Export Keras block data

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

application/json

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

200

OK

Body

application/json

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

JavaScriptCurlPython

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

200

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