增加运维机器人单元

aibox/skills/facerec.py

@@ -0,0 +1,399 @@
+#!/usr/bin/env python3
+"""人脸检测和识别工具 - 检测图像中的人脸并保存裁剪的人脸图像。"""
+
+import os
+import sys
+import argparse
+import cv2
+import numpy as np
+from datetime import datetime
+
+try:
+    import face_recognition
+except ImportError:
+    print("❌ 缺少依赖库: face_recognition。请运行: pip install face_recognition")
+    sys.exit(1)
+
+
+class FaceDetector:
+    """人脸检测和识别工具"""
+    
+    def __init__(self):
+        self.faces_dir = os.path.expanduser("~/.aibox/faces")
+        self.known_faces_dir = os.path.expanduser("~/.aibox/known_faces")
+        self._ensure_dirs()
+        self.known_face_encodings = []
+        self.known_face_names = []
+        self._load_known_faces()
+    
+    def _ensure_dirs(self):
+        os.makedirs(self.faces_dir, exist_ok=True)
+        os.makedirs(self.known_faces_dir, exist_ok=True)
+    
+    def _load_known_faces(self):
+        """加载已知人脸编码"""
+        self.known_face_encodings = []
+        self.known_face_names = []
+        
+        if os.path.exists(self.known_faces_dir):
+            for filename in os.listdir(self.known_faces_dir):
+                if filename.endswith(('.jpg', '.jpeg', '.png')):
+                    filepath = os.path.join(self.known_faces_dir, filename)
+                    try:
+                        image = face_recognition.load_image_file(filepath)
+                        encodings = face_recognition.face_encodings(image)
+                        if encodings:
+                            name = os.path.splitext(filename)[0]
+                            self.known_face_encodings.append(encodings[0])
+                            self.known_face_names.append(name)
+                    except Exception as e:
+                        print(f"加载已知人脸失败 {filename}: {e}", file=sys.stderr)
+    
+    def detect_faces(self, image_path: str, save_cropped: bool = True, 
+                     recognize: bool = True, tolerance: float = 0.6) -> str:
+        """检测图像中的人脸并保存裁剪的人脸"""
+        try:
+            if not os.path.exists(image_path):
+                return f"❌ 错误：文件不存在 - {image_path}"
+            
+            image = face_recognition.load_image_file(image_path)
+            face_locations = face_recognition.face_locations(image)
+            
+            if not face_locations:
+                return "📭 未检测到人脸"
+            
+            face_encodings = face_recognition.face_encodings(image, face_locations)
+            
+            results = []
+            saved_files = []
+            
+            for i, (top, right, bottom, left) in enumerate(face_locations):
+                face_data = {
+                    "index": i + 1,
+                    "position": {"top": top, "right": right, "bottom": bottom, "left": left},
+                    "size": {"width": right - left, "height": bottom - top}
+                }
+                
+                if recognize and self.known_face_encodings and i < len(face_encodings):
+                    matches = face_recognition.compare_faces(
+                        self.known_face_encodings, 
+                        face_encodings[i], 
+                        tolerance=tolerance
+                    )
+                    
+                    if True in matches:
+                        match_index = matches.index(True)
+                        name = self.known_face_names[match_index]
+                        face_data["name"] = name
+                        face_data["match"] = True
+                        
+                        distances = face_recognition.face_distance(
+                            self.known_face_encodings, 
+                            face_encodings[i]
+                        )
+                        face_data["similarity"] = f"{1 - distances[match_index]:.3f}"
+                    else:
+                        face_data["name"] = "Unknown"
+                        face_data["match"] = False
+                else:
+                    face_data["name"] = f"Face_{i+1}"
+                    face_data["match"] = False
+                
+                if save_cropped:
+                    image_array = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
+                    
+                    margin = 20
+                    top_crop = max(0, top - margin)
+                    bottom_crop = min(image_array.shape[0], bottom + margin)
+                    left_crop = max(0, left - margin)
+                    right_crop = min(image_array.shape[1], right + margin)
+                    
+                    face_crop = image_array[top_crop:bottom_crop, left_crop:right_crop]
+                    
+                    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+                    safe_name = face_data['name'].replace(' ', '_')
+                    filename = f"{timestamp}_face_{i+1}_{safe_name}.jpg"
+                    filepath = os.path.join(self.faces_dir, filename)
+                    
+                    cv2.imwrite(filepath, face_crop)
+                    
+                    face_data["saved_file"] = filename
