Deploy Pretrained Model

Takes in a TFLite file and builds the model and SDK. Updates are streamed over the websocket API (or can be retrieved through the /stdout endpoint).

Error while loading OpenAPI operation — Invalid OpenAPI document

cURL

curl --request POST \
  --url https://studio.edgeimpulse.com/v1/api/{projectId}/jobs/deploy-pretrained-model \
  --header 'content-type: application/json' \
  --header 'x-jwt-token: REPLACE_KEY_VALUE' \
  --data '{"modelFileBase64":"string","modelFileType":"tflite","deploymentType":"string","engine":"tflite","modelInfo":{"input":{},"model":{}}}'

Python

import http.client

conn = http.client.HTTPSConnection("studio.edgeimpulse.com")

payload = "{\"modelFileBase64\":\"string\",\"modelFileType\":\"tflite\",\"deploymentType\":\"string\",\"engine\":\"tflite\",\"modelInfo\":{\"input\":{},\"model\":{}}}"

headers = {
    'content-type': "application/json",
    'x-jwt-token': "REPLACE_KEY_VALUE"
    }

conn.request("POST", "/v1/api/{projectId}/jobs/deploy-pretrained-model", payload, headers)

res = conn.getresponse()
data = res.read()

print(data.decode("utf-8"))

Node.js

const request = require('request');

const options = {
  method: 'POST',
  url: 'https://studio.edgeimpulse.com/v1/api/{projectId}/jobs/deploy-pretrained-model',
  headers: {'content-type': 'application/json', 'x-jwt-token': 'REPLACE_KEY_VALUE'},
  body: {
    modelFileBase64: 'string',
    modelFileType: 'tflite',
    deploymentType: 'string',
    engine: 'tflite',
    modelInfo: {input: {}, model: {}}
  },
  json: true
};

request(options, function (error, response, body) {
  if (error) throw new Error(error);

  console.log(body);
});