pyside2 视频流 外加直方图

好的，如果您想在Pyside2应用程序中添加视频流并显示带刻度的直方图，您可以使用OpenCV库来捕获和处理视频流，并使用Matplotlib库来绘制直方图。

下面是一个简单的例子，可以帮助您开始：

import sys
import cv2
from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.figure import Figure
from PySide2.QtWidgets import QApplication, QWidget, QVBoxLayout, QLabel

class VideoPlayer(QWidget):
    def __init__(self, video_source=0):
        super().__init__()

        # Open the video source
        self.video = cv2.VideoCapture(video_source)

        # Create a figure for the histogram
        self.figure = Figure()
        self.canvas = FigureCanvas(self.figure)
        self.ax = self.figure.add_subplot(111)

        # Create a label for displaying the video frames
        self.image_label = QLabel(self)

        # Set up the layout
        layout = QVBoxLayout()
        layout.addWidget(self.image_label)
        layout.addWidget(self.canvas)
        self.setLayout(layout)

        # Start the timer to update the video frames and histogram
        self.timer = QTimer()
        self.timer.timeout.connect(self.update_frame)
        self.timer.start(30)

    def update_frame(self):
        # Read the next frame from the video stream
        ret, frame = self.video.read()

        if ret:
            # Convert the frame to grayscale and calculate the histogram
            gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
            hist, bins = np.histogram(gray.ravel(), 256, [0, 256])

            # Update the histogram plot
            self.ax.clear()
            self.ax.bar(bins[:-1], hist, width=1)
            self.ax.set_xlim([0, 256])
            self.ax.set_ylim([0, 5000])
            self.canvas.draw()

            # Convert the frame to QImage format and display it
            height, width, channels = frame.shape
            bytes_per_line = channels * width
            qimg = QImage(frame.data, width, height, bytes_per_line, QImage.Format_BGR888)
            pixmap = QPixmap.fromImage(qimg)
            self.image_label.setPixmap(pixmap)

if __name__ == '__main__':
    app = QApplication(sys.argv)
    player = VideoPlayer()
    player.show()
    sys.exit(app.exec_())

在这个例子中，我们创建了一个名为`VideoPlayer`的自定义QWidget类，它包含一个用于显示视频帧的QLabel和一个用于显示直方图的Matplotlib图表。我们使用OpenCV库来捕获和处理视频流，并使用Matplotlib库来计算和绘制直方图。我们还使用PySide2的QTimer类来定期更新视频帧和直方图。

请注意，这只是一个简单的例子，您需要根据您的应用程序需求进行修改。