PYQT6做UI，用YOLOV8检测RTSP视频流_pyqt6 yolov8

import sys
import cv2
import imutils
 
from PyQt6.QtCore import QThread, pyqtSignal
from PyQt6.QtGui import QImage, QPixmap
from PyQt6.QtWidgets import QApplication, QLabel, QMainWindow, QPushButton, QVBoxLayout, QWidget
from ultralytics import YOLO
 
model = YOLO("D:/YOLOHIDOZ/ultralytics/yolov8n.pt")  # 填入自己的模型地址
 
 
class VideoThread(QThread):
    model_detection_signal = pyqtSignal(QImage)
 
    def __init__(self, rtsp_url):
        super().__init__()
        self.rtsp_url = rtsp_url
        self.running = False
 
    def run(self):
        self.running = True
        cap = cv2.VideoCapture(self.rtsp_url)
 
        while self.running:
            # 从视频流中读取一帧
            ret, frame = cap.read()
            # 如果读取失败（例如，视频结束或连接断开），则跳出循环
            if not ret:
                break
 
            # 使用imutils的resize函数调整帧的大小到640像素宽
            frame = imutils.resize(frame, width=640)
 
            # 使用模型预测处理帧，并将结果存储在results中
            results = model.predict(source=frame)
 
            # 从results中获取第一个元素并绘制它
            annotated_frame = results[0].plot()
            # 获取帧的高度、宽度和通道数
            height, width, channel = annotated_frame.shape
            # 计算每行字节数，因为QImage使用每行像素数*每像素字节数的方式来表示图像数据
            bytes_per_line = 3 * width
 
            # 创建QImage对象，从annotated_frame中获取数据，并设置宽度、高度、每行字节数和图像格式
            # rgbSwapped()方法是因为OpenCV默认使用BGR格式，而QImage使用RGB格式
            qimage = QImage(annotated_frame.data, width, height, bytes_per_line,
                            QImage.Format.Format_RGB888).rgbSwapped()
 
            # 发出信号，将处理后的QImage对象发送出去，用于在GUI中显示
            self.model_detection_signal.emit(qimage)
 
        cap.release()
 
    def stop(self):
        self.running = False
        self.wait()
 
 
class MainWindow(QMainWindow):
    def __init__(self):
        super().__init__()
 
        self.setWindowTitle("测试")
        self.setGeometry(100, 100, 800, 600)
        layout = QVBoxLayout()
        self.label = QLabel("视频监控")
        self.button = QPushButton("打开")
 
        layout.addWidget(self.label)
        layout.addWidget(self.button)
        container = QWidget()
        container.setLayout(layout)
        self.setCentralWidget(container)
 
        self.thread = VideoThread(0)  # 你的RTSP视频流
        # 让信号绑定函数，用来在label上更新图片帧
        self.thread.model_detection_signal.connect(self.update_image)
        self.button.clicked.connect(self.start_streams)
 
    def start_streams(self):
        """
        # 定义方法改变按钮的字样，同时打开/关闭线程
        @return:
        """
        if self.button.text() == "打开":
            self.button.setText("关闭")
            # 开启线程
            self.thread.start()
        else:
            self.button.setText("打开")
            # 关闭线程
            self.thread.stop()
 
    def update_image(self, qimage):
        """
        # 用来更新图片
        @param qimage: 获取信号的图片帧
        @return: None
        """
        pixmap = QPixmap.fromImage(qimage)
        self.label.setPixmap(pixmap)
 
 
if __name__ == "__main__":
    app = QApplication(sys.argv)
    window = MainWindow()
    window.show()
    sys.exit(app.exec())