[feat] 3.6

.idea/.gitignore

@@ -0,0 +1,5 @@
+# 默认忽略的文件
+/shelf/
+/workspace.xml
+# 基于编辑器的 HTTP 客户端请求
+/httpRequests/

.idea/.name

@@ -0,0 +1 @@
+3-2.py

.idea/face-random.iml

@@ -0,0 +1,8 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$" />
+    <orderEntry type="jdk" jdkName="Python 3.10" jdkType="Python SDK" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+</module>

.idea/inspectionProfiles/profiles_settings.xml

@@ -0,0 +1,6 @@
+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>

.idea/misc.xml

@@ -0,0 +1,7 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="Black">
+    <option name="sdkName" value="Python 3.10" />
+  </component>
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.10" project-jdk-type="Python SDK" />
+</project>

.idea/modules.xml

@@ -0,0 +1,8 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/face-random.iml" filepath="$PROJECT_DIR$/.idea/face-random.iml" />
+    </modules>
+  </component>
+</project>

.idea/vcs.xml

@@ -0,0 +1,6 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="" vcs="Git" />
+  </component>
+</project>

1.py

@@ -2,9 +2,9 @@ import sys
 import random
 import cv2
 from cvzone.FaceDetectionModule import FaceDetector
-from PyQt6.QtCore import QTimer
-from PyQt6.QtGui import QImage, QPixmap
-from PyQt6.QtWidgets import QApplication, QWidget, QLabel, QPushButton
+from PySide6.QtCore import QTimer
+from PySide6.QtGui import QImage, QPixmap
+from PySide6.QtWidgets import QApplication, QWidget, QLabel, QPushButton
 
 
 class FaceRandomApp(QWidget):

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()

3-1.py

@@ -0,0 +1,199 @@
+import sys
+import random
+import cv2
+from cvzone.FaceDetectionModule import FaceDetector
+from PySide6.QtCore import QTimer
+from PySide6.QtGui import QImage, QPixmap
+from PySide6.QtWidgets import QApplication, QWidget, QLabel, QPushButton
+
+
+class FaceRandomApp(QWidget):
+    def __init__(self):
+        super().__init__()
+
+        self.setWindowTitle("Face Random Selector")
+        
+        # 状态：normal → random
+        self.state = "normal"
+        self.selected_face_index = -1
+        self.static_frame = None  # 保存随机状态下的静态画面
+        self.all_faces_snapshot = []  # 保存所有人脸信息快照
+
+        # ---------------- 摄像头 ----------------
+        self.cap = cv2.VideoCapture(0)
+        
+        # 设置摄像头分辨率
+        self.cap.set(3, 1280)
+        self.cap.set(4, 720)
+        
+        # 设置窗口初始大小
+        self.resize(1280, 720)
+        
+        # 使用长距离模型和更低的人脸检测阈值以提高检测率
+        self.detector = FaceDetector(minDetectionCon=0.25, modelSelection=1)
+
+        # ---------------- 创建界面 ----------------
+        self.setup_ui()
+
+        self.faces = []
+
+    def setup_ui(self):
+        # 视频标签 - 填充整个窗口
+        self.video_label = QLabel(self)
+        self.video_label.setStyleSheet("background:#000;")
+        self.video_label.setGeometry(0, 0, self.width(), self.height())
+
+        # 按钮 - 叠加在视频上
+        self.btn = QPushButton("随机", self)
+        self.btn.setFixedSize(140, 55)
+        self.btn.setStyleSheet("""
+            QPushButton {
+                background-color: rgba(0, 0, 0, 120);
+                color: white;
+                font-size: 20px;
+                padding: 10px 20px;
+                border-radius: 8px;
+            }
+            QPushButton:hover {
+                background-color: rgba(30, 30, 30, 180);
+            }
+        """)
+        self.btn.clicked.connect(self.button_clicked)
+        
+        # 初始按钮位置
+        self.update_button_position()
+
+    def resizeEvent(self, event):
+        """窗口大小改变时自动调整视频和按钮位置"""
+        self.video_label.setGeometry(0, 0, self.width(), self.height())
+        self.update_button_position()
+        super().resizeEvent(event)
+
+    def update_button_position(self):
+        """更新按钮位置"""
+        btn_w = 140
+        btn_h = 55
+        margin = 20
+        self.btn.setGeometry(
+            margin,
+            self.height() - btn_h - margin,
+            btn_w,
+            btn_h
+        )
+
+    # ---------------------------------------------------------
+    # 逻辑按钮：随机 ↔ 重置
+    # ---------------------------------------------------------
+    def button_clicked(self):
+        if self.state == "normal":
+            # 切换到随机状态
+            self.state = "random"
+            self.btn.setText("重置")
+
+            # 随机选择一个人脸
+            if len(self.faces) > 0:
+                self.selected_face_index = random.randint(0, len(self.faces) - 1)
+
+                # 保存当前帧作为静态画面
+                ret, img = self.cap.read()
+                if ret:
+                    img = cv2.flip(img, 1)
+                    # 调整图像大小以适应窗口
+                    img = cv2.resize(img, (self.video_label.width(), self.video_label.height()))
+                    self.static_frame = img.copy()
+                    self.all_faces_snapshot = self.faces.copy()
+        else:  # self.state == "random"
+            # 切换回初始状态
+            self.state = "normal"
+            self.selected_face_index = -1
+            self.static_frame = None
+            self.all_faces_snapshot = []
+            self.btn.setText("随机")
+
+    # ---------------------------------------------------------
+    # 刷视频帧
+    # ---------------------------------------------------------
+    def update_frame(self):
+        # ============================
+        # 状态：normal（检测所有人脸并显示绿框）
+        # ============================
+        if self.state == "normal":
+            ret, img = self.cap.read()
+            if not ret:
+                return
+
+            img = cv2.flip(img, 1)
+            
+            # 调整图像大小以适应窗口
+            img = cv2.resize(img, (self.video_label.width(), self.video_label.height()))
+
+            # 检测人脸
+            img, faces = self.detector.findFaces(img, draw=False)
+            self.faces = faces if faces else []
+
+            # 绘制所有人脸为绿色
+            for face in self.faces:
+                x, y, w, h = face["bbox"]
+                score = face["score"][0]
+                cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 3)
+                cv2.putText(img, f"{score:.2f}", (x, y - 10),
+                            cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 255, 0), 2)
+
+            # 显示图像
+            self.display_image(img)
+
+        # ============================
+        # 状态：random（显示静态画面，选中的人脸为红色，其他为绿色）
+        # ============================
+        elif self.state == "random" and self.static_frame is not None:
+            img = self.static_frame.copy()
+
+            # 绘制所有人脸，选中的为红色，其他为绿色
+            for i, face in enumerate(self.all_faces_snapshot):
+                x, y, w, h = face["bbox"]
+                score = face["score"][0]
+
+                if i == self.selected_face_index:
+                    color = (0, 0, 255)  # 红色
+                else:
+                    color = (0, 255, 0)  # 绿色
+
+                cv2.rectangle(img, (x, y), (x + w, y + h), color, 3)
+                cv2.putText(img, f"{score:.2f}", (x, y - 10),
+                            cv2.FONT_HERSHEY_SIMPLEX, 0.6, color, 2)
+
+            # 显示图像
+            self.display_image(img)
+
+    # ---------------------------------------------------------
+    # 显示图像到 QLabel
+    # ---------------------------------------------------------
+    def display_image(self, img):
+        rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+        h, w, ch = rgb.shape
+        bytes_per_line = ch * w
+        qimg = QImage(rgb.data, w, h, bytes_per_line, QImage.Format.Format_RGB888)
+        self.video_label.setPixmap(QPixmap.fromImage(qimg))
+
+    # ---------------------------------------------------------
+    def closeEvent(self, event):
+        if self.cap.isOpened():
+            self.cap.release()
+        event.accept()
+
+
+def main():
+    app = QApplication(sys.argv)
+    window = FaceRandomApp()
+    window.show()
+    
+    # 启动定时器
+    timer = QTimer()
+    timer.timeout.connect(window.update_frame)
+    timer.start(30)
+    
+    sys.exit(app.exec())
+
+
+if __name__ == "__main__":
+    main()

