def run_customization(image_loader, feature_extractor): logging.info("Start customize svm") logging.info("Generate sample") data = get_class_data(params.first_class_params, params.sample_size/2) + get_class_data(params.second_class_params, params.sample_size/2) random.shuffle(data) trainer = Trainer(image_loader, feature_extractor) c_range = [10 ** i for i in xrange(-5, 10)] gamma_range = [10 ** i for i in xrange(-5, 5)] results = trainer.svm_params_customization(data, params.svm_params, c_range, gamma_range) return results