def recognize_data(self, group, folder_name): classifier_path = f"classifiers/{self.photos_size}/{folder_name}" paths_to_recognize = [] y_true = [] photos_ids = [] for photos_path in group: paths_to_recognize.append(photos_path) student_id = int(os.path.split(photos_path)[-1].split("-")[0]) photo_id = int( os.path.split(photos_path)[-1].split("-")[1].split(".")[0]) y_true.append(student_id) photos_ids.append(photo_id) recognizer = Recognizer(paths_to_recognize, classifier_path) eigenfaces_y_pred = recognizer.eigenfaces() eigenfaces_metrics = MetricsCalculator(y_true, photos_ids, eigenfaces_y_pred) eigenfaces_metrics.calculate_metrics() eigenfaces_metrics.print_metrics() self.eigenfaces_metrics.append(eigenfaces_metrics) fisherfaces_y_pred = recognizer.fisherfaces() fisherfaces_metrics = MetricsCalculator(y_true, photos_ids, fisherfaces_y_pred) fisherfaces_metrics.calculate_metrics() fisherfaces_metrics.print_metrics() self.fisherfaces_metrics.append(fisherfaces_metrics) lbph_y_pred = recognizer.lbph() lbph_metrics = MetricsCalculator(y_true, photos_ids, lbph_y_pred) lbph_metrics.calculate_metrics() lbph_metrics.print_metrics() self.lbph_metrics.append(lbph_metrics)