diff --git a/3-4.py b/3-4.py new file mode 100644 index 0000000..4f605a3 --- /dev/null +++ b/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() \ No newline at end of file diff --git a/3-control.py b/3-control.py new file mode 100644 index 0000000..fb87a1a --- /dev/null +++ b/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() \ No newline at end of file diff --git a/icon.ico b/icon.ico deleted file mode 100644 index 30f1d8e..0000000 Binary files a/icon.ico and /dev/null differ diff --git a/readme.md b/readme.md index f23851d..1b2cc43 100644 --- a/readme.md +++ b/readme.md @@ -4,8 +4,13 @@ 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 -` nuitka --standalone --include-package=cv2 --enable-plugin=pyside6 --windows-console-mode=disable --windows-icon-from-ico=./icon.ico --include-data-dir=F:\python310\lib\site-packages\cv2\data=cv2\data --output-dir=dist32 --remove-output 3-2.py ` +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 --include-package=numpy --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 --include-data-files=model/face_detection_yunet_2023mar.onnx=model/face_detection_yunet_2023mar.onnx --output-dir=dist34 --remove-output 3-4.py` ## 3.版本说明 1. 1.py 2.py：非稳定版本 @@ -13,4 +18,6 @@ FaceRandomSelector 是一款人脸随机选择工具。软件采用opencv的人 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 > 软件务必保存在纯英文路径中！ \ No newline at end of file diff --git a/text.ico b/text.ico new file mode 100644 index 0000000..c0cc6e8 Binary files /dev/null and b/text.ico differ