+                    saved_files.append(filename)
+                
+                results.append(face_data)
+            
+            output = []
+            output.append(f"✅ 检测到 {len(face_locations)} 个人脸")
+            output.append(f"📁 人脸图像保存位置: {self.faces_dir}")
+            output.append("")
+            
+            for face in results:
+                output.append(f"人脸 #{face['index']}:")
+                output.append(f"  位置: 左={face['position']['left']}, 上={face['position']['top']}, "
+                            f"右={face['position']['right']}, 下={face['position']['bottom']}")
+                output.append(f"  大小: {face['size']['width']}x{face['size']['height']} 像素")
+                output.append(f"  识别结果: {face['name']}")
+                
+                if 'similarity' in face:
+                    output.append(f"  相似度: {face['similarity']}")
+                
+                if 'saved_file' in face:
+                    output.append(f"  保存文件: {face['saved_file']}")
+                
+                output.append("")
+            
+            if saved_files:
+                output.append("📋 保存的文件列表:")
+                for f in saved_files:
+                    output.append(f"  • {f}")
+            
+            return "\n".join(output)
+            
+        except Exception as e:
+            return f"❌ 人脸检测失败: {str(e)}"
+    
+    def list_saved_faces(self, limit: int = 20) -> str:
+        """列出已保存的人脸图像"""
+        try:
+            files = []
+            if os.path.exists(self.faces_dir):
+                for filename in sorted(os.listdir(self.faces_dir), reverse=True):
+                    if filename.endswith(('.jpg', '.jpeg', '.png')):
+                        files.append(filename)
+                        if len(files) >= limit:
+                            break
+            
+            if files:
+                output = [f"📁 已保存的人脸图像 (最近 {len(files)} 张):"]
+                for f in files:
+                    output.append(f"  • {f}")
+                output.append(f"\n📂 保存位置: {self.faces_dir}")
+                return "\n".join(output)
+            else:
+                return "📭 尚未保存任何人脸图像"
+        except Exception as e:
+            return f"❌ 列出失败: {str(e)}"
+    
+    def list_known_faces(self) -> str:
+        """列出已知人脸库中的人脸"""
+        try:
+            faces = []
+            if os.path.exists(self.known_faces_dir):
+                for filename in os.listdir(self.known_faces_dir):
+                    if filename.endswith(('.jpg', '.jpeg', '.png')):
+                        name = os.path.splitext(filename)[0]
+                        faces.append(name)
+            
+            if faces:
+                output = [f"👥 已知人脸库 (共 {len(faces)} 人):"]
+                for name in faces:
+                    output.append(f"  • {name}")
+                output.append(f"\n📂 数据库位置: {self.known_faces_dir}")
+                return "\n".join(output)
+            else:
+                return "📭 已知人脸库为空"
+        except Exception as e:
+            return f"❌ 列出失败: {str(e)}"
+    
+    def add_known_face(self, image_path: str, person_name: str) -> str:
+        """添加已知人脸到数据库"""
+        try:
+            if not os.path.exists(image_path):
+                return f"❌ 文件不存在: {image_path}"
+            
+            image = face_recognition.load_image_file(image_path)
+            face_locations = face_recognition.face_locations(image)
+            
+            if not face_locations:
+                return "❌ 未检测到人脸，无法添加"
+            
+            if len(face_locations) > 1:
+                return f"⚠️ 检测到 {len(face_locations)} 个人脸，请使用单人脸图片"
+            
+            filepath = os.path.join(self.known_faces_dir, f"{person_name}.jpg")
+            
+            if os.path.exists(filepath):
+                os.remove(filepath)
+            
+            image_array = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
+            top, right, bottom, left = face_locations[0]
+            
+            margin = 20
+            top_crop = max(0, top - margin)
+            bottom_crop = min(image_array.shape[0], bottom + margin)
+            left_crop = max(0, left - margin)
+            right_crop = min(image_array.shape[1], right + margin)
+            
+            face_crop = image_array[top_crop:bottom_crop, left_crop:right_crop]
+            cv2.imwrite(filepath, face_crop)
+            
+            self._load_known_faces()
+            
+            return f"✅ 已添加已知人脸: {person_name}\n📁 保存位置: {filepath}"
+            
+        except Exception as e:
+            return f"❌ 添加失败: {str(e)}"
+    
+    def remove_known_face(self, person_name: str) -> str:
+        """从已知人脸库中删除人脸"""
+        try:
+            filepath = os.path.join(self.known_faces_dir, f"{person_name}.jpg")
+            
+            if not os.path.exists(filepath):
+                for filename in os.listdir(self.known_faces_dir):
+                    if filename.endswith(('.jpg', '.jpeg', '.png')):
+                        name = os.path.splitext(filename)[0]
+                        if name.lower() == person_name.lower():
