fix

2.py

@@ -0,0 +1,207 @@
+import cv2
+import numpy as np
+import random
+import os
+import sys
+from collections import deque
+
+class FaceSelector:
+    def __init__(self):
+        # 获取模型文件的正确路径
+        cascade_path = self.get_cascade_path()
+        self.face_cascade = cv2.CascadeClassifier(cascade_path)
+        
+        # 检查模型是否加载成功
+        if self.face_cascade.empty():
+            fallback_path = cv2.data.haarcascades + 'haarcascade_frontalface_default.xml'
+            self.face_cascade = cv2.CascadeClassifier(fallback_path)
+            
+            if self.face_cascade.empty():
+                sys.exit(1)
+        
+        # 状态变量
+        self.random_mode = False
+        self.selected_face = None
+        self.static_frame = None
+        self.static_faces = None
+        
+        # 用于平滑检测的队列
+        self.face_queue = deque(maxlen=5)
+        
+        # 创建窗口
+        self.window_name = "Face Selector"
+        cv2.namedWindow(self.window_name, cv2.WINDOW_NORMAL)
+        
+        # 添加窗口关闭事件处理
+        self.running = True
+        
+    def get_cascade_path(self):
+        """获取模型文件的正确路径"""
+        if getattr(sys, 'frozen', False):
+            base_path = sys._MEIPASS
+        else:
+            base_path = os.path.dirname(os.path.abspath(__file__))
+        
+        possible_paths = [
+            os.path.join(base_path, 'haarcascade_frontalface_default.xml'),
+            os.path.join(base_path, 'cv2', 'data', 'haarcascade_frontalface_default.xml'),
+            os.path.join(base_path, 'Library', 'etc', 'haarcascades', 'haarcascade_frontalface_default.xml'),
+            cv2.data.haarcascades + 'haarcascade_frontalface_default.xml'
+        ]
+        
+        for path in possible_paths:
+            if os.path.isfile(path):
+                return path
+        
+        return possible_paths[0]
+    
+    def detect_faces(self, frame):
+        """检测人脸并返回位置"""
+        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+        
+        faces = self.face_cascade.detectMultiScale(
+            gray,
+            scaleFactor=1.05,
+            minNeighbors=6,
+            minSize=(40, 40),
+            flags=cv2.CASCADE_SCALE_IMAGE
+        )
+        return faces
+    
+    def draw_faces(self, frame, faces):
+        """在帧上绘制人脸框"""
+        # 在随机模式下，只绘制选中的红框
+        if self.random_mode and self.selected_face is not None and self.static_faces is not None:
+            if self.selected_face < len(self.static_faces):
+                x, y, w, h = self.static_faces[self.selected_face]
+                cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 0, 255), 3)  # 选中的为红色
+        else:
+            # 在正常模式下，绘制所有人脸框
+            for (x, y, w, h) in faces:
+                cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)  # 绿色
+        
+        return frame
+    
+    def draw_button(self, frame):
+        """绘制按钮"""
+        button_text = "Reset" if self.random_mode else "Random"
+        button_color = (0, 0, 255) if self.random_mode else (0, 255, 0)
+        
+        # 绘制按钮背景
+        cv2.rectangle(frame, (10, 10), (150, 50), button_color, -1)
+        cv2.rectangle(frame, (10, 10), (150, 50), (255, 255, 255), 2)
+        
+        # 绘制按钮文字
+        cv2.putText(frame, button_text, (20, 35), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 255, 255), 2)
+        
+        return frame
+    
+    def toggle_random_mode(self, frame, faces):
+        """切换随机模式"""
+        if not self.random_mode:
+            # 进入随机模式
+            self.random_mode = True
+            if len(faces) > 0:
+                self.selected_face = random.randint(0, len(faces)-1)
+                self.static_frame = frame.copy()
+                self.static_faces = faces.copy()  # 保存静态状态下的人脸位置
+            else:
+                self.selected_face = None
+                self.static_frame = None
+                self.static_faces = None
+        else:
+            # 退出随机模式
+            self.random_mode = False
+            self.selected_face = None
+            self.static_frame = None
+            self.static_faces = None
+    
+    def process_frame(self, frame):
+        """处理每一帧"""
+        # 检测人脸
+        faces = self.detect_faces(frame)
+        
+        # 更新人脸队列
+        if len(faces) > 0:
+            self.face_queue.append(faces)
+        
+        # 使用队列中最新的人脸数据
+        current_faces = faces
+        if self.face_queue:
+            current_faces = self.face_queue[-1]
+        
+        # 处理随机模式
+        if self.random_mode:
+            if self.static_frame is not None:
+                # 使用静态帧，只绘制选中的红框
+                display_frame = self.static_frame.copy()
+                display_frame = self.draw_faces(display_frame, current_faces)
+            else:
+                display_frame = frame.copy()
+        else:
+            # 在实时帧上绘制所有人脸
+            display_frame = self.draw_faces(frame.copy(), current_faces)
+        
+        # 绘制按钮
+        display_frame = self.draw_button(display_frame)
+        
+        return display_frame
+    
+    def run(self):
+        """运行主程序"""
+        cap = cv2.VideoCapture(0)
+        
+        if not cap.isOpened():
+            return
+        
+        # 获取摄像头分辨率并设置窗口大小
+        ret, frame = cap.read()
+        if ret:
+            height, width = frame.shape[:2]
+            cv2.resizeWindow(self.window_name, width, height)
+        
+        while self.running:
+            ret, frame = cap.read()
+            if not ret:
+                cv2.waitKey(1000)
+                continue
+            
+            # 处理帧
+            display_frame = self.process_frame(frame)
+            
+            # 显示结果
+            cv2.imshow(self.window_name, display_frame)
+            
+            # 处理鼠标点击
+            def mouse_callback(event, x, y, flags, param):
+                if event == cv2.EVENT_LBUTTONDOWN:
+                    # 检查是否点击了按钮区域
+                    if 10 <= x <= 150 and 10 <= y <= 50:
+                        faces = self.detect_faces(frame)
+                        self.toggle_random_mode(frame, faces)
+            
+            cv2.setMouseCallback(self.window_name, mouse_callback)
+            
+            # 处理键盘输入和窗口关闭事件
+            key = cv2.waitKey(1) & 0xFF
+            if key == ord('q') or key == 27:  # 'q' 或 ESC 键退出
+                self.running = False
+                break
+            
+            # 检查窗口是否被关闭
+            try:
+                if cv2.getWindowProperty(self.window_name, cv2.WND_PROP_VISIBLE) <= 0:
+                    self.running = False
+                    break
+            except:
+                self.running = False
+                break
+        
+        # 释放资源
+        cap.release()
+        cv2.destroyAllWindows()
+        sys.exit(0)
+
+if __name__ == "__main__":
+    app = FaceSelector()
+    app.run()