fixed multi-faces recognition

src/face.py

@@ -0,0 +1,25 @@
+import cv2
+
+class Face():
+
+    def __init__(self, data, img, name):
+        self.data = data
+        self.img = img
+        self.name = name
+
+        self.feature = None
+
+        self.l2 = None
+        self.cosine = None
+    
+    def set_feature(self, fetaure):
+        self.feature = feature
+
+    def set_cosine(self, cosine:float):
+        self.cosine = cosine
+    
+    def set_l2(self, l2:float):
+        self.l2 = l2
+
+    def save(self, path:str, extension:str = "png"):
+        cv2.imwrite(f"{path}/{self.name}.{extension}", self.img)

src/face_recognition.py

@@ -1,16 +1,21 @@
 import cv2
 
 from recognizer import Recognizer
+from face import *
 
-def extract_faces(faces:list, img:list, filename:str): 
+def extract_faces(faces_data:list, img:list, filename:str): 
     
     recognizer = Recognizer.get()
+    res = []
+    for i in range(1, len(faces_data[1])):
+        face_data = faces_data[1][i]
 
-    for i in range(1, len(faces)):
+        croped_img = recognizer.alignCrop(img, face_data)
-        face = faces[i]
+        face = Face(face_data, croped_img, f"{filename}_{i}")
         
-        croped_img = recognizer.alignCrop(img, face[0])
+        res.append(face)
-        cv2.imwrite(f"./data/extracted/{filename}_{i}.png", croped_img)
+    
+    return res
 
 
 def is_same_face(

src/main.py

@@ -9,6 +9,7 @@ from face_recognition import *
 files = list_all_files("./data/raw", ["jpg", "webp"])
 
 # process each files
+faces = []
 for file_path in files:
     
     filename = file_path.split("/")[-1].split(".")[0]
@@ -18,12 +19,16 @@ for file_path in files:
     if img is None:
         print(f"ERROR: Could not read image at {file_path}")
         continue
-    cv2.imshow("image1", img)
 
     # detect faces file
-    faces = detect_face_in_image(img, scale=1)
+    faces_data = detect_face_in_image(img, scale=1)
 
+    print("faces_data: ", faces_data[1])
     # extract faces from file
-    extract_faces(faces, img, filename)
+    faces += extract_faces(faces_data, img, filename)
+
+# classify each faces
+for face in faces:
+    face.save("./data/extracted")
 
 cv2.destroyAllWindows()