예제 #1
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 def from_config(cls, config):
     return cls(feature_extractor=FeatureExtractor(config['INCEPTION_MODEL_FILE']),
                package_uris=config['CLOUD_ML_PACKAGE_URIS'],
                python_module=config['CLOUD_ML_PYTHON_MODULE'],
                data_dir_format=config['CLOUD_ML_DATA_DIR'],
                train_dir_format=config['CLOUD_ML_TRAIN_DIR'],
                log_dir_format=config['CLOUD_ML_LOG_DIR'],
                local_model_dir=config['MODEL_DIR'],
                local_classifier_model_dir=config['CLASSIFIER_MODEL_DIR'])
예제 #2
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class CandyClassifier(object):
    def __init__(self, checkpoint_dir, params_file, inception_model_file):
        self.inception_model = None
        self.model = None
        self.checkpoint_dir = checkpoint_dir
        self.params_file = params_file
        self.inception_model_file = inception_model_file

    @classmethod
    def from_config(cls, config):
        checkpoint_dir = get_classifier_dir(config)
        return cls(checkpoint_dir=checkpoint_dir,
                   params_file=os.path.join(checkpoint_dir, 'params.json'),
                   inception_model_file=config['INCEPTION_MODEL_FILE'])

    def init(self):
        self._load_inception_model()
        self._load_transfer_model()

    def reload(self):
        tf.reset_default_graph()
        self._load_transfer_model()

    def _load_inception_model(self):
        logger.info('Loading inception model...')
        self.inception_model = FeatureExtractor(self.inception_model_file)
        logger.info('Finished loading inception model.')

    def _load_transfer_model(self):
        logger.info('Loading transfer model...')
        with tf.gfile.FastGFile(self.params_file, 'r') as f:
            params = ModelParams.from_json(f.read())
        self.model = TransferModel.from_model_params(params)
        logger.info('Finished loading transfer model.')

    def classify(self, img_bgr):
        features = self.inception_model.get_feature_vector(img_bgr)
        ckpt = tf.train.get_checkpoint_state(self.checkpoint_dir)
        if ckpt is None:
            raise IOError('Checkpoints not found.')
        checkpoint_path = ckpt.model_checkpoint_path
        result = self.model.restore_and_predict(features, checkpoint_path)
        return result[0]
예제 #3
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 def _load_inception_model(self):
     logger.info('Loading inception model...')
     self.inception_model = FeatureExtractor(self.inception_model_file)
     logger.info('Finished loading inception model.')