3-2.py

@@ -0,0 +1,266 @@
+import sys
+import random
+import cv2
+from cvzone.FaceDetectionModule import FaceDetector
+from PySide6.QtCore import QTimer, Qt
+from PySide6.QtGui import QImage, QPixmap
+from PySide6.QtWidgets import QApplication, QWidget, QLabel, QPushButton, QVBoxLayout, QProgressBar
+
+
+class LoadingScreen(QWidget):
+    def __init__(self):
+        super().__init__()
+        self.setWindowTitle("加载中...")
+        self.setFixedSize(300, 150)
+        self.setWindowFlags(Qt.FramelessWindowHint | Qt.WindowStaysOnTopHint)
+        self.setStyleSheet("background-color: #1E90FF;")  # 蓝色背景
+        
+        # 创建布局
+        layout = QVBoxLayout()
+        layout.setAlignment(Qt.AlignCenter)
+        layout.setSpacing(15)
+        
+        # 加载提示文字
+        self.loading_label = QLabel("人脸模型加载中")
+        self.loading_label.setAlignment(Qt.AlignCenter)
+        self.loading_label.setStyleSheet("color: white; font-size: 18px; font-weight: bold;")
+        layout.addWidget(self.loading_label)
+        
+        # 进度条 - 设置为不确定模式，显示加载动画
+        self.progress_bar = QProgressBar()
+        self.progress_bar.setRange(0, 0)  # 设置为0,0表示不确定模式
+        self.progress_bar.setFixedHeight(10)
+        self.progress_bar.setStyleSheet("""
+            QProgressBar {
+                border: 1px solid rgba(255, 255, 255, 100);
+                border-radius: 5px;
+                background-color: rgba(255, 255, 255, 50);
+            }
+            QProgressBar::chunk {
+                background-color: white;
+                border-radius: 4px;
+            }
+        """)
+        layout.addWidget(self.progress_bar)
+        
+        self.setLayout(layout)
+
+
+class FaceRandomApp(QWidget):
+    def __init__(self):
+        super().__init__()
+        
+        # 先显示加载页面
+        self.loading_screen = LoadingScreen()
+        self.loading_screen.show()
+        
+        # 延迟初始化主界面，让加载页面先显示
+        QTimer.singleShot(100, self.initialize_app)
+
+    def initialize_app(self):
+        # 设置窗口标题
+        self.setWindowTitle("Face Random Selector")
+        
+        # 状态：normal → random
+        self.state = "normal"
+        self.selected_face_index = -1
+        self.static_frame = None  # 保存随机状态下的静态画面
+        self.all_faces_snapshot = []  # 保存所有人脸信息快照
+
+        # ---------------- 摄像头 ----------------
+        self.cap = cv2.VideoCapture(0)
+        
+        # 设置摄像头分辨率
+        self.cap.set(3, 1280)
+        self.cap.set(4, 720)
+        
+        # 设置窗口初始大小
+        self.resize(1280, 720)
+        
+        # 使用长距离模型和更低的人脸检测阈值以提高检测率
+        # 这里会加载模型，可能需要一些时间
+        try:
+            self.detector = FaceDetector(minDetectionCon=0.25, modelSelection=1)
+        except Exception as e:
+            print(f"初始化人脸检测器时出错: {e}")
+            # 如果初始化失败，使用一个空的检测器
+            self.detector = None
+
+        # ---------------- 创建界面 ----------------
+        self.setup_ui()
+
+        self.faces = []
+        
+        # 模拟加载完成
+        QTimer.singleShot(2000, self.finish_loading)
+
+    def finish_loading(self):
+        # 关闭加载页面
+        self.loading_screen.close()
+        # 显示主窗口
+        self.show()
+        
+        # 启动定时器更新视频帧
+        self.timer = QTimer()
+        self.timer.timeout.connect(self.update_frame)
+        self.timer.start(30)
+
+    def setup_ui(self):
+        # 视频标签 - 填充整个窗口
+        self.video_label = QLabel(self)
+        self.video_label.setStyleSheet("background:#000;")
+        self.video_label.setGeometry(0, 0, self.width(), self.height())
+
+        # 按钮 - 叠加在视频上
+        self.btn = QPushButton("随机", self)
+        self.btn.setFixedSize(140, 55)
+        self.btn.setStyleSheet("""
+            QPushButton {
+                background-color: rgba(0, 0, 0, 120);
+                color: white;
+                font-size: 20px;
+                padding: 10px 20px;
+                border-radius: 8px;
+            }
+            QPushButton:hover {
+                background-color: rgba(30, 30, 30, 180);
+            }
+        """)
+        self.btn.clicked.connect(self.button_clicked)
+        
+        # 初始按钮位置
+        self.update_button_position()
+
+    def resizeEvent(self, event):
+        """窗口大小改变时自动调整视频和按钮位置"""
+        self.video_label.setGeometry(0, 0, self.width(), self.height())
+        self.update_button_position()
+        super().resizeEvent(event)
+
+    def update_button_position(self):
+        """更新按钮位置"""
+        btn_w = 140
+        btn_h = 55
+        margin = 20
+        self.btn.setGeometry(
+            margin,
+            self.height() - btn_h - margin,
+            btn_w,
+            btn_h
+        )
+
+    # ---------------------------------------------------------
+    # 逻辑按钮：随机 ↔ 重置
+    # ---------------------------------------------------------
+    def button_clicked(self):
+        if self.state == "normal":
+            # 切换到随机状态
+            self.state = "random"
+            self.btn.setText("重置")
+
+            # 随机选择一个人脸
+            if len(self.faces) > 0:
+                self.selected_face_index = random.randint(0, len(self.faces) - 1)
+
+                # 保存当前帧作为静态画面
+                ret, img = self.cap.read()
+                if ret:
+                    img = cv2.flip(img, 1)
+                    # 调整图像大小以适应窗口
+                    img = cv2.resize(img, (self.video_label.width(), self.video_label.height()))
+                    self.static_frame = img.copy()
+                    self.all_faces_snapshot = self.faces.copy()
+        else:  # self.state == "random"
+            # 切换回初始状态
+            self.state = "normal"
+            self.selected_face_index = -1
+            self.static_frame = None
+            self.all_faces_snapshot = []
+            self.btn.setText("随机")
+
+    # ---------------------------------------------------------
+    # 刷视频帧
+    # ---------------------------------------------------------
+    def update_frame(self):
+        # ============================
+        # 状态：normal（检测所有人脸并显示绿框）
+        # ============================
+        if self.state == "normal":
+            ret, img = self.cap.read()
+            if not ret:
+                return
+
+            img = cv2.flip(img, 1)
+            
+            # 调整图像大小以适应窗口
+            img = cv2.resize(img, (self.video_label.width(), self.video_label.height()))
+
+            # 检测人脸
+            if self.detector is not None:
+                img, faces = self.detector.findFaces(img, draw=False)
+                self.faces = faces if faces else []
+            else:
+                self.faces = []
+
+            # 绘制所有人脸为绿色
+            for face in self.faces:
+                x, y, w, h = face["bbox"]
+                score = face["score"][0]
+                cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 3)
+                cv2.putText(img, f"{score:.2f}", (x, y - 10),
+                            cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 255, 0), 2)
+
+            # 显示图像
+            self.display_image(img)
+
+        # ============================
+        # 状态：random（显示静态画面，选中的人脸为红色，其他为绿色）
+        # ============================
+        elif self.state == "random" and self.static_frame is not None:
+            img = self.static_frame.copy()
+
+            # 绘制所有人脸，选中的为红色，其他为绿色
+            for i, face in enumerate(self.all_faces_snapshot):
+                x, y, w, h = face["bbox"]
+                score = face["score"][0]
+
+                if i == self.selected_face_index:
+                    color = (0, 0, 255)  # 红色
+                else:
+                    color = (0, 255, 0)  # 绿色
+
+                cv2.rectangle(img, (x, y), (x + w, y + h), color, 3)
+                cv2.putText(img, f"{score:.2f}", (x, y - 10),
+                            cv2.FONT_HERSHEY_SIMPLEX, 0.6, color, 2)
+
+            # 显示图像
+            self.display_image(img)
+
+    # ---------------------------------------------------------
+    # 显示图像到 QLabel
+    # ---------------------------------------------------------
+    def display_image(self, img):
+        rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+        h, w, ch = rgb.shape
+        bytes_per_line = ch * w
+        qimg = QImage(rgb.data, w, h, bytes_per_line, QImage.Format.Format_RGB888)
+        self.video_label.setPixmap(QPixmap.fromImage(qimg))
+
+    # ---------------------------------------------------------
+    def closeEvent(self, event):
+        if self.cap.isOpened():
+            self.cap.release()
+        event.accept()
+
+
+def main():
+    app = QApplication(sys.argv)
+    
+    # 直接创建主应用窗口，它内部会处理加载页面
+    window = FaceRandomApp()
+    
+    sys.exit(app.exec())
+
+
+if __name__ == "__main__":
+    main()

3-3.py

@@ -0,0 +1,275 @@
+import sys
+import random
+import cv2
+from cvzone.FaceDetectionModule import FaceDetector
+from PySide6.QtCore import QTimer, Qt
+from PySide6.QtGui import QImage, QPixmap
+from PySide6.QtWidgets import QApplication, QWidget, QLabel, QPushButton, QVBoxLayout, QProgressBar
+
+
+class LoadingScreen(QWidget):
+    def __init__(self):
+        super().__init__()
+        self.setWindowTitle("加载中...")
+        self.setFixedSize(300, 150)
+        self.setWindowFlags(Qt.FramelessWindowHint | Qt.WindowStaysOnTopHint)
+        self.setStyleSheet("background-color: #1E90FF;")  # 蓝色背景
+        
+        # 创建布局
+        layout = QVBoxLayout()
+        layout.setAlignment(Qt.AlignCenter)
+        layout.setSpacing(15)
+        
+        # 加载提示文字
+        self.loading_label = QLabel("人脸模型加载中")
+        self.loading_label.setAlignment(Qt.AlignCenter)
+        self.loading_label.setStyleSheet("color: white; font-size: 18px; font-weight: bold;")
+        layout.addWidget(self.loading_label)
+        
+        # 进度条 - 设置为不确定模式，显示加载动画
+        self.progress_bar = QProgressBar()
+        self.progress_bar.setRange(0, 0)  # 设置为0,0表示不确定模式
+        self.progress_bar.setFixedHeight(10)
+        self.progress_bar.setStyleSheet("""
+            QProgressBar {
+                border: 1px solid rgba(255, 255, 255, 100);
+                border-radius: 5px;
+                background-color: rgba(255, 255, 255, 50);
+            }
+            QProgressBar::chunk {
+                background-color: white;
+                border-radius: 4px;
+            }
+        """)
+        layout.addWidget(self.progress_bar)
+        
+        self.setLayout(layout)
+
+
+class FaceRandomApp(QWidget):
+    def __init__(self):
+        super().__init__()
+        
+        # 先显示加载页面
+        self.loading_screen = LoadingScreen()
+        self.loading_screen.show()
+        
+        # 强制立即处理GUI事件，确保加载页面能立即显示
+        QApplication.processEvents()
+        
+        # 延迟初始化主界面，让加载页面先显示
+        QTimer.singleShot(100, self.initialize_app)
+
+    def initialize_app(self):
+        # 设置窗口标题
+        self.setWindowTitle("Face Random Selector")
+        
+        # 状态：normal → random
+        self.state = "normal"
+        self.selected_face_index = -1
+        self.static_frame = None  # 保存随机状态下的静态画面
+        self.all_faces_snapshot = []  # 保存所有人脸信息快照
+
+        # ---------------- 摄像头 ----------------
+        self.cap = cv2.VideoCapture(0)
+        
+        # 设置摄像头分辨率
+        self.cap.set(3, 1280)
+        self.cap.set(4, 720)
+        
+        # 设置窗口初始大小
+        self.resize(1280, 720)
+        
+        # 更新加载页面文字，提示正在进行人脸模型初始化
+        self.loading_screen.loading_label.setText("正在初始化人脸检测模型...")
+        QApplication.processEvents()
+        
+        # 使用长距离模型和更低的人脸检测阈值以提高检测率
+        # 这里会加载模型，可能需要一些时间
+        try:
+            self.detector = FaceDetector(minDetectionCon=0.25, modelSelection=1)
+            self.loading_screen.loading_label.setText("人脸模型加载完成!")
+        except Exception as e:
+            print(f"初始化人脸检测器时出错: {e}")
+            # 如果初始化失败，使用一个空的检测器
+            self.detector = None
+            self.loading_screen.loading_label.setText("人脸模型加载失败，使用基础模式")
+
+        # ---------------- 创建界面 ----------------
+        self.setup_ui()
+
+        self.faces = []
+        
+        # 模拟加载完成
+        QTimer.singleShot(1500, self.finish_loading)
+
+    def finish_loading(self):
+        # 关闭加载页面
+        self.loading_screen.close()
+        # 显示主窗口
+        self.show()
+        
+        # 启动定时器更新视频帧
+        self.timer = QTimer()
+        self.timer.timeout.connect(self.update_frame)
+        self.timer.start(30)
+
+    def setup_ui(self):
+        # 视频标签 - 填充整个窗口
+        self.video_label = QLabel(self)
+        self.video_label.setStyleSheet("background:#000;")
+        self.video_label.setGeometry(0, 0, self.width(), self.height())
+
+        # 按钮 - 叠加在视频上
+        self.btn = QPushButton("随机", self)
+        self.btn.setFixedSize(140, 55)
+        self.btn.setStyleSheet("""
+            QPushButton {
+                background-color: rgba(0, 0, 0, 120);
+                color: white;
+                font-size: 20px;
+                padding: 10px 20px;
+                border-radius: 8px;
+            }
+            QPushButton:hover {
+                background-color: rgba(30, 30, 30, 180);
+            }
+        """)
+        self.btn.clicked.connect(self.button_clicked)
+        
+        # 初始按钮位置
+        self.update_button_position()
+
+    def resizeEvent(self, event):
+        """窗口大小改变时自动调整视频和按钮位置"""
+        self.video_label.setGeometry(0, 0, self.width(), self.height())
+        self.update_button_position()
+        super().resizeEvent(event)
+
+    def update_button_position(self):
+        """更新按钮位置"""
+        btn_w = 140
+        btn_h = 55
+        margin = 20
+        self.btn.setGeometry(
+            margin,
+            self.height() - btn_h - margin,
+            btn_w,
+            btn_h
+        )
+
+    # ---------------------------------------------------------
+    # 逻辑按钮：随机 ↔ 重置
+    # ---------------------------------------------------------
+    def button_clicked(self):
+        if self.state == "normal":
+            # 切换到随机状态
+            self.state = "random"
+            self.btn.setText("重置")
+
+            # 随机选择一个人脸
+            if len(self.faces) > 0:
+                self.selected_face_index = random.randint(0, len(self.faces) - 1)
+
+                # 保存当前帧作为静态画面
+                ret, img = self.cap.read()
+                if ret:
+                    img = cv2.flip(img, 1)
+                    # 调整图像大小以适应窗口
+                    img = cv2.resize(img, (self.video_label.width(), self.video_label.height()))
+                    self.static_frame = img.copy()
+                    self.all_faces_snapshot = self.faces.copy()
+        else:  # self.state == "random"
+            # 切换回初始状态
+            self.state = "normal"
+            self.selected_face_index = -1
+            self.static_frame = None
+            self.all_faces_snapshot = []
+            self.btn.setText("随机")
+
+    # ---------------------------------------------------------
+    # 刷视频帧
+    # ---------------------------------------------------------
+    def update_frame(self):
+        # ============================
+        # 状态：normal（检测所有人脸并显示绿框）
+        # ============================
+        if self.state == "normal":
+            ret, img = self.cap.read()
+            if not ret:
+                return
+
+            img = cv2.flip(img, 1)
+            
+            # 调整图像大小以适应窗口
+            img = cv2.resize(img, (self.video_label.width(), self.video_label.height()))
+
+            # 检测人脸
+            if self.detector is not None:
+                img, faces = self.detector.findFaces(img, draw=False)
+                self.faces = faces if faces else []
+            else:
+                self.faces = []
+
+            # 绘制所有人脸为绿色
+            for face in self.faces:
+                x, y, w, h = face["bbox"]
+                score = face["score"][0]
+                cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 3)
+                cv2.putText(img, f"{score:.2f}", (x, y - 10),
+                            cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 255, 0), 2)
+
+            # 显示图像
+            self.display_image(img)
+
+        # ============================
+        # 状态：random（显示静态画面，选中的人脸为红色，其他为绿色）
+        # ============================
+        elif self.state == "random" and self.static_frame is not None:
+            img = self.static_frame.copy()
+
+            # 绘制所有人脸，选中的为红色，其他为绿色
+            for i, face in enumerate(self.all_faces_snapshot):
+                x, y, w, h = face["bbox"]
+                score = face["score"][0]
+
+                if i == self.selected_face_index:
+                    color = (0, 0, 255)  # 红色
+                else:
+                    color = (0, 255, 0)  # 绿色
+
+                cv2.rectangle(img, (x, y), (x + w, y + h), color, 3)
+                cv2.putText(img, f"{score:.2f}", (x, y - 10),
+                            cv2.FONT_HERSHEY_SIMPLEX, 0.6, color, 2)
+
+            # 显示图像
+            self.display_image(img)
+
+    # ---------------------------------------------------------
+    # 显示图像到 QLabel
+    # ---------------------------------------------------------
+    def display_image(self, img):
+        rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+        h, w, ch = rgb.shape
+        bytes_per_line = ch * w
+        qimg = QImage(rgb.data, w, h, bytes_per_line, QImage.Format.Format_RGB888)
+        self.video_label.setPixmap(QPixmap.fromImage(qimg))
+
+    # ---------------------------------------------------------
+    def closeEvent(self, event):
+        if self.cap.isOpened():
+            self.cap.release()
+        event.accept()
+
+
+def main():
+    app = QApplication(sys.argv)
+    
+    # 直接创建主应用窗口，它内部会处理加载页面
+    window = FaceRandomApp()
+    
+    sys.exit(app.exec())
+
+
+if __name__ == "__main__":
+    main()

