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POST
/
api
/
{projectId}
/
pretrained-model
/
upload
Upload a pretrained model
curl --request POST \
  --url https://studio.edgeimpulse.com/v1/api/{projectId}/pretrained-model/upload \
  --header 'Content-Type: multipart/form-data' \
  --header 'x-api-key: <api-key>' \
  --form modelFile='@example-file' \
  --form 'modelFileName=<string>' \
  --form modelFileType=tflite \
  --form representativeFeatures='@example-file' \
  --form 'device=<string>'
{
  "success": true,
  "id": 12873488112,
  "error": "<string>"
}

Authorizations

​
x-api-key
string
header
required

Path Parameters

​
projectId
integer
required

Project ID

Query Parameters

​
impulseId
integer

Impulse ID. If this is unset then the default impulse is used.

Body

multipart/form-data
​
modelFile
file
required
​
modelFileName
string
required
​
modelFileType
enum<string>
required
Available options:
tflite,
onnx,
saved_model
​
representativeFeatures
file
​
device
string

MCU used for calculating latency, query latencyDevices in listProject for a list of supported devices (and use the "mcu" property here). If this is kept empty then we'll show an overview of multiple devices.

Response

200 - application/json

OK

​
success
boolean
required

Whether the operation succeeded

​
id
integer
required

Job identifier. Status updates will include this identifier.

Example:

12873488112

​
error
string

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