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Keras metadata

Get metadata about a trained Keras block. Use the impulse blocks to find the learnId.

get/api/{projectId}/training/keras/{learnId}/metadata

Request

Path parameters

projectIdinteger required

Project ID

learnIdinteger required

Learn Block ID, use the impulse functions to retrieve the ID

Query parameters

excludeLabelsboolean

If set to "true", the "labels" field is left empty (which can be big on e.g. regression projects).

Response

OK

successboolean required

Whether the operation succeeded

errorstring

Optional error description (set if 'success' was false)

createdstring date-time required

Date when the model was trained

classNamesstring[] required

Labels for the output layer

labelsstring[] required

Original labels in the dataset when features were generated, e.g. used to render the feature explorer.

availableModelTypesKerasModelTypeEnum[] required

The types of model that are available

recommendedModelType'int8' | 'float32' | 'akida' | 'requiresRetrain' required
hasTrainedModelboolean required
mode'classification' | 'regression' | 'object-detection' | 'visual-anomaly' | 'anomaly-gmm' | 'freeform' | 'anomaly' required
objectDetectionLastLayer'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' | 'qc-yolox'
imageInputScaling'0..1' | '-1..1' | '-128..127' | '0..255' | 'torch' | 'bgr-subtract-imagenet-mean' required

Normalization that is applied to images. If this is not set then 0..1 is used. "0..1" gives you non-normalized pixels between 0 and 1. "-1..1" gives you non-normalized pixels between -1 and 1. "0..255" gives you non-normalized pixels between 0 and 255. "-128..127" gives you non-normalized pixels between -128 and 127. "torch" first scales pixels between 0 and 1, then applies normalization using the ImageNet dataset (same as torchvision.transforms.Normalize()). "bgr-subtract-imagenet-mean" scales to 0..255, reorders pixels to BGR, and subtracts the ImageNet mean from each channel.

Changes

No recorded changes to this operation across all 1 revision of this API.