3-4.py

@@ -0,0 +1,339 @@
+import sys
+import os
+import random
+import cv2
+import numpy as np
+from PySide6.QtCore import QTimer, Qt
+from PySide6.QtGui import QImage, QPixmap
+from PySide6.QtWidgets import QApplication, QWidget, QLabel, QPushButton, QSlider, QVBoxLayout, QProgressBar
+
+
+# ======================================================
+# 加载动画界面
+# ======================================================
+class LoadingScreen(QWidget):
+    def __init__(self):
+        super().__init__()
+        self.setWindowTitle("Face Random Selector")
+        self.setFixedSize(300, 150)
+        self.setWindowFlags(Qt.FramelessWindowHint | Qt.WindowStaysOnTopHint)
+        self.setStyleSheet("""
+            background-color: #1E90FF;
+            border-radius: 10px;
+        """)
+
+        # 创建布局
+        layout = QVBoxLayout()
+        layout.setAlignment(Qt.AlignCenter)
+        layout.setSpacing(15)
+
+        # 加载提示文字
+        self.loading_label = QLabel("正在加载模型...")
+        self.loading_label.setAlignment(Qt.AlignCenter)
+        self.loading_label.setStyleSheet("""
+            color: white; 
+            font-size: 18px; 
+            font-weight: bold;
+        """)
+        layout.addWidget(self.loading_label)
+
+        # 进度条 - 设置为不确定模式，显示加载动画
+        self.progress_bar = QProgressBar()
+        self.progress_bar.setRange(0, 0)  # 设置为0,0表示不确定模式
+        self.progress_bar.setFixedHeight(10)
+        self.progress_bar.setStyleSheet("""
+            QProgressBar {
+                border: 1px solid rgba(255, 255, 255, 100);
+                border-radius: 5px;
+                background-color: rgba(255, 255, 255, 50);
+            }
+            QProgressBar::chunk {
+                background-color: white;
+                border-radius: 4px;
+            }
+        """)
+        layout.addWidget(self.progress_bar)
+
+        self.setLayout(layout)
+
+
+# ======================================================
+# YuNet 模型路径
+# ======================================================
+def get_yunet_model_path():
+    base_dir = os.path.dirname(os.path.abspath(__file__))
+    model_path = os.path.join(base_dir, "model", "face_detection_yunet_2023mar.onnx")
+
+    if not os.path.exists(model_path):
+        raise FileNotFoundError(f"YuNet 模型不存在: {model_path}")
+    return model_path
+
+
+# ======================================================
+# 主窗口
+# ======================================================
+class FaceRandomApp(QWidget):
+    def __init__(self):
+        super().__init__()
+        
+        # 先显示加载页面
+        self.loading_screen = LoadingScreen()
+        self.loading_screen.show()
+        
+        # 强制立即处理GUI事件，确保加载页面能立即显示
+        QApplication.processEvents()
+        
+        # 延迟初始化主界面，让加载页面先显示
+        QTimer.singleShot(100, self.initialize_app)
+
+    def initialize_app(self):
+        """初始化应用程序"""
+        # 状态
+        self.state = "normal"
+        self.selected_face_index = -1
+        self.static_frame = None
+        self.faces_snapshot = []
+
+        # 参数
+        self.detection_confidence = 0.6
+        self.faces = []
+
+        # 摄像头
+        self.cap = cv2.VideoCapture(0)
+        self.cap.set(3, 1280)
+        self.cap.set(4, 720)
+
+        # YuNet 加载
+        model_path = get_yunet_model_path()
+        self.detector = cv2.FaceDetectorYN.create(
+            model_path,
+            "",
+            (640, 480),
+            score_threshold=self.detection_confidence,
+            nms_threshold=0.3,
+            top_k=5000
+        )
+
+        # UI
+        self.setup_ui()
+        
+        # 关闭加载界面并显示主窗口
+        self.loading_screen.close()
+        self.show()
+
+        # Timer
+        self.timer = QTimer()
+        self.timer.timeout.connect(self.update_frame)
+        self.timer.start(30)
+
+    # ======================================================
+    # UI
+    # ======================================================
+    def setup_ui(self):
+        self.setWindowTitle("Face Random Selector")
+        self.resize(1280, 720)
+
+        self.video_label = QLabel(self)
+        self.video_label.setGeometry(0, 0, self.width(), self.height())
+        self.video_label.setStyleSheet("background: black;")
+
+        # 按钮 - 简约黑色半透明样式，无边框
+        self.btn = QPushButton("随机", self)
+        self.btn.setFixedSize(140, 55)
+        self.btn.move(20, self.height() - 75)
+        self.btn.clicked.connect(self.on_random_clicked)
+        self.btn.setStyleSheet("""
+            QPushButton {
+                background-color: rgba(0, 0, 0, 180);
+                color: white;
+                font-size: 20px;
+                font-weight: bold;
+                border: none;
+                border-radius: 8px;
+            }
+            QPushButton:hover {
+                background-color: rgba(30, 30, 30, 200);
+            }
+            QPushButton:pressed {
+                background-color: rgba(50, 50, 50, 220);
+            }
+        """)
+
+        # 置信度滑条 - 简约半透明样式
+        self.slider = QSlider(Qt.Horizontal, self)
+        self.slider.setRange(30, 90)
+        self.slider.setValue(int(self.detection_confidence * 100))
+        self.slider.setFixedWidth(200)
+        self.slider.move(120, 20)
+        self.slider.valueChanged.connect(self.on_confidence_change)
+        self.slider.setStyleSheet("""
+            QSlider::groove:horizontal {
+                background: rgba(0, 0, 0, 120);
+                height: 4px;
+                border-radius: 2px;
+            }
+            QSlider::handle:horizontal {
+                background: white;
+                width: 14px;
+                height: 14px;
+                border-radius: 7px;
+                margin: -5px 0;
+            }
+        """)
+
+        # 置信度标签 - 简约白色文字
+        self.conf_label = QLabel("置信度", self)
+        self.conf_label.move(20, 20)
+        self.conf_label.setStyleSheet("""
+            color: white; 
+            font-size: 16px; 
+            font-weight: bold;
+            background: transparent;
+        """)
+
+    # ======================================================
+    def resizeEvent(self, event):
+        self.video_label.setGeometry(0, 0, self.width(), self.height())
+        self.btn.move(20, self.height() - 75)
+        super().resizeEvent(event)
+
+    # ======================================================
+    # 置信度
+    # ======================================================
+    def on_confidence_change(self, value):
+        self.detection_confidence = value / 100.0
+        self.detector.setScoreThreshold(self.detection_confidence)
+
+    # ======================================================
+    # 随机按钮
+    # ======================================================
+    def on_random_clicked(self):
+        if self.state == "normal":
+            self.state = "random"
+            self.btn.setText("重置")
+
+            if len(self.faces) > 0:
+                self.selected_face_index = random.randint(0, len(self.faces) - 1)
+
+                # 捕获静态帧
+                ret, img = self.cap.read()
+                img = cv2.flip(img, 1)
+                img = self.resize_cover(img, self.video_label.width(), self.video_label.height())
+
+                self.static_frame = img.copy()
+                self.faces_snapshot = self.faces.copy()
+
+        else:
+            self.state = "normal"
+            self.btn.setText("随机")
+            self.selected_face_index = -1
+            self.static_frame = None
+
+    # ======================================================
+    # 等比例覆盖（无黑边）
+    # ======================================================
+    def resize_cover(self, img, target_w, target_h):
+        """等比例缩放 + 居中裁切 = 无黑边"""
+        h, w = img.shape[:2]
+
+        scale = max(target_w / w, target_h / h)
+        new_w = int(w * scale)
+        new_h = int(h * scale)
+
+        resized = cv2.resize(img, (new_w, new_h))
+
+        # 居中裁切
+        x_start = (new_w - target_w) // 2
+        y_start = (new_h - target_h) // 2
+
+        cropped = resized[y_start:y_start + target_h, x_start:x_start + target_w]
+        return cropped
+
+    # ======================================================
+    # 绘制人脸框和置信度 - 优化样式
+    # ======================================================
+    def draw_face_with_confidence(self, img, face, color, thickness=2):
+        """绘制人脸框和置信度"""
+        x, y, w, h = map(int, face[:4])
+        score = face[4]  # 置信度分数，范围0-1
+
+        # 绘制人脸框
+        cv2.rectangle(img, (x, y), (x + w, y + h), color, thickness)
+
+        # 绘制置信度文本
+        confidence_text = f"{score:.2f}"
+        text_y = max(y - 10, 20)  # 确保文本不超出图像顶部
+
+        # 绘制半透明文本背景
+        text_size = cv2.getTextSize(confidence_text, cv2.FONT_HERSHEY_SIMPLEX, 0.6, 2)[0]
+        
+        # 创建半透明覆盖层
+        overlay = img.copy()
+        cv2.rectangle(overlay, (x, text_y - text_size[1] - 5),
+                      (x + text_size[0] + 10, text_y + 5), color, -1)
+        
+        # 应用半透明效果
+        alpha = 0.7  # 透明度
+        cv2.addWeighted(overlay, alpha, img, 1 - alpha, 0, img)
+
+        # 绘制文本
+        cv2.putText(img, confidence_text, (x + 5, text_y),
+                    cv2.FONT_HERSHEY_SIMPLEX, 0.6, (255, 255, 255), 2)
+
+    # ======================================================
+    # 主循环
+    # ======================================================
+    def update_frame(self):
+        ret, img = self.cap.read()
+        if not ret:
+            return
+
+        img = cv2.flip(img, 1)
+        img = self.resize_cover(img, self.video_label.width(), self.video_label.height())
+
+        if self.state == "normal":
+            # 设置 YuNet 输入大小
+            self.detector.setInputSize((img.shape[1], img.shape[0]))
+
+            # 检测
+            _, detected = self.detector.detect(img)
+            self.faces = detected if detected is not None else []
+
+            # 画框和置信度
+            for face in self.faces:
+                self.draw_face_with_confidence(img, face, (0, 255, 0), 2)
+
+        else:  # random 模式
+            img = self.static_frame.copy()
+
+            for i, face in enumerate(self.faces_snapshot):
+                color = (0, 0, 255) if i == self.selected_face_index else (0, 255, 0)
+                thickness = 3 if i == self.selected_face_index else 2
+                self.draw_face_with_confidence(img, face, color, thickness)
+
+        self.display(img)
+
+    # ======================================================
+    def display(self, img):
+        rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+        h, w, c = rgb.shape
+        qimg = QImage(rgb.data, w, h, c * w, QImage.Format_RGB888)
+        self.video_label.setPixmap(QPixmap.fromImage(qimg))
+
+    # ======================================================
+    def closeEvent(self, event):
+        if self.cap.isOpened():
+            self.cap.release()
+        event.accept()
+
+
+# ======================================================
+def main():
+    app = QApplication(sys.argv)
+    window = FaceRandomApp()
+    # 注意：这里不再调用 window.show()，因为 FaceRandomApp 内部会处理显示逻辑
+    sys.exit(app.exec())
+
+
+if __name__ == "__main__":
+    main()

