diff --git a/3-5.py b/3-5.py new file mode 100644 index 0000000..d5c1f69 --- /dev/null +++ b/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() \ No newline at end of file diff --git a/model/face_detection_yunet_2023mar.onnx b/model/face_detection_yunet_2023mar.onnx new file mode 100644 index 0000000..f9beb30 Binary files /dev/null and b/model/face_detection_yunet_2023mar.onnx differ diff --git a/readme.md b/readme.md index 1b2cc43..abc5e14 100644 --- a/readme.md +++ b/readme.md @@ -10,14 +10,15 @@ FaceRandomSelector 是一款人脸随机选择工具。软件采用opencv的人 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` +` 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 +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 > 软件务必保存在纯英文路径中！ \ No newline at end of file