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reproject/face_library.py

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+import face_recognition
+import numpy as np
+
+class FaceLibrary:
+    def __init__(self, face_db):
+        """
+        face_db: 字典 {"Name": {"image-path": "x.jpg", "age": 20}, ...}
+        """
+        self.known_encodings = []
+        self.known_names = []
+        self.known_infos = []
+        self._load_database(face_db)
+
+    def _load_database(self, face_db):
+        print("正在加载人脸底库...")
+        for name, info in face_db.items():
+            try:
+                image = face_recognition.load_image_file(info["image-path"])
+                encodings = face_recognition.face_encodings(image)
+                if encodings:
+                    self.known_encodings.append(encodings[0])
+                    self.known_names.append(name)
+                    self.known_infos.append(info)
+                    print(f"✅ 已加载: {name}")
+                else:
+                    print(f"⚠️ 无法提取特征: {name}")
+            except Exception as e:
+                print(f"❌ 加载失败 {name}: {e}")
+
+    def identify(self, frame_rgb, face_location=None, tolerance=0.5):
+        """
+        frame_rgb: RGB 图片
+        face_location: (top, right, bottom, left) 或者 None (全图搜索)
+        """
+        if not self.known_encodings:
+            return None
+
+        locations = [face_location] if face_location else None
+        
+        try: 
+            encodings = face_recognition.face_encodings(frame_rgb, known_face_locations=locations)
+            
+            if not encodings:
+                return None
+            
+            unknown_encoding = encodings[0]
+            distances = face_recognition.face_distance(self.known_encodings, unknown_encoding)
+            min_idx = np.argmin(distances)
+            
+            if distances[min_idx] <= tolerance:
+                return {
+                    "name": self.known_names[min_idx],
+                    "info": self.known_infos[min_idx],
+                    "distance": distances[min_idx]
+                }
+        except Exception as e:
+            print(f"识别出错: {e}")
+            
+        return None