3-5.py

@@ -0,0 +1,373 @@
+import sys
+import os
+import random
+import cv2
+from PySide6.QtCore import QTimer, Qt, QThread, Signal
+from PySide6.QtGui import QImage, QPixmap
+from PySide6.QtWidgets import QApplication, QWidget, QLabel, QPushButton, QSlider, QVBoxLayout, QProgressBar
+
+
+# ======================================================
+# 加载动画界面
+# ======================================================
+class LoadingScreen(QWidget):
+    def __init__(self):
+        super().__init__()
+        self.setWindowTitle("Face Random Selector")
+        self.setFixedSize(300, 150)
+        self.setWindowFlags(Qt.FramelessWindowHint | Qt.WindowStaysOnTopHint)
+        self.setStyleSheet("""
+            background-color: #1E90FF;
+            border-radius: 10px;
+        """)
+
+        # 创建布局
+        layout = QVBoxLayout()
+        layout.setAlignment(Qt.AlignCenter)
+        layout.setSpacing(15)
+
+        # 加载提示文字
+        self.loading_label = QLabel("正在加载模型...")
+        self.loading_label.setAlignment(Qt.AlignCenter)
+        self.loading_label.setStyleSheet("""
+            color: white; 
+            font-size: 18px; 
+            font-weight: bold;
+        """)
+        layout.addWidget(self.loading_label)
+
+        # 进度条 - 设置为不确定模式，显示加载动画
+        self.progress_bar = QProgressBar()
+        self.progress_bar.setRange(0, 0)  # 设置为0,0表示不确定模式
+        self.progress_bar.setFixedHeight(10)
+        self.progress_bar.setStyleSheet("""
+            QProgressBar {
+                border: 1px solid rgba(255, 255, 255, 100);
+                border-radius: 5px;
+                background-color: rgba(255, 255, 255, 50);
+            }
+            QProgressBar::chunk {
+                background-color: white;
+                border-radius: 4px;
+            }
+        """)
+        layout.addWidget(self.progress_bar)
+
+        self.setLayout(layout)
+
+
+# ======================================================
+# 模型加载线程
+# ======================================================
+class ModelLoader(QThread):
+    loaded = Signal(object, str)  # 模型加载完成信号
+    progress = Signal(str)  # 进度更新信号
+
+    def __init__(self, model_path):
+        super().__init__()
+        self.model_path = model_path
+
+    def run(self):
+        try:
+            # 模拟进度更新
+            self.progress.emit("正在初始化模型...")
+
+            # 延迟加载检测器
+            detector = cv2.FaceDetectorYN.create(
+                self.model_path,
+                "",
+                (640, 480),
+                score_threshold=0.6,
+                nms_threshold=0.3,
+                top_k=5000
+            )
+
+            self.progress.emit("模型加载完成")
+            self.loaded.emit(detector, "")
+        except Exception as e:
+            self.loaded.emit(None, str(e))
+
+
+# ======================================================
+# 主窗口
+# ======================================================
+class FaceRandomApp(QWidget):
+    def __init__(self):
+        super().__init__()
+
+        # 先显示加载页面
+        self.loading_screen = LoadingScreen()
+        self.loading_screen.show()
+
+        # 强制立即处理GUI事件，确保加载页面能立即显示
+        QApplication.processEvents()
+
+        # 延迟初始化主界面
+        QTimer.singleShot(100, self.initialize_app)
+
+    def initialize_app(self):
+        """初始化应用程序"""
+        # 状态
+        self.state = "normal"
+        self.selected_face_index = -1
+        self.static_frame = None
+        self.faces_snapshot = []
+        self.faces = []
+        self.detection_confidence = 0.6
+
+        # 初始化摄像头 - 使用原代码的高分辨率设置
+        self.cap = cv2.VideoCapture(0)
+        if self.cap.isOpened():
+            self.cap.set(cv2.CAP_PROP_FRAME_WIDTH, 1280)
+            self.cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 720)
+            # 提高图像质量设置
+            self.cap.set(cv2.CAP_PROP_FPS, 30)
+
+        # UI
+        self.setup_ui()
+
+        # 启动模型加载
+        self.start_model_loading()
+
+    def start_model_loading(self):
+        """启动模型加载"""
+        model_path = self.get_yunet_model_path()
+        if model_path:
+            self.loader = ModelLoader(model_path)
+            self.loader.loaded.connect(self.on_model_loaded)
+            self.loader.progress.connect(self.on_loading_progress)
+            self.loader.start()
+        else:
+            # 如果没有模型，跳过模型加载
+            self.loading_screen.close()
+            self.show()
+            self.timer = QTimer()
+            self.timer.timeout.connect(self.update_frame)
+            self.timer.start(30)
+
+    def get_yunet_model_path(self):
+        """获取模型路径"""
+        base_dir = os.path.dirname(os.path.abspath(__file__))
+        model_path = os.path.join(base_dir, "model", "face_detection_yunet_2023mar.onnx")
+        return model_path if os.path.exists(model_path) else None
+
+    def on_loading_progress(self, message):
+        """加载进度更新"""
+        self.loading_screen.loading_label.setText(message)
+
+    def on_model_loaded(self, detector, error):
+        """模型加载完成回调"""
+        if detector and not error:
+            self.detector = detector
+            # 更新置信度
+            self.detector.setScoreThreshold(self.detection_confidence)
+        else:
+            print(f"模型加载失败: {error}")
+
+        # 关闭加载界面并显示主窗口
+        self.loading_screen.close()
+        self.show()
+
+        # 启动视频更新定时器
+        self.timer = QTimer()
+        self.timer.timeout.connect(self.update_frame)
+        self.timer.start(30)
+
+    # ======================================================
+    # UI
+    # ======================================================
+    def setup_ui(self):
+        self.setWindowTitle("Face Random Selector")
+        self.resize(1280, 720)
+
+        self.video_label = QLabel(self)
+        self.video_label.setGeometry(0, 0, self.width(), self.height())
+        self.video_label.setStyleSheet("background: black;")
+
+        # 随机按钮
+        self.btn = QPushButton("随机", self)
+        self.btn.setFixedSize(140, 55)
+        self.btn.move(20, self.height() - 75)
+        self.btn.clicked.connect(self.on_random_clicked)
+        self.btn.setStyleSheet("""
+            QPushButton {
+                background-color: rgba(0, 0, 0, 180);
+                color: white;
+                font-size: 20px;
+                font-weight: bold;
+                border: none;
+                border-radius: 8px;
+            }
+            QPushButton:hover {
+                background-color: rgba(30, 30, 30, 200);
+            }
+            QPushButton:pressed {
+                background-color: rgba(50, 50, 50, 220);
+            }
+        """)
+
+        # 置信度滑条
+        self.slider = QSlider(Qt.Horizontal, self)
+        self.slider.setRange(30, 90)
+        self.slider.setValue(int(self.detection_confidence * 100))
+        self.slider.setFixedWidth(200)
+        self.slider.move(120, 20)
+        self.slider.valueChanged.connect(self.on_confidence_change)
+        self.slider.setStyleSheet("""
+            QSlider::groove:horizontal {
+                background: rgba(0, 0, 0, 120);
+                height: 4px;
+                border-radius: 2px;
+            }
+            QSlider::handle:horizontal {
+                background: white;
+                width: 14px;
+                height: 14px;
+                border-radius: 7px;
+                margin: -5px 0;
+            }
+        """)
+
+        # 置信度标签
+        self.conf_label = QLabel("置信度", self)
+        self.conf_label.move(20, 20)
+        self.conf_label.setStyleSheet("""
+            color: white; 
+            font-size: 16px; 
+            font-weight: bold;
+            background: transparent;
+        """)
+
+    def resizeEvent(self, event):
+        self.video_label.setGeometry(0, 0, self.width(), self.height())
+        self.btn.move(20, self.height() - 75)
+        super().resizeEvent(event)
+
+    def on_confidence_change(self, value):
+        self.detection_confidence = value / 100.0
+        if hasattr(self, 'detector'):
+            self.detector.setScoreThreshold(self.detection_confidence)
+
+    def on_random_clicked(self):
+        if self.state == "normal":
+            self.state = "random"
+            self.btn.setText("重置")
+
+            if len(self.faces) > 0:
+                self.selected_face_index = random.randint(0, len(self.faces) - 1)
+
+                # 捕获静态帧
+                if self.cap and self.cap.isOpened():
+                    ret, img = self.cap.read()
+                    if ret:
+                        img = cv2.flip(img, 1)
+                        img = self.resize_cover(img, self.video_label.width(), self.video_label.height())
+                        self.static_frame = img.copy()
+                        self.faces_snapshot = self.faces.copy()
+        else:
+            self.state = "normal"
+            self.btn.setText("随机")
+            self.selected_face_index = -1
+            self.static_frame = None
+
+    def resize_cover(self, img, target_w, target_h):
+        h, w = img.shape[:2]
+        scale = max(target_w / w, target_h / h)
+        new_w = int(w * scale)
+        new_h = int(h * scale)
+        resized = cv2.resize(img, (new_w, new_h))
+        x_start = (new_w - target_w) // 2
+        y_start = (new_h - target_h) // 2
+        return resized[y_start:y_start + target_h, x_start:x_start + target_w]
+
+    def draw_face_with_confidence(self, img, face, color, thickness=2):
+        """绘制人脸框和置信度"""
+        x, y, w, h = map(int, face[:4])
+        score = face[4]
+
+        # 绘制人脸框
+        cv2.rectangle(img, (x, y), (x + w, y + h), color, thickness)
+
+        # 绘制置信度文本
+        confidence_text = f"{score:.2f}"
+        text_y = max(y - 10, 20)
+
+        # 创建半透明背景
+        overlay = img.copy()
+        text_size = cv2.getTextSize(confidence_text, cv2.FONT_HERSHEY_SIMPLEX, 0.6, 2)[0]
+        cv2.rectangle(overlay, (x, text_y - text_size[1] - 5),
+                      (x + text_size[0] + 10, text_y + 5), color, -1)
+
+        # 应用透明度
+        alpha = 0.7
+        cv2.addWeighted(overlay, alpha, img, 1 - alpha, 0, img)
+
+        # 绘制文本
+        cv2.putText(img, confidence_text, (x + 5, text_y),
+                    cv2.FONT_HERSHEY_SIMPLEX, 0.6, (255, 255, 255), 2)
+
+    def update_frame(self):
+        if not self.cap or not self.cap.isOpened():
+            return
+
+        ret, img = self.cap.read()
+        if not ret:
+            return
+
+        # 使用原代码的镜像翻转
+        img = cv2.flip(img, 1)
+
+        # 使用原代码的resize_cover方法，保持视野大小
+        img = self.resize_cover(img, self.video_label.width(), self.video_label.height())
+
+        if self.state == "normal":
+            if hasattr(self, 'detector'):
+                # 设置检测器输入大小
+                self.detector.setInputSize((img.shape[1], img.shape[0]))
+
+                # 检测人脸
+                _, detected = self.detector.detect(img)
+                self.faces = detected if detected is not None else []
+
+                # 绘制检测结果
+                for face in self.faces:
+                    self.draw_face_with_confidence(img, face, (0, 255, 0), 2)
+            else:
+                # 如果没有模型，只显示原始图像
+                pass
+        else:  # random 模式
+            if self.static_frame is not None:
+                img = self.static_frame.copy()
+                for i, face in enumerate(self.faces_snapshot):
+                    color = (0, 0, 255) if i == self.selected_face_index else (0, 255, 0)
+                    thickness = 3 if i == self.selected_face_index else 2
+                    self.draw_face_with_confidence(img, face, color, thickness)
+
+        self.display(img)
+
+    def display(self, img):
+        # 保持原代码的图像显示方式
+        rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+        h, w, c = rgb.shape
+        qimg = QImage(rgb.data, w, h, c * w, QImage.Format_RGB888)
+        self.video_label.setPixmap(QPixmap.fromImage(qimg))
+
+    def closeEvent(self, event):
+        if self.cap and self.cap.isOpened():
+            self.cap.release()
+        if hasattr(self, 'loader') and self.loader.isRunning():
+            self.loader.quit()
+            self.loader.wait()
+        event.accept()
+
+
+# ======================================================
+def main():
+    app = QApplication(sys.argv)
+    window = FaceRandomApp()
+    # 注意：这里不再调用 window.show()，因为 FaceRandomApp 内部会处理显示逻辑
+    sys.exit(app.exec())
+
+
+if __name__ == "__main__":
+    main()

