deepfuze

2024-06-13 07:56:13 +05:30
commit 47d3520c19
184 changed files with 10075 additions and 0 deletions
@@ -0,0 +1,51 @@
+from typing import Any, Dict
+import numpy
+
+import deepfuze.globals
+from deepfuze.face_store import FACE_STORE
+from deepfuze.typing import FaceSet
+from deepfuze import logger
+
+
+def create_statistics(static_faces : FaceSet) -> Dict[str, Any]:
+	face_detector_score_list = []
+	face_landmarker_score_list = []
+	statistics =\
+	{
+		'min_face_detector_score': 0,
+		'min_face_landmarker_score': 0,
+		'max_face_detector_score': 0,
+		'max_face_landmarker_score': 0,
+		'average_face_detector_score': 0,
+		'average_face_landmarker_score': 0,
+		'total_face_landmark_5_fallbacks': 0,
+		'total_frames_with_faces': 0,
+		'total_faces': 0
+	}
+
+	for faces in static_faces.values():
+		statistics['total_frames_with_faces'] = statistics.get('total_frames_with_faces') + 1
+		for face in faces:
+			statistics['total_faces'] = statistics.get('total_faces') + 1
+			face_detector_score_list.append(face.scores.get('detector'))
+			face_landmarker_score_list.append(face.scores.get('landmarker'))
+			if numpy.array_equal(face.landmarks.get('5'), face.landmarks.get('5/68')):
+				statistics['total_face_landmark_5_fallbacks'] = statistics.get('total_face_landmark_5_fallbacks') + 1
+
+	if face_detector_score_list:
+		statistics['min_face_detector_score'] = round(min(face_detector_score_list), 2)
+		statistics['max_face_detector_score'] = round(max(face_detector_score_list), 2)
+		statistics['average_face_detector_score'] = round(numpy.mean(face_detector_score_list), 2)
+	if face_landmarker_score_list:
+		statistics['min_face_landmarker_score'] = round(min(face_landmarker_score_list), 2)
+		statistics['max_face_landmarker_score'] = round(max(face_landmarker_score_list), 2)
+		statistics['average_face_landmarker_score'] = round(numpy.mean(face_landmarker_score_list), 2)
+	return statistics
+
+
+def conditional_log_statistics() -> None:
+	if deepfuze.globals.log_level == 'debug':
+		statistics = create_statistics(FACE_STORE.get('static_faces'))
+
+		for name, value in statistics.items():
+			logger.debug(str(name) + ': ' + str(value), __name__.upper())