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.

post

/api/{projectId}/jobs/train/keras/{learnId}/data

Authorizations

ApiKeyAuthenticationJWTAuthenticationJWTHttpHeaderAuthentication

Path parameters

projectIdintegerrequired

Project ID

learnIdintegerrequired

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

Body

overrideImageInputScalingstring · 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.

Options: 0..1, -1..1, -128..127, 0..255, torch, bgr-subtract-imagenet-mean

Responses

application/json

cURL

JavaScript

Python

HTTP

cURL

curl -L \
  --request POST \
  --url 'https://studio.edgeimpulse.com/v1/api/{projectId}/jobs/train/keras/{learnId}/data' \
  --header 'x-api-key: YOUR_API_KEY' \
  --header 'Content-Type: application/json' \
  --data '{"overrideImageInputScaling":"0..1"}'

200

200

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

OK