3-6.py

@@ -0,0 +1,425 @@
+import sys
+import os
+import random
+import cv2
+import numpy as np
+from PySide6.QtCore import QTimer, Qt, QThread, Signal
+from PySide6.QtGui import QImage, QPixmap
+from PySide6.QtWidgets import QApplication, QWidget, QLabel, QPushButton, QSlider, QVBoxLayout, QProgressBar
+
+
+# ======================================================
+# 加载动画界面
+# ======================================================
+class LoadingScreen(QWidget):
+    def __init__(self):
+        super().__init__()
+        self.setWindowTitle("Face Random Selector")
+        self.setFixedSize(300, 150)
+        self.setWindowFlags(Qt.FramelessWindowHint | Qt.WindowStaysOnTopHint)
+        self.setStyleSheet("""
+            background-color: #1E90FF;
+            border-radius: 10px;
+        """)
+
+        # 创建布局
+        layout = QVBoxLayout()
+        layout.setAlignment(Qt.AlignCenter)
+        layout.setSpacing(15)
+
+        # 加载提示文字
+        self.loading_label = QLabel("正在加载模型...")
+        self.loading_label.setAlignment(Qt.AlignCenter)
+        self.loading_label.setStyleSheet("""
+            color: white; 
+            font-size: 18px; 
+            font-weight: bold;
+        """)
+        layout.addWidget(self.loading_label)
+
+        # 进度条 - 设置为不确定模式，显示加载动画
+        self.progress_bar = QProgressBar()
+        self.progress_bar.setRange(0, 0)  # 设置为0,0表示不确定模式
+        self.progress_bar.setFixedHeight(10)
+        self.progress_bar.setStyleSheet("""
+            QProgressBar {
+                border: 1px solid rgba(255, 255, 255, 100);
+                border-radius: 5px;
+                background-color: rgba(255, 255, 255, 50);
+            }
+            QProgressBar::chunk {
+                background-color: white;
+                border-radius: 4px;
+            }
+        """)
+        layout.addWidget(self.progress_bar)
+
+        self.setLayout(layout)
+
+
+# ======================================================
+# 模型加载线程
+# ======================================================
+class ModelLoader(QThread):
+    loaded = Signal(object, str)  # 模型加载完成信号
+    progress = Signal(str)  # 进度更新信号
+
+    def __init__(self, model_path):
+        super().__init__()
+        self.model_path = model_path
+
+    def run(self):
+        try:
+            # 模拟进度更新
+            self.progress.emit("正在初始化模型...")
+
+            # 启用 OpenCV 的优化并设置线程数，减少模型加载/运算开销
+            try:
+                cv2.setUseOptimized(True)
+            except Exception:
+                pass
+
+            # 延迟加载检测器。
+            detector = cv2.FaceDetectorYN.create(
+                self.model_path,
+                "",
+                (320, 240),
+                score_threshold=0.6,
+                nms_threshold=0.3,
+                top_k=5000
+            )
+
+            self.progress.emit("模型加载完成")
+            self.loaded.emit(detector, "")
+        except Exception as e:
+            self.loaded.emit(None, str(e))
+
+
+# ======================================================
+# 主窗口
+# ======================================================
+class FaceRandomApp(QWidget):
+    def __init__(self):
+        super().__init__()
+
+        # 先显示加载页面
+        self.loading_screen = LoadingScreen()
+        self.loading_screen.show()
+
+        # 强制立即处理GUI事件，确保加载页面能立即显示
+        QApplication.processEvents()
+
+        # 延迟初始化主界面
+        QTimer.singleShot(100, self.initialize_app)
+
+    def initialize_app(self):
+        """初始化应用程序"""
+        # 状态
+        self.state = "normal"
+        self.selected_face_index = -1
+        self.static_frame = None
+        self.faces_snapshot = []
+        self.faces = []
+        self.detection_confidence = 0.6
+        self.is_static_mode = False
+
+        # 初始化摄像头
+        self.cap = cv2.VideoCapture(0)
+        if self.cap.isOpened():
+            self.cap.set(cv2.CAP_PROP_FRAME_WIDTH, 1280)
+            self.cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 720)
+            # 提高图像质量设置
+            self.cap.set(cv2.CAP_PROP_FPS, 30)
+
+        # UI
+        self.setup_ui()
+
+        # 启动模型加载
+        self.start_model_loading()
+
+    def start_model_loading(self):
+        """启动模型加载"""
+        model_path = self.get_yunet_model_path()
+        if model_path:
+            self.loader = ModelLoader(model_path)
+            self.loader.loaded.connect(self.on_model_loaded)
+            self.loader.progress.connect(self.on_loading_progress)
+            self.loader.start()
+        else:
+            # 如果没有模型，跳过模型加载
+            self.loading_screen.close()
+            self.show()
+            self.timer = QTimer()
+            self.timer.timeout.connect(self.update_frame)
+            self.timer.start(30)
+
+    def get_yunet_model_path(self):
+        """获取模型路径"""
+        base_dir = os.path.dirname(os.path.abspath(__file__))
+        model_path = os.path.join(base_dir, "model", "face_detection_yunet_2023mar.onnx")
+        return model_path if os.path.exists(model_path) else None
+
+    def on_loading_progress(self, message):
+        """加载进度更新"""
+        self.loading_screen.loading_label.setText(message)
+
+    def on_model_loaded(self, detector, error):
+        """模型加载完成回调"""
+        if detector and not error:
+            self.detector = detector
+            # 更新置信度
+            self.detector.setScoreThreshold(self.detection_confidence)
+        else:
+            print(f"模型加载失败: {error}")
+
+        # 关闭加载界面并显示主窗口
+        self.loading_screen.close()
+        self.show()
+
+        # 启动视频更新定时器
+        self.timer = QTimer()
+        self.timer.timeout.connect(self.update_frame)
+        self.timer.start(30)
+
+    # ======================================================
+    # UI
+    # ======================================================
+    def setup_ui(self):
+        self.setWindowTitle("Face Random Selector")
+        self.resize(1280, 720)
+
+        self.video_label = QLabel(self)
+        self.video_label.setGeometry(0, 0, self.width(), self.height())
+        self.video_label.setStyleSheet("background: black;")
+
+        # 随机按钮
+        self.btn = QPushButton("随机", self)
+        self.btn.setFixedSize(140, 55)
+        self.btn.move(20, self.height() - 75)
+        self.btn.clicked.connect(self.on_random_clicked)
+        self.btn.setStyleSheet("""
+            QPushButton {
+                background-color: rgba(0, 0, 0, 180);
+                color: white;
+                font-size: 20px;
+                font-weight: bold;
+                border: none;
+                border-radius: 8px;
+            }
+            QPushButton:hover {
+                background-color: rgba(30, 30, 30, 200);
+            }
+            QPushButton:pressed {
+                background-color: rgba(50, 50, 50, 220);
+            }
+        """)
+
+        # 置信度滑条
+        self.slider = QSlider(Qt.Horizontal, self)
+        self.slider.setRange(30, 90)
+        self.slider.setValue(int(self.detection_confidence * 100))
+        self.slider.setFixedWidth(200)
+        self.slider.move(120, 20)
+        self.slider.valueChanged.connect(self.on_confidence_change)
+        self.slider.setStyleSheet("""
+            QSlider::groove:horizontal {
+                background: rgba(0, 0, 0, 120);
+                height: 4px;
+                border-radius: 2px;
+            }
+            QSlider::handle:horizontal {
+                background: white;
+                width: 14px;
+                height: 14px;
+                border-radius: 7px;
+                margin: -5px 0;
+            }
+        """)
+
+        # 置信度标签
+        self.conf_label = QLabel("置信度", self)
+        self.conf_label.move(20, 20)
+        self.conf_label.setStyleSheet("""
+            color: white; 
+            font-size: 16px; 
+            font-weight: bold;
+            background: transparent;
+        """)
+
+        # 静止按钮 (圆形半透明)
+        self.static_btn = QPushButton("静", self)
+        self.static_btn.setFixedSize(55, 55)
+        self.static_btn.move(self.btn.x() + self.btn.width() + 20, self.height() - 75)
+        self.static_btn.clicked.connect(self.on_static_clicked)
+        self.static_btn.setStyleSheet("""
+            QPushButton {
+                background-color: rgba(0, 0, 0, 140);
+                color: white;
+                font-size: 18px;
+                font-weight: bold;
+                border: none;
+                border-radius: 27px;
+            }
+            QPushButton:hover {
+                background-color: rgba(30, 30, 30, 180);
+            }
+            QPushButton:pressed {
+                background-color: rgba(50, 50, 50, 200);
+            }
+        """)
+
+    def resizeEvent(self, event):
+        self.video_label.setGeometry(0, 0, self.width(), self.height())
+        self.btn.move(20, self.height() - 75)
+        if hasattr(self, 'static_btn'):
+            self.static_btn.move(self.btn.x() + self.btn.width() + 20, self.height() - 75)
+        super().resizeEvent(event)
+
+    def on_confidence_change(self, value):
+        self.detection_confidence = value / 100.0
+        if hasattr(self, 'detector'):
+            self.detector.setScoreThreshold(self.detection_confidence)
+
+    def on_random_clicked(self):
+        if self.state == "normal":
+            self.state = "random"
+            self.btn.setText("重置")
+
+            if len(self.faces) > 0:
+                self.selected_face_index = random.randint(0, len(self.faces) - 1)
+
+                # 捕获静态帧
+                if self.cap and self.cap.isOpened():
+                    ret, img = self.cap.read()
+                    if ret:
+                        img = cv2.flip(img, 1)
+                        img = self.resize_cover(img, self.video_label.width(), self.video_label.height())
+                        self.static_frame = img.copy()
+                        self.faces_snapshot = self.faces.copy()
+        else:
+            self.state = "normal"
+            self.btn.setText("随机")
+            self.selected_face_index = -1
+            self.static_frame = None
+
+    def on_static_clicked(self):
+        """ 静止模式 """
+        if not getattr(self, 'is_static_mode', False):
+            # 静止模式：保留已加载的模型，不释放摄像头，只停止读取/检测
+            self.is_static_mode = True
+            try:
+                self.static_btn.setText("恢复")
+            except Exception:
+                pass
+        else:
+            # 退出静止模式，恢复摄像头和模型
+            self.is_static_mode = False
+            try:
+                self.static_btn.setText("静")
+            except Exception:
+                pass
+
+            # 重新打开摄像头（仅在当前没有打开时）
+            if not hasattr(self, 'cap') or self.cap is None or not self.cap.isOpened():
+                self.cap = cv2.VideoCapture(0)
+                if self.cap.isOpened():
+                    self.cap.set(cv2.CAP_PROP_FRAME_WIDTH, 1280)
+                    self.cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 720)
+                    self.cap.set(cv2.CAP_PROP_FPS, 30)
+
+            # 保留 detector（如果之前加载过则直接可用），无需重新加载。
+            # 重新打开摄像头，检测器若存在则继续使用；否则重新加载模型。
+            if not hasattr(self, 'detector') or self.detector is None:
+                # 仅在没有 detector 时重新加载
+                self.start_model_loading()
+
+    def resize_cover(self, img, target_w, target_h):
+        h, w = img.shape[:2]
+        scale = max(target_w / w, target_h / h)
+        new_w = int(w * scale)
+        new_h = int(h * scale)
+        resized = cv2.resize(img, (new_w, new_h))
+        x_start = (new_w - target_w) // 2
+        y_start = (new_h - target_h) // 2
+        return resized[y_start:y_start + target_h, x_start:x_start + target_w]
+
+    def draw_face_with_confidence(self, img, face, color, thickness=2):
+        """绘制人脸框和置信度"""
+        x, y, w, h = map(int, face[:4])
+        # 仅绘制人脸矩形框，不显示置信度文本
+        cv2.rectangle(img, (x, y), (x + w, y + h), color, thickness)
+
+    def update_frame(self):
+        # 如果处于静止模式，不使用摄像头和模型，摄像头区域黑屏以节省资源
+        if getattr(self, 'is_static_mode', False):
+            h = self.video_label.height()
+            w = self.video_label.width()
+            black = np.zeros((h, w, 3), dtype=np.uint8)
+            self.display(black)
+            return
+
+        # 非静止模式，需要摄像头
+        if not self.cap or not self.cap.isOpened():
+            return
+
+        ret, img = self.cap.read()
+        if not ret:
+            return
+
+        # 镜像翻转
+        img = cv2.flip(img, 1)
+
+        # resize_cover方法，保持视野大小
+        img = self.resize_cover(img, self.video_label.width(), self.video_label.height())
+
+        if self.state == "normal":
+            if hasattr(self, 'detector') and self.detector is not None:
+                # 设置检测器输入大小
+                self.detector.setInputSize((img.shape[1], img.shape[0]))
+
+                # 检测人脸
+                _, detected = self.detector.detect(img)
+                self.faces = detected if detected is not None else []
+
+                # 绘制检测结果（正常模式绘制全部绿色框）
+                for face in self.faces:
+                    self.draw_face_with_confidence(img, face, (0, 255, 0), 2)
+            else:
+                # 如果没有模型，只显示原始图像
+                pass
+        else:  # random 模式
+            if self.static_frame is not None:
+                img = self.static_frame.copy()
+                # 仅绘制被选中的红色框，其他不显示
+                if self.selected_face_index != -1 and len(self.faces_snapshot) > self.selected_face_index:
+                    face = self.faces_snapshot[self.selected_face_index]
+                    self.draw_face_with_confidence(img, face, (0, 0, 255), 3)
+
+        self.display(img)
+
+    def display(self, img):
+        # 图像显示
+        rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+        h, w, c = rgb.shape
+        qimg = QImage(rgb.data, w, h, c * w, QImage.Format_RGB888)
+        self.video_label.setPixmap(QPixmap.fromImage(qimg))
+
+    def closeEvent(self, event):
+        if self.cap and self.cap.isOpened():
+            self.cap.release()
+        if hasattr(self, 'loader') and self.loader.isRunning():
+            self.loader.quit()
+            self.loader.wait()
+        event.accept()
+
+
+# ======================================================
+def main():
+    app = QApplication(sys.argv)
+    window = FaceRandomApp()
+    # 注意：这里不再调用 window.show()，因为 FaceRandomApp 内部会处理显示逻辑
+    sys.exit(app.exec())
+
+
+if __name__ == "__main__":
+    main()

