameter: name: labels in: query required: false description: >- Only include samples with a label within the given list of labels, given as a JSON string schema: example: '["idle", "snake"]' type: string FiltersFilenameParameter: name: filename in: query required: false description: Only include samples whose filename includes the given filename schema: type: string FiltersMaxLengthParameter: name: maxLength in: query required: false description: Only include samples shorter than the given length, in milliseconds schema: type: integer FiltersMinLengthParameter: name: minLength in: query required: false description: Only include samples longer than the given length, in milliseconds schema: type: integer FiltersMinFrequencyParameter: name: minFrequency in: query required: false description: >- Only include samples with higher frequency than given frequency, in hertz schema: type: number FiltersMaxFrequencyParameter: name: maxFrequency in: query required: false description: Only include samples with lower frequency than given frequency, in hertz schema: type: number FiltersSignatureParameter: name: signatureValidity in: query required: false description: Include samples with either valid or invalid signatures schema: type: string enum: - both - valid - invalid FiltersMinLabelParameter: name: minLabel in: query required: false description: Only include samples with a label >= this value schema: type: number FiltersMaxLabelParameter: name: maxLabel in: query required: false description: Only include samples with a label < this value schema: type: number SearchQueryParameter: name: search in: query required: false description: Search query schema: example: type: string FiltersDataTypeParameter: name: dataType in: query required: false description: Include only samples with a particular data type schema: type: string enum: - audio - image FiltersMinIdParameter: name: minId in: query required: false description: Include only samples with an ID >= this value schema: type: integer FiltersMaxIdParameter: name: maxId in: query required: false description: Include only samples with an ID < this value schema: type: integer FiltersMetadataParameter: name: metadata in: query required: false description: > Filter samples by metadata key-value pairs, provided as a JSON string. Each item in the filter list is an object with the following properties: - "key": Metadata key to filter on. - "op": Operator ("eq" for positive match, "neq" for negative match). - "values": (optional) Array of values to match/exclude. If omitted or empty, matches/excludes all values for the key. In addition to filter objects, the following option objects can be specified: - { "no_metadata": boolean } - If true, include samples without any metadata - { "filters_combinator": ("and" | "or") } - Specifies the combinator and matching mode: - "and": All filter items must match (logical AND). - "or": Any filter item may match (logical OR); samples with metadata keys not present in the filters are included. schema: example: > Example 1: returns samples where metadata key "foo" is 'bar' or 'baz' AND metadata key "k" is "v". [ { "no_metadata": true }, { "filters_combinator": "and" }, { "key": "foo", "op": "eq", "values": ["bar", "baz"] }, { "key": "k", "op": "eq", "values": ["v"] } ] Example 2: returns samples where metadata key "foo" is not 'bar'. Samples without any metadata are filtered out. [ { "no_metadata": false }, { "filters_combinator": "or" }, { "key": "foo", "op": "neq", "values": ["bar"] } ] type: string FiltersMinDateParameter: name: minDate in: query required: false description: Only include samples that where added after the date given schema: type: string format: date-time example: '2023-01-01T00:00:00.000Z' FiltersMaxDateParameter: name: maxDate in: query required: false description: Only include samples that were added before the date given schema: type: string format: date-time example: '2024-12-31T00:00:00.000Z' schemas: ClassifyJobResponsePage: allOf: - $ref: '#/components/schemas/GenericApiResponse' - type: object required: - result - predictions - totalCount properties: result: type: array items: $ref: '#/components/schemas/ModelResult' predictions: type: array items: $ref: '#/components/schemas/ModelPrediction' totalCount: type: integer description: Total sample count KerasModelVariantEnum: type: string enum: - int8 - float32 - akida 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) ModelResult: type: object required: - sampleId - sample - classifications properties: sampleId: type: integer sample: $ref: '#/components/schemas/Sample' classifications: type: array items: $ref: '#/components/schemas/ClassifySampleResponseClassification' 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 Sample: type: object required: - id - filename - signatureValidate - created - lastModified - category - coldstorageFilename - label - intervalMs - frequency - originalIntervalMs - originalFrequency - deviceType - sensors - valuesCount - added - boundingBoxes - boundingBoxesType - chartType - isDisabled - isProcessing - processingError - isCropped - projectId - sha256Hash - datastreams properties: id: type: integer example: 2 filename: type: string example: idle01.d8Ae signatureValidate: type: boolean description: Whether signature validation passed example: true signatureMethod: type: string example: HS256 signatureKey: type: string description: >- Either the shared key or the public key that was used to validate the sample created: type: string format: date-time description: >- Timestamp when the sample was created on device, or if no accurate time was known on device, the time that the file was processed by the ingestion service. lastModified: type: string format: date-time description: Timestamp when the sample was last modified. category: $ref: '#/components/schemas/RawDataCategory' example: training coldstorageFilename: type: string label: type: string example: healthy-machine intervalMs: type: number description: >- Interval between two windows (1000 / frequency). NOTE: Previously this value could change depending on whether the sample was resampled. This behavior has been removed. example: 16 frequency: type: number description: >- Frequency of the sample. NOTE: Previously this value could change depending on whether the sample was resampled. This behavior has been removed. example: 62.5 originalIntervalMs: type: number description: DEPRECATED. See "intervalMs". example: 16 originalFrequency: type: number description: DEPRECATED. See "frequency". example: 62.5 deviceName: type: string deviceType: type: string sensors: type: array items: $ref: '#/components/schemas/Sensor' valuesCount: type: integer description: >- Number of readings in this file. If you have multiple datastreams, this is the value count from the datastream with the highest frequency. totalLengthMs: type: number description: Total length (in ms.) of this file added: type: string format: date-time description: >- Timestamp when the sample was added to the current acquisition bucket. boundingBoxes: type: array items: $ref: '#/components/schemas/BoundingBox' boundingBoxesType: type: string enum: - object_detection - constrained_object_detection chartType: type: string enum: - chart - image - video - table thumbnailVideo: type: string thumbnailVideoFull: type: string isDisabled: type: boolean description: True if the current sample is excluded from use isProcessing: type: boolean description: True if the current sample is still processing (e.g. for video) processingJobId: type: integer description: Set when sample is processing and a job has picked up the request processingError: type: boolean description: Set when processing this sample failed processingErrorString: type: string description: Error (only set when processing this sample failed) isCropped: type: boolean description: >- Whether the sample is cropped from another sample (and has crop start / end info) metadata: type: object description: Sample free form associated metadata additionalProperties: type: string projectId: type: integer description: Unique identifier of the project this sample belongs to projectOwnerName: type: string description: Name of the owner of the project this sample belongs to projectName: type: string description: Name of the project this sample belongs to projectLabelingMethod: $ref: '#/components/schemas/ProjectLabelingMethod' description: What labeling flow the project this sample belongs to uses sha256Hash: type: string description: Data sample SHA 256 hash (including CBOR envelope if applicable) structuredLabels: type: array items: $ref: '#/components/schemas/StructuredLabel' structuredLabelsList: type: array items: type: string createdBySyntheticDataJobId: type: integer description: >- If this sample was created by a synthetic data job, it's referenced here. imageDimensions: type: object required: - width - height properties: width: type: integer height: type: integer videoUrl: type: string description: Video link, cropped and in original resolution. videoUrlFull: type: string description: Video link in original resolution. labelMap: $ref: '#/components/schemas/SampleLabelMapLabels' datastreams: type: array items: $ref: '#/components/schemas/SampleDatastream' ClassifySampleResponseClassification: type: object required: - learnBlock - result - expectedLabels - minimumConfidenceRating - thresholds - intervalMs - frequencyHz properties: learnBlock: $ref: '#/components/schemas/ImpulseLearnBlock' result: type: array description: Classification result, one item per window. example: - idle: 0.0002 wave: 0.9998 anomaly: -0.42 items: type: object description: >- Classification value per label. For a neural network this will be the confidence, for anomalies the anomaly score. additionalProperties: type: number anomalyResult: type: array