+                            filepath = os.path.join(self.known_faces_dir, filename)
+                            break
+                else:
+                    return f"❌ 未找到已知人脸: {person_name}"
+            
+            os.remove(filepath)
+            self._load_known_faces()
+            
+            return f"✅ 已删除已知人脸: {person_name}"
+            
+        except Exception as e:
+            return f"❌ 删除失败: {str(e)}"
+    
+    def get_face_info(self, person_name: str) -> str:
+        """获取已知人脸信息"""
+        try:
+            filepath = os.path.join(self.known_faces_dir, f"{person_name}.jpg")
+            
+            if not os.path.exists(filepath):
+                for filename in os.listdir(self.known_faces_dir):
+                    if filename.endswith(('.jpg', '.jpeg', '.png')):
+                        name = os.path.splitext(filename)[0]
+                        if name.lower() == person_name.lower():
+                            filepath = os.path.join(self.known_faces_dir, filename)
+                            person_name = name
+                            break
+                else:
+                    return f"❌ 未找到人脸: {person_name}"
+            
+            file_size = os.path.getsize(filepath)
+            modified_time = datetime.fromtimestamp(os.path.getmtime(filepath))
+            
+            output = []
+            output.append(f"👤 人脸信息: {person_name}")
+            output.append(f"📁 文件路径: {filepath}")
+            output.append(f"📊 文件大小: {file_size} 字节 ({file_size/1024:.1f}KB)")
+            output.append(f"🕐 最后修改: {modified_time.strftime('%Y-%m-%d %H:%M:%S')}")
+            
+            return "\n".join(output)
+            
+        except Exception as e:
+            return f"❌ 获取人脸信息失败: {str(e)}"
+
+
+def main():
+    parser = argparse.ArgumentParser(
+        description="人脸检测和识别工具 - 检测图像中的人脸并保存裁剪的人脸图像。",
+        epilog="""
+使用示例:
+  # 检测人脸
+  face-detector --action detect --image-path photo.jpg
+
+  # 检测人脸（不保存裁剪）
+  face-detector --action detect --image-path photo.jpg --no-save
+
+  # 检测人脸（不进行识别）
+  face-detector --action detect --image-path photo.jpg --no-recognize
+
+  # 列出已保存的人脸图像
+  face-detector --action list-faces --limit 10
+
+  # 列出已知人脸库
+  face-detector --action list-known
+
+  # 添加已知人脸
+  face-detector --action add-known --image-path face.jpg --person-name "张三"
+
+  # 删除已知人脸
+  face-detector --action remove-known --person-name "张三"
+
+  # 查看人脸信息
+  face-detector --action get-info --person-name "张三"
+
+目录结构:
+  ~/.aibox/faces/       - 人脸图像保存位置
+  ~/.aibox/known_faces/ - 已知人脸数据库
+
+需要安装:
+  pip install face_recognition opencv-python
+        """
+    )
+    
+    parser.add_argument("--action", "-a", required=True,
+        choices=["detect", "list-faces", "list-known", "add-known", "remove-known", "get-info"],
+        help="操作类型")
+    
+    # 检测参数
+    parser.add_argument("--image-path", "-i", help="图片文件路径")
+    parser.add_argument("--no-save", action="store_true", help="不保存裁剪的人脸图像")
+    parser.add_argument("--no-recognize", action="store_true", help="不进行人脸识别")
+    parser.add_argument("--tolerance", "-t", type=float, default=0.6, help="识别容差（默认: 0.6）")
+    
+    # 列表参数
+    parser.add_argument("--limit", "-l", type=int, default=20, help="列出文件数量限制（默认: 20）")
+    
+    # 已知人脸参数
+    parser.add_argument("--person-name", "-n", help="人名标识")
+    
+    args = parser.parse_args()
+    
+    detector = FaceDetector()
+    
+    try:
+        if args.action == "detect":
+            if not args.image_path:
+                print("❌ 需要提供 --image-path 参数")
+                sys.exit(1)
+            
+            result = detector.detect_faces(
+                image_path=args.image_path,
+                save_cropped=not args.no_save,
+                recognize=not args.no_recognize,
+                tolerance=args.tolerance
+            )
+            print(result)
+        
+        elif args.action == "list-faces":
+            print(detector.list_saved_faces(args.limit))
+        
+        elif args.action == "list-known":
+            print(detector.list_known_faces())
+        
+        elif args.action == "add-known":
+            if not args.image_path or not args.person_name:
+                print("❌ 需要提供 --image-path 和 --person-name 参数")
+                sys.exit(1)
+            
+            result = detector.add_known_face(args.image_path, args.person_name)
+            print(result)
+        
+        elif args.action == "remove-known":
+            if not args.person_name:
+                print("❌ 需要提供 --person-name 参数")
+                sys.exit(1)
+            
+            result = detector.remove_known_face(args.person_name)
+            print(result)
+        
+        elif args.action == "get-info":
+            if not args.person_name:
+                print("❌ 需要提供 --person-name 参数")
+                sys.exit(1)
+            
+            result = detector.get_face_info(args.person_name)
+            print(result)
+        
+    except Exception as e:
+        print(f"❌ 执行错误: {str(e)}")
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()