base function (face detetion + face recognition)

src/detector.py

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+import cv2
+
+class Detector():
+
+    detector = None
+
+    @classmethod
+    def get(self):
+        
+        if self.detector is None:
+            self.detector = cv2.FaceDetectorYN.create(
+                "../models/face_detection_yunet_2026may.onnx",
+                "",
+                (320,320),
+                0.85,
+                0.3,
+                5000
+            )
+        
+        return self.detector

src/face_detection.py

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+import cv2
+
+from detector import *
+
+def detect_in_image(image_path:str, scale = 1):
+    
+    img = cv2.imread(image_path)
+    
+    imgW = img1.shape[1] * scale
+    imgH = img1.shape[0] * scale
+
+    img = cv2.resize(img, (imgH, imgW))
+
+    detector = Detector.get()
+    detector.setInputSize((imgH, imgW))
+
+    face = detector.detect(img)
+
+    return face

src/face_recognition.py

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+import cv2
+
+from recognizer import Recognizer
+
+def extract_faces(faces:list, img:list, filename:str): 
+    
+    for i in faces:
+        face = faces[i]
+        croped_img = recognizer.alignCrop(img, face[1][0])
+        cv2.imwrite(f"../data/extracted/{filename}_{i}.png")
+
+
+def is_same_face(
+    face1_img:list, 
+    face2_img:list, 
+    cosine_similarity_threshold:float = 0.363,
+    l2_similarity_threshold:float = 1.128
+) -> bool:
+
+    recognizer = Recognizer.get()
+
+    faces1_features = recognizer.feature(face1_img)
+    faces2_features = recognizer.feature(face2_img)
+
+    cosine_score = recognizer.match(faces1_features, faces2_features, cv2.FaceRecognizerSF_FR_COSINE)
+    l2_score = recognizer.match(faces1_features, faces2_features, cv2.FaceRecognizerSF_FR_NORM_L2)
+
+    return cosine_score >= cosine_similarity_threshold and l2_score <= l2_similarity_threshold

src/main.py

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+import cv2
+
+from face_detection import *
+from face_recognition import *
+

src/recognizer.py

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+import cv2
+
+class Recognizer():
+
+    recognizer = None
+
+    @classmethod
+    def get(self):
+        
+        if self.recognizer is None:
+            recognizer = cv2.FaceRecognizerSF.create(
+               "../models/face_recognition_sface_2021dec_int8.onnx",
+                ""
+            )
+        
+        return self.recognizer

src/utils.py

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+
+
+def load_image