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Parcurcik
Asked:2022-07-20 19:32:17 +0000 UTC2022-07-20 19:32:17 +0000 UTC

如何通过神经网络从相机运行帧？

  • 772

如何通过神经网络（函数）从网络摄像头（函数camera_on，
以及）“传递”帧？control_timernetwork

class PredictNumber:
    face_cascade = cv2.CascadeClassifier('cascade/haarcascade_russian_plate_number.xml')

    def network(self, image_video):
        ret, frame = image_video.read()
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        plaques = face_cascade.detectMultiScale(gray, 1.3, 5)
        for i, (x, y, w, h) in enumerate(plaques):
            roi_color = frame[y:y + h, x:x + w]
            r = 400.0 / roi_color.shape[1]
            dim = (400, int(roi_color.shape[0] * r))
            resized = cv2.resize(roi_color, dim, interpolation=cv2.INTER_AREA)
            w_resized = resized.shape[0]
            h_resized = resized.shape[1]
            frame[100:100 + w_resized, 100:100 + h_resized] = resized
        return resized 

    def camera_on(self):
        ret, image = self.cap.read()
        image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
        height, width, channel = image.shape
        step = channel * width
        img = QImage(image.data, width, height, step, QImage.Format_RGB888)
        image_video = PredictNumber.network(self, img) 
# Таким образом не работает, 
происходит вылет программы.
        self.ui.Cam.setPixmap(QPixmap.fromImage(image_video))
        self.ui.Cam.setScaledContents(True)

    def control_timer(self):
        if not self.timer.isActive():
            self.cap = cv2.VideoCapture(0, cv2.CAP_DSHOW)
            self.timer.start(0)

UPD：重写并将相机移动到单独的类

为了避免将格式从 cv 转换为 QT image，我这样做了，添加了级联，但程序仍然崩溃：

class Worker1(QThread):
    ImageUpdate = pyqtSignal(QImage)
    face_cascade = cv2.CascadeClassifier('cascade/haarcascade_russian_plate_number.xml')
    def run(self):
        self.ThreadActive = True
        Capture = cv2.VideoCapture(0)
        while self.ThreadActive:
            ret, frame = Capture.read()
            if ret:
                image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
                flipped_image = cv2.flip(image, 1)
                with_cascade = faceCascade.detectMultiScale(flipped_image, 1.3, 7)
                for (x, y, w, h) in with_cascade:
                    roi_color = ret[y:y + h, x:x + w]
                    r = 300.0 / roi_color.shape[1]
                    dim = (400, int(roi_color.shape[0] * r))
                    resized = cv2.resize(roi_color, dim, interpolation=cv2.INTER_AREA)
                convert_to_qt_format = QImage(resized.data, resized.shape[1], fresized.shape[0], QImage.Format_RGB888)
                self.ImageUpdate.emit(convert_to_qt_format)

在这里，该类被初始化，并在按下按钮时启动。

        self.Worker1 = Worker1()
        self.Worker1.ImageUpdate.connect(self.image_update_slot)
        self.ui.Camera_btn.clicked.connect(self.Worker1.start)

这是一个用于更新相机的插槽。最后一行根据小部件制作相机大小

    def image_update_slot(self, Image):
        self.ui.Cam.setPixmap(QPixmap.fromImage(Image))
        self.ui.Cam.setScaledContents(True)
python

2 个回答

  1. 很明显，它不起作用 - 您传输 type 的数据QImage，但将其处理为VideoCapture(?)

    你需要做这样的事情：

    class PredictNumber:
    face_cascade = cv2.CascadeClassifier('cascade/haarcascade_russian_plate_number.xml')

    def network(self, image):
        # QImage в cv::Mat  
        frame = Mat(image.height(), image.width(), <тип данных из cv, который соответствует QImage.Format_RGB888>...)

        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        plaques = face_cascade.detectMultiScale(gray, 1.3, 5)
        for i, (x, y, w, h) in enumerate(plaques):
            roi_color = frame[y:y + h, x:x + w]
            r = 400.0 / roi_color.shape[1]
            dim = (400, int(roi_color.shape[0] * r))
            resized = cv2.resize(roi_color, dim, interpolation=cv2.INTER_AREA)
            w_resized = resized.shape[0]
            h_resized = resized.shape[1]
            frame[100:100 + w_resized, 100:100 + h_resized] = resized
        return resized

    如果它不起作用，请按照此处Mat(image....)的说明尝试

    • 1
  2. Best Answer

    尝试替换类Worker1：

    class Worker1(QThread):
    ImageUpdate = pyqtSignal(QImage)
    
    def __init__(self, *args, **kwargs): 
        super().__init__()
        self.ThreadActive = True
        self.cam = cv2.VideoCapture(0)    
    
    def run(self):
        while self.ThreadActive:
# --------> vvvvvvvvvvvv
            face_cascade = cv2.CascadeClassifier('cascade/haarcascade_russian_plate_number.xml')
            ret, frame = self.cam.read()                      # Capture.read()
            if ret:
                image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
                flipped_image = cv2.flip(image, 1)
# ---------------------------> ???????????                
#                with_cascade = faceCascade.detectMultiScale(flipped_image, 1.3, 7)
# ---------------------------> vvvvvvvvvvvv                 
                with_cascade = face_cascade.detectMultiScale(flipped_image, 1.3, 7)
                
                for (x, y, w, h) in with_cascade:
                    roi_color = ret[y:y + h, x:x + w]
                    r = 300.0 / roi_color.shape[1]
                    dim = (400, int(roi_color.shape[0] * r))
                    resized = cv2.resize(roi_color, dim, interpolation=cv2.INTER_AREA)
                convert_to_qt_format = QImage(resized.data, resized.shape[1], fresized.shape[0], QImage.Format_RGB888)
                self.ImageUpdate.emit(convert_to_qt_format)
    • 1

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