def __init__(self, workspace_server_id=None, host='localhost', port=9008, user_id='admin', password='******', debug=False): self.printer = pprint.PrettyPrinter(indent=4) config = skil_client.Configuration() config.host = "{}:{}".format(host, port) config.debug = debug self.config = config self.uploads = [] self.uploaded_model_names = [] self.auth_headers = None self.api_client = skil_client.ApiClient(configuration=config) self.api = skil_client.DefaultApi(api_client=self.api_client) try: self.printer.pprint('>>> Authenticating SKIL...') credentials = Cred(user_id=user_id, password=password) token = self.api.login(credentials) self.token = token.token config.api_key['authorization'] = self.token config.api_key_prefix['authorization'] = "Bearer" self.printer.pprint('>>> Done!') except api_exception as e: raise Exception( "Exception when calling DefaultApi->login: {}\n".format(e)) if workspace_server_id: self.server_id = workspace_server_id else: self.server_id = self.get_default_server_id() result = { 'host': host, 'port': port, 'user_id': user_id, 'password': password, 'debug': debug, 'workspace_server_id': self.server_id } save_skil_config(result)
image_batch = tf.stack(crops) return image_batch def make_single_image_batch(image_path, coder): image_data = tf.gfile.FastGFile(image_path, 'rb').read() image = coder.decode_jpeg(image_data) crop = tf.image.resize_images(image, (227,227)) image_batch = tf.stack([crop]) return image_batch with tf.Session() as sess: coder = ImageCoder() image_batch = make_multi_crop_batch(image_file, coder) image_batch = image_batch.eval() configuration = skil_client.Configuration() configuration.host = 'http://192.168.1.128:9008' configuration.username = '******' configuration.password = '******' r = requests.post("http://192.168.1.128:9008/login", json={"userId": "admin", "password": "******"}) token = r.json()['token'] configuration.api_key['authorization'] = f'Bearer {token}' api_instance = skil_client.DefaultApi(skil_client.ApiClient(configuration)) list_ind_array = [[convert_indarray(np.expand_dims(image_batch[i,:,:,:], axis=0))] for i in range(12)] batch_results = [] index = 0