python代码实现：Qt界面链接yolov5目标检测

以下是使用 PyQT5 实现 Qt 界面链接 YOLOv5 目标检测的 Python 代码示例：

import sys
from PyQt5.QtWidgets import QApplication, QWidget, QLabel, QPushButton, QFileDialog
from PyQt5.QtGui import QPixmap
import cv2
from yolov5.detect import YOLOv5Detector

class App(QWidget):
    def __init__(self):
        super().__init__()
        self.title = 'YOLOv5 Object Detection'
        self.left = 50
        self.top = 50
        self.width = 640
        self.height = 480
        self.image_path = ''
        self.initUI()

    def initUI(self):
        self.setWindowTitle(self.title)
        self.setGeometry(self.left, self.top, self.width, self.height)

        # 选择图像文件按钮
        self.select_button = QPushButton('Select Image', self)
        self.select_button.move(20, 20)
        self.select_button.clicked.connect(self.select_image)

        # 显示图像
        self.image_label = QLabel(self)
        self.image_label.move(20, 60)
        self.image_label.resize(600, 400)

        # 检测目标按钮
        self.detect_button = QPushButton('Detect Objects', self)
        self.detect_button.move(20, 470)
        self.detect_button.clicked.connect(self.detect_objects)

        self.show()

    def select_image(self):
        options = QFileDialog.Options()
        options |= QFileDialog.DontUseNativeDialog
        file_name, _ = QFileDialog.getOpenFileName(self, 'Select Image', '', 'Images (*.png *.xpm *.jpg *.bmp *.gif)', options=options)
        if file_name:
            self.image_path = file_name
            pixmap = QPixmap(file_name)
            self.image_label.setPixmap(pixmap)
            self.image_label.setScaledContents(True)

    def detect_objects(self):
        if not self.image_path:
            return
        detector = YOLOv5Detector()
        image = cv2.imread(self.image_path)
        result_image, _ = detector.detect(image)
        cv2.imwrite('result.jpg', result_image)
        pixmap = QPixmap('result.jpg')
        self.image_label.setPixmap(pixmap)
        self.image_label.setScaledContents(True)

if __name__ == '__main__':
    app = QApplication(sys.argv)
    ex = App()
    sys.exit(app.exec_())

其中 `yolov5.detect` 模块的代码可以参考 YOLOv5 的官方实现。在 `detect` 函数中，需要对输入的图像进行目标检测，并返回检测结果。在本例中，我们将检测结果保存为 `result.jpg`，并在界面中显示出来。

注意，需要将模型文件和权重文件放在适当的位置，并在 `YOLOv5Detector` 类中设置正确的路径。