3-control.py

@@ -0,0 +1,551 @@
+import sys
+import random
+import cv2
+import numpy as np
+from cvzone.FaceDetectionModule import FaceDetector
+from PySide6.QtCore import QTimer, Qt
+from PySide6.QtGui import QImage, QPixmap
+from PySide6.QtWidgets import (QApplication, QWidget, QLabel, QPushButton, 
+                               QVBoxLayout, QProgressBar, QHBoxLayout, 
+                               QSlider, QGroupBox, QDoubleSpinBox)
+
+
+class LoadingScreen(QWidget):
+    def __init__(self):
+        super().__init__()
+        self.setWindowTitle("加载中...")
+        self.setFixedSize(300, 150)
+        self.setWindowFlags(Qt.FramelessWindowHint | Qt.WindowStaysOnTopHint)
+        self.setStyleSheet("background-color: #1E90FF;")  # 蓝色背景
+        
+        # 创建布局
+        layout = QVBoxLayout()
+        layout.setAlignment(Qt.AlignCenter)
+        layout.setSpacing(15)
+        
+        # 加载提示文字
+        self.loading_label = QLabel("人脸模型加载中")
+        self.loading_label.setAlignment(Qt.AlignCenter)
+        self.loading_label.setStyleSheet("color: white; font-size: 18px; font-weight: bold;")
+        layout.addWidget(self.loading_label)
+        
+        # 进度条 - 设置为不确定模式，显示加载动画
+        self.progress_bar = QProgressBar()
+        self.progress_bar.setRange(0, 0)  # 设置为0,0表示不确定模式
+        self.progress_bar.setFixedHeight(10)
+        self.progress_bar.setStyleSheet("""
+            QProgressBar {
+                border: 1px solid rgba(255, 255, 255, 100);
+                border-radius: 5px;
+                background-color: rgba(255, 255, 255, 50);
+            }
+            QProgressBar::chunk {
+                background-color: white;
+                border-radius: 4px;
+            }
+        """)
+        layout.addWidget(self.progress_bar)
+        
+        self.setLayout(layout)
+
+
+class FaceRandomApp(QWidget):
+    def __init__(self):
+        super().__init__()
+        
+        # 先显示加载页面
+        self.loading_screen = LoadingScreen()
+        self.loading_screen.show()
+        
+        # 强制立即处理GUI事件，确保加载页面能立即显示
+        QApplication.processEvents()
+        
+        # 延迟初始化主界面，让加载页面先显示
+        QTimer.singleShot(100, self.initialize_app)
+
+    def initialize_app(self):
+        # 设置窗口标题
+        self.setWindowTitle("Face Random Selector")
+        
+        # 状态：normal → random
+        self.state = "normal"
+        self.selected_face_index = -1
+        self.static_frame = None  # 保存随机状态下的静态画面
+        self.all_faces_snapshot = []  # 保存所有人脸信息快照
+        
+        # 检测参数
+        self.detection_confidence = 0.15  # 降低置信度阈值以提高检测率
+        self.model_selection = 1  # 长距离模型
+        self.control_panel_visible = False  # 控制面板显示状态
+        self.multi_scale_enabled = True  # 启用多尺度检测
+
+        # ---------------- 摄像头 ----------------
+        self.cap = cv2.VideoCapture(0)
+        
+        # 设置更高分辨率以捕捉更多细节
+        self.cap.set(3, 1920)  # 宽度
+        self.cap.set(4, 1080)  # 高度
+        
+        # 设置窗口初始大小
+        self.resize(1280, 720)
+        
+        # 更新加载页面文字，提示正在进行人脸模型初始化
+        self.loading_screen.loading_label.setText("正在初始化人脸检测模型...")
+        QApplication.processEvents()
+        
+        # 使用优化的参数
+        try:
+            self.detector = FaceDetector(
+                minDetectionCon=self.detection_confidence, 
+                modelSelection=self.model_selection
+            )
+            self.loading_screen.loading_label.setText("人脸模型加载完成!")
+        except Exception as e:
+            print(f"初始化人脸检测器时出错: {e}")
+            # 如果初始化失败，使用一个空的检测器
+            self.detector = None
+            self.loading_screen.loading_label.setText("人脸模型加载失败，使用基础模式")
+
+        # ---------------- 创建界面 ----------------
+        self.setup_ui()
+
+        self.faces = []
+        
+        # 模拟加载完成
+        QTimer.singleShot(1500, self.finish_loading)
+
+    def finish_loading(self):
+        # 关闭加载页面
+        self.loading_screen.close()
+        # 显示主窗口
+        self.show()
+        
+        # 启动定时器更新视频帧
+        self.timer = QTimer()
+        self.timer.timeout.connect(self.update_frame)
+        self.timer.start(30)
+
+    def setup_ui(self):
+        # 视频标签 - 填充整个窗口
+        self.video_label = QLabel(self)
+        self.video_label.setStyleSheet("background:#000;")
+        self.video_label.setGeometry(0, 0, self.width(), self.height())
+
+        # 随机按钮 - 叠加在视频上
+        self.btn = QPushButton("随机", self)
+        self.btn.setFixedSize(140, 55)
+        self.btn.setStyleSheet("""
+            QPushButton {
+                background-color: rgba(0, 0, 0, 120);
+                color: white;
+                font-size: 20px;
+                padding: 10px 20px;
+                border-radius: 8px;
+            }
+            QPushButton:hover {
+                background-color: rgba(30, 30, 30, 180);
+            }
+        """)
+        self.btn.clicked.connect(self.button_clicked)
+        
+        # 控制按钮 - 新增
+        self.control_btn = QPushButton("控制", self)
+        self.control_btn.setFixedSize(80, 40)
+        self.control_btn.setStyleSheet("""
+            QPushButton {
+                background-color: rgba(0, 0, 0, 120);
+                color: white;
+                font-size: 16px;
+                padding: 5px 10px;
+                border-radius: 6px;
+            }
+            QPushButton:hover {
+                background-color: rgba(30, 30, 30, 180);
+            }
+        """)
+        self.control_btn.clicked.connect(self.toggle_control_panel)
+        
+        # 控制面板 - 新增
+        self.control_panel = QWidget(self)
+        self.control_panel.setFixedSize(300, 180)  # 减小高度
+        self.control_panel.setStyleSheet("""
+            QWidget {
+                background-color: rgba(0, 0, 0, 180);
+                border-radius: 10px;
+                border: 1px solid rgba(255, 255, 255, 100);
+            }
+        """)
+        self.control_panel.hide()  # 初始隐藏
+        
+        # 控制面板布局
+        control_layout = QVBoxLayout(self.control_panel)
+        control_layout.setContentsMargins(15, 15, 15, 15)
+        control_layout.setSpacing(10)
+        
+        # 置信度控制
+        confidence_layout = QHBoxLayout()
+        confidence_label = QLabel("置信度:")
+        confidence_label.setStyleSheet("color: white; font-size: 14px;")
+        self.confidence_slider = QSlider(Qt.Horizontal)
+        self.confidence_slider.setRange(5, 50)  # 调整范围以适应教室环境
+        self.confidence_slider.setValue(15)  # 默认0.15
+        self.confidence_slider.valueChanged.connect(self.on_confidence_changed)
+        self.confidence_slider.setStyleSheet("""
+            QSlider::groove:horizontal {
+                background: rgba(255, 255, 255, 100);
+                height: 6px;
+                border-radius: 3px;
+            }
+            QSlider::handle:horizontal {
+                background: white;
+                width: 16px;
+                height: 16px;
+                border-radius: 8px;
+                margin: -5px 0;
+            }
+        """)
+        
+        self.confidence_value = QLabel("0.15")
+        self.confidence_value.setStyleSheet("color: white; font-size: 14px; min-width: 40px;")
+        
+        confidence_layout.addWidget(confidence_label)
+        confidence_layout.addWidget(self.confidence_slider)
+        confidence_layout.addWidget(self.confidence_value)
+        control_layout.addLayout(confidence_layout)
+        
+        # 多尺度检测选项
+        multiscale_layout = QHBoxLayout()
+        multiscale_label = QLabel("多尺度检测:")
+        multiscale_label.setStyleSheet("color: white; font-size: 14px;")
+        
+        self.multiscale_check = QPushButton("启用")
+        self.multiscale_check.setCheckable(True)
+        self.multiscale_check.setChecked(True)
+        self.multiscale_check.setFixedHeight(30)
+        self.multiscale_check.setStyleSheet("""
+            QPushButton {
+                background-color: rgba(255, 255, 255, 50);
+                color: white;
+                border: 1px solid rgba(255, 255, 255, 100);
+                border-radius: 4px;
+                font-size: 12px;
+            }
+            QPushButton:checked {
+                background-color: rgba(30, 144, 255, 200);
+                border: 1px solid rgba(255, 255, 255, 200);
+            }
+            QPushButton:hover {
+                background-color: rgba(255, 255, 255, 80);
+            }
+        """)
+        self.multiscale_check.clicked.connect(self.on_multiscale_changed)
+        
+        multiscale_layout.addWidget(multiscale_label)
+        multiscale_layout.addWidget(self.multiscale_check)
+        multiscale_layout.addStretch()
+        control_layout.addLayout(multiscale_layout)
+        
+        # 模型选择
+        model_layout = QHBoxLayout()
+        model_label = QLabel("检测模型:")
+        model_label.setStyleSheet("color: white; font-size: 14px;")
+        
+        self.model_short_btn = QPushButton("短距离")
+        self.model_long_btn = QPushButton("长距离")
+        
+        for btn in [self.model_short_btn, self.model_long_btn]:
+            btn.setCheckable(True)
+            btn.setFixedHeight(30)
+            btn.setStyleSheet("""
+                QPushButton {
+                    background-color: rgba(255, 255, 255, 50);
+                    color: white;
+                    border: 1px solid rgba(255, 255, 255, 100);
+                    border-radius: 4px;
+                    font-size: 12px;
+                }
+                QPushButton:checked {
+                    background-color: rgba(30, 144, 255, 200);
+                    border: 1px solid rgba(255, 255, 255, 200);
