YOLOv5是一种高效的实时目标检测算法，广泛应用于各类计算机视觉任务中。为了实现便捷的图形用户界面（GUI），我们采用了PyQt框架。PyQt是一个Python绑定的Qt库，用于创建跨平台的应用程序。

在本研究中，我们首先对YOLOv5模型进行了训练和优化，以适应特定的目标检测需求。接着，设计并实现了一个基于PyQt的图形用户界面，用户可以通过该界面加载图像或视频，并实时查看目标检测结果。我们详细阐述了如何将YOLOv5模型集成到PyQt应用程序中的具体步骤，包括模型加载、图像预处理、目标检测以及结果展示等关键环节。

github:https://github.com/Hjananggch/pyqt_yolo

import sys
import cv2
import torch
from PyQt5.QtWidgets import (QApplication, QWidget, QPushButton, QVBoxLayout,QFileDialog, QLabel, QHBoxLayout)
from PyQt5.QtCore import QTimer, Qt
from PyQt5.QtGui import QImage, QPixmap, QFont#加载模型
model = torch.hub.load(r'C:\Users\AN\Desktop\pyqt_yolo\model', 'custom',path=r"C:\Users\AN\Desktop\pyqt_yolo\weights\best.pt", source='local')
model.conf = 0.5
model.iou = 0.45class VideoPlayer(QWidget):def __init__(self):super().__init__()self.initUI()def initUI(self):self.setWindowTitle('YOLOv5 Video Player')self.setGeometry(100, 100, 1000, 700)self.layout = QVBoxLayout()title = QLabel('YOLOv5 Object Detection Video Player')title.setFont(QFont('Arial', 20))title.setAlignment(Qt.AlignCenter)self.layout.addWidget(title)self.videoLabel = QLabel()self.videoLabel.setAlignment(Qt.AlignCenter)self.layout.addWidget(self.videoLabel)buttonLayout = QHBoxLayout()self.openButton = QPushButton('Open Video')self.openButton.setFont(QFont('Arial', 14))self.openButton.clicked.connect(self.openVideoFile)buttonLayout.addWidget(self.openButton)self.quitButton = QPushButton('Quit')self.quitButton.setFont(QFont('Arial', 14))self.quitButton.clicked.connect(self.close)buttonLayout.addWidget(self.quitButton)self.layout.addLayout(buttonLayout)self.setLayout(self.layout)self.timer = QTimer()self.timer.timeout.connect(self.nextFrameSlot)self.cap = Nonedef openVideoFile(self):videoPath, _ = QFileDialog.getOpenFileName(self, "Open Video File", "", "Video Files (*.mp4 *.avi *.mkv)")if videoPath != '':self.cap = cv2.VideoCapture(videoPath)self.timer.start(30)def nextFrameSlot(self):ret, frame = self.cap.read()if ret:results = model(frame)frame = self.box(frame, results)frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)image = QImage(frame, frame.shape[1], frame.shape[0], frame.strides[0], QImage.Format_RGB888)self.videoLabel.setPixmap(QPixmap.fromImage(image))else:self.timer.stop()self.cap.release()def box(self, frame, results):results = results.pandas().xyxy[0].to_numpy()color = (251, 238, 1)for box in results:cls = box[6]l, t, r, b = box[:4].astype('int')cv2.rectangle(frame, (l, t), (r, b), color, 2)cv2.putText(frame, str(cls), (l, t), cv2.FONT_HERSHEY_SIMPLEX, 1, color, 1)return frameif __name__ == '__main__':app = QApplication(sys.argv)player = VideoPlayer()player.show()sys.exit(app.exec_())