description: >- Anomaly scores and computed metrics for visual anomaly detection, one item per window. items: $ref: '#/components/schemas/AnomalyResult' structuredResult: type: array description: >- Results of inferencing that returns structured data, such as object detection items: $ref: '#/components/schemas/StructuredClassifyResult' minimumConfidenceRating: type: number description: >- DEPRECATED, see "thresholds" instead. The minimum confidence rating for this block. For regression, this is the absolute error (which can be larger than 1). details: type: array description: >- Structured outputs and computed metrics for some model types (e.g. object detection), one item per window. items: $ref: '#/components/schemas/ClassifySampleResponseClassificationDetails' objectDetectionLastLayer: $ref: '#/components/schemas/ObjectDetectionLastLayer' expectedLabels: type: array description: An array with an expected label per window. items: $ref: '#/components/schemas/StructuredLabel' expectedAnomalyOutcome: type: array description: > An array with the expected anomaly outcome for each window — either “anomaly” or “no anomaly”. The outcome is determined by which labels are marked as anomalous in the project setup, or by the sample label if no such configuration is defined. items: $ref: '#/components/schemas/StructuredLabel' thresholds: type: array description: List of configurable thresholds for this block. items: $ref: '#/components/schemas/BlockThreshold' isMultiLabel: type: boolean intervalMs: description: Interval between two windows in "expectedLabels" (1000 / frequency). type: number frequencyHz: description: Frequency of the windows in "expectedLabels" type: number 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 RawDataCategory: type: string enum: - training - testing - validation - post-processing Sensor: type: object required: - index - name - units properties: index: type: integer description: >- Index of the sensor (globally, so you can refer back to it in e.g. getSampleAsAudio) name: type: string description: Name of the axis example: accX units: type: string description: >- Type of data on this axis. Needs to comply to SenML units (see https://www.iana.org/assignments/senml/senml.xhtml). BoundingBox: type: object description: >- This has the _absolute values_ for x/y/w/h (so 0..x (where x is the w/h of the image)) required: - label - x - 'y' - width - height properties: label: type: string x: type: integer 'y': type: integer width: type: integer height: type: integer ProjectLabelingMethod: type: string enum: - single_label - object_detection - label_map StructuredLabel: type: object description: >- A structured label contains a label, and the range for which this label is valid. `endIndex` is inclusive. E.g. `{ startIndex: 10, endIndex: 13, label: 'running' }` means that the values at index 10, 11, 12, 13 are labeled 'running'. To get time codes you can multiple by the sample's `intervalMs` property. required: - startIndex - endIndex - label properties: startIndex: type: integer description: Start index of the label (e.g. 0) endIndex: type: integer description: >- End index of the label (e.g. 3). This value is inclusive, so { startIndex: 0, endIndex: 3 } covers 0, 1, 2, 3. label: type: string description: The label for this section. labelMap: $ref: '#/components/schemas/SampleLabelMapLabels' SampleLabelMapLabels: description: > Structured sample labels in the form of a key-value map. This property is optional and only defined for samples with key-value labels. discriminator: propertyName: type mapping: key-values: $ref: '#/components/schemas/SampleKeyValueLabels' oneOf: - $ref: '#/components/schemas/SampleKeyValueLabels' SampleDatastream: type: object required: - index - chartType - intervalMs - frequencyHz - sensors - valuesCount - totalLengthMs properties: index: type: integer chartType: type: string enum: - chart - image - video - table intervalMs: description: Interval between two windows (1000 / frequency). type: number frequencyHz: description: Frequency of the datastream type: number sensors: type: array items: $ref: '#/components/schemas/Sensor' valuesCount: type: integer description: Number of readings in this datastream. imageDimensions: type: object required: - width - height properties: width: type: integer height: type: integer totalLengthMs: type: number description: Total length (in ms.) of the datastream ImpulseLearnBlock: type: object required: - id - type - name - dsp - title properties: id: type: integer minimum: 1 description: >- Identifier for this block. Make sure to up this number when creating a new block via `getNewBlockId`, and don't re-use identifiers. If the block hasn't changed, keep the ID as-is. ID must be unique across the project and greather than zero (>0). type: $ref: '#/components/schemas/LearnBlockType' name: type: string description: >- Block name, will be used in menus. If a