+                }
+                QPushButton:hover {
+                    background-color: rgba(255, 255, 255, 80);
+                }
+            """)
+        
+        self.model_short_btn.clicked.connect(lambda: self.on_model_changed(0))
+        self.model_long_btn.clicked.connect(lambda: self.on_model_changed(1))
+        
+        # 默认选择长距离模型
+        self.model_long_btn.setChecked(True)
+        
+        model_layout.addWidget(model_label)
+        model_layout.addWidget(self.model_short_btn)
+        model_layout.addWidget(self.model_long_btn)
+        model_layout.addStretch()
+        control_layout.addLayout(model_layout)
+        
+        control_layout.addStretch()
+        
+        # 初始按钮位置
+        self.update_button_position()
+
+    def toggle_control_panel(self):
+        """切换控制面板显示状态"""
+        self.control_panel_visible = not self.control_panel_visible
+        if self.control_panel_visible:
+            self.control_panel.show()
+        else:
+            self.control_panel.hide()
+
+    def on_confidence_changed(self, value):
+        """置信度滑块值改变"""
+        confidence = value / 100.0
+        self.confidence_value.setText(f"{confidence:.2f}")
+        self.detection_confidence = confidence
+        if self.detector:
+            self.detector.minDetectionCon = confidence
+
+    def on_multiscale_changed(self):
+        """多尺度检测选项改变"""
+        self.multi_scale_enabled = self.multiscale_check.isChecked()
+
+    def on_model_changed(self, model_selection):
+        """模型选择改变"""
+        self.model_selection = model_selection
+        if model_selection == 0:
+            self.model_short_btn.setChecked(True)
+            self.model_long_btn.setChecked(False)
+        else:
+            self.model_short_btn.setChecked(False)
+            self.model_long_btn.setChecked(True)
+        
+        # 重新初始化检测器
+        try:
+            self.detector = FaceDetector(
+                minDetectionCon=self.detection_confidence,
+                modelSelection=model_selection
+            )
+        except Exception as e:
+            print(f"重新初始化检测器失败: {e}")
+
+    def multi_scale_detection(self, img):
+        """多尺度人脸检测，提高小尺寸人脸的检测率"""
+        if not self.multi_scale_enabled or self.detector is None:
+            return self.detector.findFaces(img, draw=False) if self.detector else (img, [])
+        
+        faces = []
+        scales = [1.0, 0.75, 0.5]  # 多尺度因子
+        
+        for scale in scales:
+            # 缩放图像
+            if scale != 1.0:
+                h, w = img.shape[:2]
+                new_w, new_h = int(w * scale), int(h * scale)
+                scaled_img = cv2.resize(img, (new_w, new_h))
+            else:
+                scaled_img = img.copy()
+            
+            # 在当前尺度下检测人脸
+            _, scaled_faces = self.detector.findFaces(scaled_img, draw=False)
+            
+            # 将检测到的人脸坐标转换回原始尺度
+            if scaled_faces:
+                for face in scaled_faces:
+                    bbox = face["bbox"]
+                    # 调整边界框坐标
+                    face["bbox"] = [
+                        int(bbox[0] / scale),
+                        int(bbox[1] / scale),
+                        int(bbox[2] / scale),
+                        int(bbox[3] / scale)
+                    ]
+                    # 只添加新检测到的人脸（避免重复）
+                    if not self.is_duplicate_face(face, faces):
+                        faces.append(face)
+        
+        return img, faces
+
+    def is_duplicate_face(self, new_face, existing_faces, threshold=0.5):
+        """检查是否重复检测到同一个人脸"""
+        if not existing_faces:
+            return False
+            
+        new_x, new_y, new_w, new_h = new_face["bbox"]
+        new_center = (new_x + new_w/2, new_y + new_h/2)
+        
+        for face in existing_faces:
+            x, y, w, h = face["bbox"]
+            center = (x + w/2, y + h/2)
+            
+            # 计算两个边界框中心点的距离
+            distance = np.sqrt((new_center[0] - center[0])**2 + (new_center[1] - center[1])**2)
+            
+            # 如果距离小于阈值，认为是同一个人脸
+            if distance < max(new_w, new_h) * threshold:
+                return True
+                
+        return False
+
+    def resizeEvent(self, event):
+        """窗口大小改变时自动调整视频和按钮位置"""
+        self.video_label.setGeometry(0, 0, self.width(), self.height())
+        self.update_button_position()
+        super().resizeEvent(event)
+
+    def update_button_position(self):
+        """更新按钮位置"""
+        btn_w = 140
+        btn_h = 55
+        margin = 20
+        
+        # 随机按钮位置（左下角）
+        self.btn.setGeometry(
+            margin,
+            self.height() - btn_h - margin,
+            btn_w,
+            btn_h
+        )
+        
+        # 控制按钮位置（左上角）
+        control_btn_w = 80
+        control_btn_h = 40
+        self.control_btn.setGeometry(
+            margin,
+            margin,
+            control_btn_w,
+            control_btn_h
+        )
+        
+        # 控制面板位置（控制按钮下方）
+        panel_width = 300
+        panel_height = 180
+        self.control_panel.setGeometry(
+            margin,
+            margin + control_btn_h + 10,
+            panel_width,
+            panel_height
+        )
+
+    # ---------------------------------------------------------
+    # 逻辑按钮：随机 ↔ 重置
+    # ---------------------------------------------------------
+    def button_clicked(self):
+        if self.state == "normal":
+            # 切换到随机状态
+            self.state = "random"
+            self.btn.setText("重置")
+
+            # 随机选择一个人脸
+            if len(self.faces) > 0:
+                self.selected_face_index = random.randint(0, len(self.faces) - 1)
+
+                # 保存当前帧作为静态画面
+                ret, img = self.cap.read()
+                if ret:
+                    img = cv2.flip(img, 1)
+                    # 调整图像大小以适应窗口
+                    img = cv2.resize(img, (self.video_label.width(), self.video_label.height()))
+                    self.static_frame = img.copy()
+                    self.all_faces_snapshot = self.faces.copy()
+        else:  # self.state == "random"
+            # 切换回初始状态
+            self.state = "normal"
+            self.selected_face_index = -1
+            self.static_frame = None
+            self.all_faces_snapshot = []
+            self.btn.setText("随机")
+
+    # ---------------------------------------------------------
+    # 刷视频帧
+    # ---------------------------------------------------------
+    def update_frame(self):
+        # ============================
+        # 状态：normal（检测所有人脸并显示绿框）
+        # ============================
+        if self.state == "normal":
+            ret, img = self.cap.read()
+            if not ret:
+                return
+
+            img = cv2.flip(img, 1)
+            
+            # 调整图像大小以适应窗口
+            img = cv2.resize(img, (self.video_label.width(), self.video_label.height()))
+
+            # 检测人脸 - 使用多尺度检测
+            if self.detector is not None:
+                if self.multi_scale_enabled:
+                    img, self.faces = self.multi_scale_detection(img)
+                else:
+                    img, self.faces = self.detector.findFaces(img, draw=False)
+                self.faces = self.faces if self.faces else []
+            else:
+                self.faces = []
+
+            # 绘制所有人脸为绿色
+            for face in self.faces:
+                x, y, w, h = face["bbox"]
+                score = face["score"][0]
+                # 根据置信度调整边框粗细
+                thickness = max(1, int(3 * score))
+                cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), thickness)
+                cv2.putText(img, f"{score:.2f}", (x, y - 10),
+                            cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 255, 0), 2)
+
+            # 显示图像
+            self.display_image(img)
+
+        # ============================
+        # 状态：random（显示静态画面，选中的人脸为红色，其他为绿色）
+        # ============================
+        elif self.state == "random" and self.static_frame is not None:
+            img = self.static_frame.copy()
+
+            # 绘制所有人脸，选中的为红色，其他为绿色
+            for i, face in enumerate(self.all_faces_snapshot):
+                x, y, w, h = face["bbox"]
+                score = face["score"][0]
+
+                if i == self.selected_face_index:
+                    color = (0, 0, 255)  # 红色
+                    thickness = 4
+                else:
+                    color = (0, 255, 0)  # 绿色
+                    thickness = 2
+
+                cv2.rectangle(img, (x, y), (x + w, y + h), color, thickness)
+                cv2.putText(img, f"{score:.2f}", (x, y - 10),
+                            cv2.FONT_HERSHEY_SIMPLEX, 0.6, color, 2)
+
+            # 显示图像
+            self.display_image(img)
+
+    # ---------------------------------------------------------
+    # 显示图像到 QLabel
+    # ---------------------------------------------------------
+    def display_image(self, img):
+        rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+        h, w, ch = rgb.shape
+        bytes_per_line = ch * w
+        qimg = QImage(rgb.data, w, h, bytes_per_line, QImage.Format.Format_RGB888)
+        self.video_label.setPixmap(QPixmap.fromImage(qimg))
+
+    # ---------------------------------------------------------
+    def closeEvent(self, event):
+        if self.cap.isOpened():
+            self.cap.release()
+        event.accept()
+
+
+def main():
+    app = QApplication(sys.argv)
+    
+    # 直接创建主应用窗口，它内部会处理加载页面
+    window = FaceRandomApp()
+    
+    sys.exit(app.exec())
+
+
+if __name__ == "__main__":
+    main()

