Multi images prediction using AutoML generated Model

automlPredictMulti.py

import sys
import os

from google.cloud import automl_v1beta1
from google.cloud.automl_v1beta1.proto import service_pb2


def get_prediction(content, project_id, model_id):
  prediction_client = automl_v1beta1.PredictionServiceClient()

  name = 'projects/{}/locations/us-central1/models/{}'.format(project_id, model_id)
  payload = {'image': {'image_bytes': content }}
  params = {}
  request = prediction_client.predict(name, payload, params)
  return request  # waits till request is returned

if __name__ == '__main__':
  file_path = "C:/DeepEye/Data/Result/boundingbox_resources/20190409"
  project_id = "sunlit-cove-237107"
  model_id = "ICN8375020944768203011"
  result = open('result.txt', 'w')
  
  for filename in os.listdir(file_path):
    filename = file_path +'/' +filename
    print filename
    with open(filename, 'rb') as ff:
      content = ff.read()

    #print get_prediction(content, project_id,  model_id)
    result.write(filename+'\n'+ str(get_prediction(content, project_id,  model_id))+'\n')
    
  result.close()