block has a baseBlockId, this field is ignored and the base block's name is used instead. example: NN Classifier dsp: type: array description: DSP dependencies, identified by DSP block ID items: type: integer example: 27 title: type: string description: Block title, used in the impulse UI example: Classification (Keras) createdBy: type: string description: >- The system component that created the block version (createImpulse | clone | tuner). Cannot be set via API. example: createImpulse createdAt: type: string format: date-time description: >- The datetime that the block version was created. Cannot be set via API. trainingProcessor: $ref: '#/components/schemas/ExperimentalImpulseSpecificGpuTrainingProcessor' AnomalyResult: type: object properties: boxes: type: array description: >- For visual anomaly detection. An array of bounding box objects, (x, y, width, height, score, label), one per detection in the image. Filtered by the minimum confidence rating of the learn block. items: $ref: '#/components/schemas/BoundingBoxWithScore' scores: type: array description: >- 2D array of shape (n, n) with raw anomaly scores for visual anomaly detection, where n can be calculated as ((1/8 of image input size)/2 - 1). The scores corresponds to each grid cell in the image's spatial matrix. items: type: array items: type: number meanScore: type: number description: Mean value of the scores. maxScore: type: number description: Maximum value of the scores. StructuredClassifyResult: type: object required: - boxes - scores - mAP - f1 - precision - recall properties: boxes: type: array description: >- For object detection. An array of bounding box arrays, (x, y, width, height), one per detection in the image. items: type: array items: type: number labels: type: array description: >- For object detection. An array of labels, one per detection in the image. items: type: string scores: type: array description: >- For object detection. An array of probability scores, one per detection in the image. items: type: number mAP: type: number description: >- For object detection. A score that indicates accuracy compared to the ground truth, if available. f1: type: number description: >- For FOMO. A score that combines the precision and recall of a classifier into a single metric, if available. precision: type: number description: >- A measure of how many of the positive predictions made are correct (true positives). recall: type: number description: >- A measure of how many of the positive cases the classifier correctly predicted, over all the positive cases. debugInfoJson: type: string description: Debug info in JSON format example: | { "y_trues": [ {"x": 0.854, "y": 0.453125, "label": 1}, {"x": 0.197, "y": 0.53125, "label": 2} ], "y_preds": [ {"x": 0.916, "y": 0.875, "label": 1}, {"x": 0.25, "y": 0.541, "label": 2} ], "assignments": [ {"yp": 1, "yt": 1, "label": 2, "distance": 0.053} ], "normalised_min_distance": 0.2, "all_pairwise_distances": [ [0, 0, 0.426], [1, 1, 0.053] ], "unassigned_y_true_idxs": [0], "unassigned_y_pred_idxs": [0] } ClassifySampleResponseClassificationDetails: type: object properties: boxes: type: array description: Bounding boxes predicted by localization model items: type: array items: type: number labels: type: array description: Labels predicted by localization model items: type: number scores: type: array description: Scores predicted by localization model items: type: number mAP: type: number description: >- For object detection, the COCO mAP computed for the predictions on this image f1: type: number description: For FOMO, the F1 score computed for the predictions on this image ObjectDetectionLastLayer: type: string enum: - mobilenet-ssd - fomo - yolov2-akida - yolov5 - yolov5v5-drpai - yolox - yolov7 - yolo-pro - tao-retinanet - tao-ssd - tao-yolov3 - tao-yolov4 - yolov11 - yolov11-abs - paddleocr-detector - qc-face-det-lite 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" SampleKeyValueLabels: type: object required: - type - labels properties: type: type: string enum: - key-values labels: type: object additionalProperties: type: string LearnBlockType: type: string description: >- The type of learning block (anomaly, keras, keras-transfer-image, keras-transfer-kws, keras-object-detection, keras-regression, keras-freeform). Each behaves differently. enum: - anomaly - anomaly-gmm - keras - keras-transfer-image - keras-transfer-kws - keras-object-detection - keras-regression - keras-akida - keras-akida-transfer-image - keras-akida-object-detection - keras-visual-anomaly - keras-freeform - keras-anomaly - vlm ExperimentalImpulseSpecificGpuTrainingProcessor: type: string description: > EXPERIMENTAL: Training processor for the impulse-specific-gpu rollout. This field is currently gated by a project experiment and may change in future API versions. enum: - cpu - gpu 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 ````