Export Keras block data

Export the data of a Keras block (already split in train/validate data). Updates are streamed over the websocket API.

POSThttps://studio.edgeimpulse.com/v1/api/{projectId}/jobs/train/keras/{learnId}/data

Path parameters

projectId*integer

Project ID

learnId*integer

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

Body

overrideImageInputScalingImageInputScaling (enum)

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.

0..1-1..1-128..1270..255torchbgr-subtract-imagenet-mean

Response

Body

success*boolean

Whether the operation succeeded

errorstring

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

id*integer

Job identifier. Status updates will include this identifier.

Example: 12873488112

Request

const response = await fetch('https://studio.edgeimpulse.com/v1/api/{projectId}/jobs/train/keras/{learnId}/data', {
    method: 'POST',
    headers: {
      "Content-Type": "application/json"
    },
    body: JSON.stringify({}),
});
const data = await response.json();

Response

{
  "success": false,
  "error": "text",
  "id": 12873488112
}