def __init__(self): self.config = get_config() self.flask_config = self.config['flask'] self.flask_api_config = self.flask_config['api'] self.model_config = self.config['model']
def __init__(self): self.config = get_config()
def __init__(self): config = get_config() credentials = config['app']['api']['twilio'] self.client = TwilioRestClient(credentials['account_sid'], credentials['auth_token'])
print("Precision: {}%".format(100 * precision[i])) fh.write("\tPrecision: {}%".format(100 * precision[i])) print("Recall: {}%".format(100 * recall[i])) fh.write("\tRecall: {}%".format(100 * recall[i])) print("F1_Score: {}%".format(100 * f1_score[i])) fh.write("\tF1_Score: {}%".format(100 * f1_score[i])) print("confusion_matrix: ", confusion_matrix[i]) print("Normalized_confusion_matrix: ", normalised_confusion_matrix[i]) fh.close() return def main(config): np.random.seed(config.random_seed) prepare_dirs(config) header_file = config.data_dir + '/header.tfl.txt' log_file = os.path.join(config.model_dir, 'SilCamNet.out') filename = config.data_dir + '/image_set.dat' print(config.data_dir, config.model_dir, header_file, log_file, filename) # build_hd5(config.data_dir, header_file, filename) train_net(config.data_dir, config.model_dir, header_file, log_file, filename, round_num='') return if __name__ == '__main__': config, unparsed = get_config() main(config)