EDedgeimpulse
OrganizationBlocks

Update transfer learning block

Updates a transfer learning block. Only values in the body will be updated.

post/api/organizations/{organizationId}/transfer-learning/{transferLearningId}

Request

Path parameters

organizationIdinteger required

Organization ID

transferLearningIdinteger required

Transfer learning ID

Request body

namestring
dockerContainerstring
descriptionstring
operatesOn'object_detection' | 'audio' | 'image' | 'regression' | 'anomaly_detection' | 'visual_anomaly_detection' | 'other' | 'image_akida' | 'object_detection_akida' | 'classification_akida' | 'self_contained_freeform_output'
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'
implementationVersioninteger
isPublicboolean

Whether this block is publicly available to Edge Impulse users (if false, then only for members of the owning organization)

isPublicForDevicesstring[]

If isPublic is true, the list of devices (from latencyDevices) for which this model can be shown.

publicProjectTierAvailability'enterprise-only' | 'all-projects' | 'all-projects-including-whitelabels'

For public blocks, this indicates the project tiers for which this block is available.

repositoryUrlstring

URL to the source code of this custom learn block.

parametersobject[]

List of parameters, spec'ed according to https://docs.edgeimpulse.com/docs/tips-and-tricks/adding-parameters-to-custom-blocks

imageInputScaling'0..1' | '-1..1' | '-128..127' | '0..255' | 'torch' | 'bgr-subtract-imagenet-mean'

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.

indRequiresGpuboolean

If set, requires this block to be scheduled on GPU.

displayCategory'classical' | 'tao' | 'developer-preview'

Category to display this block in the UI.

indBlockNoLongerAvailableboolean

If set, then this block is no longer available for training; and blockNoLongerAvailableReason should be set.

blockNoLongerAvailableReasonstring

In Markdown format. Should be set if indBlockNoLongerAvailable is true, contains migration information for existing users of this block.

sourceCodeDownloadStaffOnlyboolean

Whether the source code is only available for staff users.

Response

OK

successboolean required

Whether the operation succeeded

errorstring

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

Changes

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