3-test.py

@@ -0,0 +1,310 @@
+import sys
+import random
+import cv2
+from cvzone.FaceDetectionModule import FaceDetector
+from PySide6.QtCore import QTimer, Qt
+from PySide6.QtGui import QImage, QPixmap
+from PySide6.QtWidgets import QApplication, QWidget, QLabel, QPushButton, QVBoxLayout, QProgressBar
+
+
+class LoadingScreen(QWidget):
+    def __init__(self):
+        super().__init__()
+        self.setWindowTitle("加载中...")
+        self.setFixedSize(400, 250)  # 增大窗口大小以容纳错误信息
+        self.setWindowFlags(Qt.WindowStaysOnTopHint)  # 保留置顶但移除无边框，方便关闭
+        self.setStyleSheet("background-color: #1E90FF;")  # 蓝色背景
+        
+        # 创建布局
+        layout = QVBoxLayout()
+        layout.setAlignment(Qt.AlignCenter)
+        layout.setSpacing(15)
+        
+        # 加载提示文字
+        self.loading_label = QLabel("人脸模型加载中")
+        self.loading_label.setAlignment(Qt.AlignCenter)
+        self.loading_label.setStyleSheet("color: white; font-size: 18px; font-weight: bold;")
+        layout.addWidget(self.loading_label)
+        
+        # 错误信息标签
+        self.error_label = QLabel("")
+        self.error_label.setAlignment(Qt.AlignCenter)
+        self.error_label.setStyleSheet("color: #FFD700; font-size: 12px; font-weight: normal;")
+        self.error_label.setWordWrap(True)
+        self.error_label.setHidden(True)  # 初始隐藏
+        layout.addWidget(self.error_label)
+        
+        # 进度条 - 设置为不确定模式，显示加载动画
+        self.progress_bar = QProgressBar()
+        self.progress_bar.setRange(0, 0)  # 设置为0,0表示不确定模式
+        self.progress_bar.setFixedHeight(10)
+        layout.addWidget(self.progress_bar)
+        
+        # 关闭按钮 - 初始隐藏
+        self.close_button = QPushButton("关闭")
+        self.close_button.setFixedSize(100, 35)
+        self.close_button.setStyleSheet("""
+            QPushButton {
+                background-color: #FF6347;
+                color: white;
+                font-size: 14px;
+                border-radius: 5px;
+            }
+            QPushButton:hover {
+                background-color: #FF4500;
+            }
+        """)
+        self.close_button.clicked.connect(self.close)
+        self.close_button.setHidden(True)  # 初始隐藏
+        layout.addWidget(self.close_button)
+        
+        self.setLayout(layout)
+        
+    def show_error(self, error_message):
+        """显示错误信息并显示关闭按钮，隐藏进度条"""
+        self.loading_label.setText("人脸模型加载失败")
+        self.error_label.setText(f"错误详情: {error_message}")
+        self.error_label.setHidden(False)
+        self.progress_bar.setHidden(True)
+        self.close_button.setHidden(False)
+        self.setWindowTitle("加载失败")
+        # 调整窗口大小以适应错误信息
+        self.adjustSize()
+        QApplication.processEvents()
+
+
+class FaceRandomApp(QWidget):
+    def __init__(self):
+        super().__init__()
+        
+        # 先显示加载页面
+        self.loading_screen = LoadingScreen()
+        self.loading_screen.show()
+        
+        # 强制立即处理GUI事件，确保加载页面能立即显示
+        QApplication.processEvents()
+        
+        # 延迟初始化主界面，让加载页面先显示
+        QTimer.singleShot(100, self.initialize_app)
+
+    def initialize_app(self):
+        # 状态：normal → random
+        self.state = "normal"
+        self.selected_face_index = -1
+        self.static_frame = None  # 保存随机状态下的静态画面
+        self.all_faces_snapshot = []  # 保存所有人脸信息快照
+
+        # 更新加载页面文字，提示正在进行人脸模型初始化
+        self.loading_screen.loading_label.setText("正在初始化人脸检测模型...")
+        QApplication.processEvents()
+        
+        # 使用长距离模型和更低的人脸检测阈值以提高检测率
+        # 这里会加载模型，可能需要一些时间
+        try:
+            self.detector = FaceDetector(minDetectionCon=0.25, modelSelection=1)
+            self.loading_screen.loading_label.setText("人脸模型加载完成!")
+            
+            # 只有在检测器初始化成功后才继续初始化
+            # 设置窗口标题
+            self.setWindowTitle("Face Random Selector")
+            
+            # ---------------- 摄像头 ----------------
+            self.cap = cv2.VideoCapture(0)
+            
+            # 设置摄像头分辨率
+            self.cap.set(3, 1280)
+            self.cap.set(4, 720)
+            
+            # 设置窗口初始大小
+            self.resize(1280, 720)
+
+            # ---------------- 创建界面 ----------------
+            self.setup_ui()
+
+            self.faces = []
+            
+            # 模拟加载完成
+            QTimer.singleShot(1500, self.finish_loading)
+            
+        except Exception as e:
+            # 捕获并显示详细的错误信息（仅显示真实的错误内容）
+            error_type = type(e).__name__
+            error_message = str(e)
+            # 只显示真实的错误类型和错误消息
+            detailed_error = f"{error_type}: {error_message}"
+            
+            print(f"初始化人脸检测器时出错: {detailed_error}")
+            # 显示错误信息并停止继续初始化
+            self.loading_screen.show_error(detailed_error)
+            # 不再继续初始化主界面
+
+    def finish_loading(self):
+        # 关闭加载页面
+        self.loading_screen.close()
+        # 显示主窗口
+        self.show()
+        
+        # 启动定时器更新视频帧
+        self.timer = QTimer()
+        self.timer.timeout.connect(self.update_frame)
+        self.timer.start(30)
+
+    def setup_ui(self):
+        # 视频标签 - 填充整个窗口
+        self.video_label = QLabel(self)
+        self.video_label.setStyleSheet("background:#000;")
+        self.video_label.setGeometry(0, 0, self.width(), self.height())
+
+        # 按钮 - 叠加在视频上
+        self.btn = QPushButton("随机", self)
+        self.btn.setFixedSize(140, 55)
+        self.btn.setStyleSheet("""
+            QPushButton {
+                background-color: rgba(0, 0, 0, 120);
+                color: white;
+                font-size: 20px;
+                padding: 10px 20px;
+                border-radius: 8px;
+            }
+            QPushButton:hover {
+                background-color: rgba(30, 30, 30, 180);
+            }
+        """)
+        self.btn.clicked.connect(self.button_clicked)
+        
+        # 初始按钮位置
+        self.update_button_position()
+
+    def resizeEvent(self, event):
+        """窗口大小改变时自动调整视频和按钮位置"""
+        self.video_label.setGeometry(0, 0, self.width(), self.height())
+        self.update_button_position()
+        super().resizeEvent(event)
+
+    def update_button_position(self):
+        """更新按钮位置"""
+        btn_w = 140
+        btn_h = 55
+        margin = 20
+        self.btn.setGeometry(
+            margin,
+            self.height() - btn_h - margin,
+            btn_w,
+            btn_h
+        )
+
+    # ---------------------------------------------------------
+    # 逻辑按钮：随机 ↔ 重置
+    # ---------------------------------------------------------
+    def button_clicked(self):
+        if self.state == "normal":
+            # 切换到随机状态
+            self.state = "random"
+            self.btn.setText("重置")
+
+            # 随机选择一个人脸
+            if len(self.faces) > 0:
+                self.selected_face_index = random.randint(0, len(self.faces) - 1)
+
+                # 保存当前帧作为静态画面
+                ret, img = self.cap.read()
+                if ret:
+                    img = cv2.flip(img, 1)
+                    # 调整图像大小以适应窗口
+                    img = cv2.resize(img, (self.video_label.width(), self.video_label.height()))
+                    self.static_frame = img.copy()
+                    self.all_faces_snapshot = self.faces.copy()
+        else:  # self.state == "random"
+            # 切换回初始状态
+            self.state = "normal"
+            self.selected_face_index = -1
+            self.static_frame = None
+            self.all_faces_snapshot = []
+            self.btn.setText("随机")
+
+    # ---------------------------------------------------------
+    # 刷视频帧
+    # ---------------------------------------------------------
+    def update_frame(self):
+        # ============================
+        # 状态：normal（检测所有人脸并显示绿框）
+        # ============================
+        if self.state == "normal":
+            ret, img = self.cap.read()
+            if not ret:
+                return
+
+            img = cv2.flip(img, 1)
+            
+            # 调整图像大小以适应窗口
+            img = cv2.resize(img, (self.video_label.width(), self.video_label.height()))
+
+            # 检测人脸
+            if self.detector is not None:
+                img, faces = self.detector.findFaces(img, draw=False)
+                self.faces = faces if faces else []
+            else:
+                self.faces = []
+
+            # 绘制所有人脸为绿色
+            for face in self.faces:
+                x, y, w, h = face["bbox"]
+                score = face["score"][0]
+                cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 3)
+                cv2.putText(img, f"{score:.2f}", (x, y - 10),
+                            cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 255, 0), 2)
+
+            # 显示图像
+            self.display_image(img)
+
+        # ============================
+        # 状态：random（显示静态画面，选中的人脸为红色，其他为绿色）
+        # ============================
+        elif self.state == "random" and self.static_frame is not None:
+            img = self.static_frame.copy()
+
+            # 绘制所有人脸，选中的为红色，其他为绿色
+            for i, face in enumerate(self.all_faces_snapshot):
+                x, y, w, h = face["bbox"]
+                score = face["score"][0]
+
+                if i == self.selected_face_index:
+                    color = (0, 0, 255)  # 红色
+                else:
+                    color = (0, 255, 0)  # 绿色
+
+                cv2.rectangle(img, (x, y), (x + w, y + h), color, 3)
+                cv2.putText(img, f"{score:.2f}", (x, y - 10),
+                            cv2.FONT_HERSHEY_SIMPLEX, 0.6, color, 2)
+
+            # 显示图像
+            self.display_image(img)
+
+    # ---------------------------------------------------------
+    # 显示图像到 QLabel
+    # ---------------------------------------------------------
+    def display_image(self, img):
+        rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+        h, w, ch = rgb.shape
+        bytes_per_line = ch * w
+        qimg = QImage(rgb.data, w, h, bytes_per_line, QImage.Format.Format_RGB888)
+        self.video_label.setPixmap(QPixmap.fromImage(qimg))
+
+    # ---------------------------------------------------------
+    def closeEvent(self, event):
+        if self.cap.isOpened():
+            self.cap.release()
+        event.accept()
+
+
+def main():
+    app = QApplication(sys.argv)
+    
+    # 直接创建主应用窗口，它内部会处理加载页面
+    window = FaceRandomApp()
+    
+    sys.exit(app.exec())
+
+
+if __name__ == "__main__":
+    main()

readme.md

@@ -0,0 +1,25 @@
+# Face Random
+
+## 1.软件说明
+FaceRandomSelector 是一款人脸随机选择工具。软件采用opencv的人脸检测算法，能够快速准确地识别摄像头中的人脸，并提供高效的随机选择功能，帮助教师轻松实现课堂互动。
+
+## 2.打包指令
+2.4版本之前：
+
+` nuitka --standalone --include-package=cv2 --enable-plugin=pyside6 --windows-console-mode=disable --windows-icon-from-ico=./text.ico --include-data-dir=F:\python310\lib\site-packages\cv2\data=cv2\data --output-dir=dist3c --remove-output 3-control.py `
+
+2.4版本之后：
+
+` nuitka --standalone --include-package=cv2 --enable-plugin=pyside6 --windows-console-mode=disable --windows-icon-from-ico=./text.ico --include-data-files=model/face_detection_yunet_2023mar.onnx=model/face_detection_yunet_2023mar.onnx --output-dir=dist34 --remove-output 3-5.py` 
+## 3.版本说明
+
+1. 1.py 2.py：非稳定版本
+2. 3-1.py：存在UI不美观 窗口大小 摄像头清晰度等问题
+3. 3-2.py：解决3-1.py的相关问题
+4. 3-3.py：添加加载进度条
+5. 3-test.py：由3-3.py改编 给出具体的人脸识别模型无法获取的相关报错
+6. 3-control.py：由3-3.py改编 用户可以修改相关参数
+7. 3-4.py：使用YuNet模型 加强对小人脸识别准确度
+8. 3-5.py：优化加载性能
+9. 3-6.py：优化加载性能 添加静止模式 删去置信度与选中绿框
+> 软件务必保存在纯英文路径中！