Train Model Keras

Take the output from a DSP block and train a neural network using Keras. Updates are streamed over the websocket API.

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cURL

curl --request POST \
  --url https://studio.edgeimpulse.com/v1/api/{projectId}/jobs/train/keras/{learnId} \
  --header 'content-type: application/json' \
  --header 'x-jwt-token: REPLACE_KEY_VALUE' \
  --data '{"mode":"expert","minimumConfidenceRating":0,"selectedModelType":"int8","script":"string","visualLayers":[{"type":"dense","neurons":0,"kernelSize":0,"dropoutRate":0,"columns":0,"stack":0,"enabled":true,"organizationModelId":0}],"trainingCycles":0,"learningRate":0,"trainTestSplit":0,"autoClassWeights":true,"findLearningRate":true,"augmentationPolicyImage":"none","augmentationPolicySpectrogram":{"enabled":true,"warping":true,"freqMasking":"none","timeMasking":"none","gaussianNoise":"none"},"profileInt8":true,"skipEmbeddingsAndMemory":true,"customValidationMetadataKey":"string"}'

Python

import http.client

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

payload = "{\"mode\":\"expert\",\"minimumConfidenceRating\":0,\"selectedModelType\":\"int8\",\"script\":\"string\",\"visualLayers\":[{\"type\":\"dense\",\"neurons\":0,\"kernelSize\":0,\"dropoutRate\":0,\"columns\":0,\"stack\":0,\"enabled\":true,\"organizationModelId\":0}],\"trainingCycles\":0,\"learningRate\":0,\"trainTestSplit\":0,\"autoClassWeights\":true,\"findLearningRate\":true,\"augmentationPolicyImage\":\"none\",\"augmentationPolicySpectrogram\":{\"enabled\":true,\"warping\":true,\"freqMasking\":\"none\",\"timeMasking\":\"none\",\"gaussianNoise\":\"none\"},\"profileInt8\":true,\"skipEmbeddingsAndMemory\":true,\"customValidationMetadataKey\":\"string\"}"

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

conn.request("POST", "/v1/api/{projectId}/jobs/train/keras/{learnId}", 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/train/keras/{learnId}',
  headers: {'content-type': 'application/json', 'x-jwt-token': 'REPLACE_KEY_VALUE'},
  body: {
    mode: 'expert',
    minimumConfidenceRating: 0,
    selectedModelType: 'int8',
    script: 'string',
    visualLayers: [
      {
        type: 'dense',
        neurons: 0,
        kernelSize: 0,
        dropoutRate: 0,
        columns: 0,
        stack: 0,
        enabled: true,
        organizationModelId: 0
      }
    ],
    trainingCycles: 0,
    learningRate: 0,
    trainTestSplit: 0,
    autoClassWeights: true,
    findLearningRate: true,
    augmentationPolicyImage: 'none',
    augmentationPolicySpectrogram: {
      enabled: true,
      warping: true,
      freqMasking: 'none',
      timeMasking: 'none',
      gaussianNoise: 'none'
    },
    profileInt8: true,
    skipEmbeddingsAndMemory: true,
    customValidationMetadataKey: 'string'
  },
  json: true
};

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

  console.log(body);
});