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)
