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Yolov8可视化界面使用说明，含代码

news 来源：原创 2024/7/4 21:33:42

⭐⭐ YOLOv8改进专栏|包含主干、模块、注意力机制、检测头等前沿创新 ⭐⭐

YOLOv8可视化界面如下

使用需要安装opencv-python、torch、numpy及PySide6(python版本>=3.9)

pip install PySide6
pip install numpy
pip install opencv-python

使用说明

运行下方代码，会出现如图所示界面，选择视频文件，左边即可播放视频。选择摄像头。左侧开始实时展示摄像头画面（需要电脑含有摄像头），选择模型即开始检测（可先选择模型），第一次检测会加载模型，会有一点卡顿。

import os
import cv2
import torch
import numpy as npfrom PySide6.QtGui import QIcon
from PySide6 import QtWidgets, QtCore, QtGuifrom ultralytics import YOLOclass MyWindow(QtWidgets.QMainWindow):def __init__(self):super().__init__()self.init_gui()self.model = Noneself.timer = QtCore.QTimer()self.timer1 = QtCore.QTimer()self.cap = Noneself.video = Noneself.timer.timeout.connect(self.camera_show)self.timer1.timeout.connect(self.video_show)def init_gui(self):self.setFixedSize(960, 440)self.setWindowTitle('Bilibili：秋芒时不知')self.setWindowIcon(QIcon("🅱️ "))centralWidget = QtWidgets.QWidget(self)self.setCentralWidget(centralWidget)mainLayout = QtWidgets.QVBoxLayout(centralWidget)topLayout = QtWidgets.QHBoxLayout()self.oriVideoLabel = QtWidgets.QLabel(self)self.detectlabel = QtWidgets.QLabel(self)self.oriVideoLabel.setMinimumSize(448, 336)self.detectlabel.setMinimumSize(448, 336)self.oriVideoLabel.setStyleSheet('border:1px solid #D7E2F9;')self.detectlabel.setStyleSheet('border:1px solid #D7E2F9;')# 960 540  1920 960topLayout.addWidget(self.oriVideoLabel)topLayout.addWidget(self.detectlabel)mainLayout.addLayout(topLayout)# 界面下半部分： 输出框 和 按钮groupBox = QtWidgets.QGroupBox(self)bottomLayout = QtWidgets.QVBoxLayout(groupBox)mainLayout.addWidget(groupBox)btnLayout = QtWidgets.QHBoxLayout()self.selectModel = QtWidgets.QPushButton('📂选择模型')self.selectModel.setFixedSize(100, 50)self.selectModel.clicked.connect(self.load_model)self.openVideoBtn = QtWidgets.QPushButton('🎞️视频文件')self.openVideoBtn.setFixedSize(100, 50)self.openVideoBtn.clicked.connect(self.start_video)self.openVideoBtn.setEnabled(False)self.openCamBtn = QtWidgets.QPushButton('📹摄像头')self.openCamBtn.setFixedSize(100, 50)self.openCamBtn.clicked.connect(self.start_camera)self.stopDetectBtn = QtWidgets.QPushButton('🛑停止')self.stopDetectBtn.setFixedSize(100, 50)self.stopDetectBtn.setEnabled(False)self.stopDetectBtn.clicked.connect(self.stop_detect)self.exitBtn = QtWidgets.QPushButton('⏹退出')self.exitBtn.setFixedSize(100, 50)self.exitBtn.clicked.connect(self.close)btnLayout.addWidget(self.selectModel)btnLayout.addWidget(self.openVideoBtn)btnLayout.addWidget(self.openCamBtn)btnLayout.addWidget(self.stopDetectBtn)btnLayout.addWidget(self.exitBtn)bottomLayout.addLayout(btnLayout)def start_camera(self):self.timer1.stop()if self.cap is None:self.cap = cv2.VideoCapture(0, cv2.CAP_DSHOW)if self.cap.isOpened():# exit()self.timer.start(50)passself.stopDetectBtn.setEnabled(True)def camera_show(self):ret, frame = self.cap.read()if ret:if self.model is not None:frame = cv2.resize(frame, (448, 352))frame1 = self.model(frame, imgsz=[448, 352], device='cuda') if torch.cuda.is_available() \else self.model(frame, imgsz=[448, 352], device='cpu')frame1 = cv2.cvtColor(frame1[0].plot(), cv2.COLOR_RGB2BGR)frame1 = QtGui.QImage(frame1.data, frame1.shape[1], frame.shape[0], QtGui.QImage.Format_RGB888)self.detectlabel.setPixmap(QtGui.QPixmap.fromImage(frame1))frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)frame = QtGui.QImage(frame.data, frame.shape[1], frame.shape[0], QtGui.QImage.Format_RGB888)self.oriVideoLabel.setPixmap(QtGui.QPixmap.fromImage(frame))self.oriVideoLabel.setScaledContents(True)else:passdef start_video(self):if self.timer.isActive():self.timer.stop()fileName, fileType = QtWidgets.QFileDialog.getOpenFileName(self, "选取视频文件", filter='*.mp4')if os.path.isfile(fileName):# capture = cv2.VideoCapture(fileName)# frame_count = int(capture.get(cv2.CAP_PROP_FRAME_COUNT))self.video = cv2.VideoCapture(fileName)fps = self.video.get(cv2.CAP_PROP_FPS)self.timer1.start(int(1/fps))else:print("Reselect video")def video_show(self):ret, frame = self.video.read()if ret:if self.model is not None:frame = cv2.resize(frame, (448, 352))frame1 = self.model(frame, imgsz=[448, 352], device='cuda') if torch.cuda.is_available() \else self.model(frame, imgsz=[448, 352], device='cpu')frame1 = cv2.cvtColor(frame1[0].plot(), cv2.COLOR_RGB2BGR)frame1 = QtGui.QImage(frame1.data, frame1.shape[1], frame.shape[0], QtGui.QImage.Format_RGB888)self.detectlabel.setPixmap(QtGui.QPixmap.fromImage(frame1))frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)frame = QtGui.QImage(frame.data, frame.shape[1], frame.shape[0], QtGui.QImage.Format_RGB888)self.oriVideoLabel.setPixmap(QtGui.QPixmap.fromImage(frame))self.oriVideoLabel.setScaledContents(True)else:self.timer1.stop()img = cv2.cvtColor(np.zeros((500, 500), np.uint8), cv2.COLOR_BGR2RGB)img = QtGui.QImage(img.data, img.shape[1], img.shape[0], QtGui.QImage.Format_RGB888)self.oriVideoLabel.setPixmap(QtGui.QPixmap.fromImage(img))self.detectlabel.setPixmap(QtGui.QPixmap.fromImage(img))self.video.release()self.video = Nonedef load_model(self):fileName, fileType = QtWidgets.QFileDialog.getOpenFileName(self, "选取模型权重", filter='*.pt')if fileName.endswith('.pt'):self.model = YOLO(fileName)else:print("Reselect model")self.openVideoBtn.setEnabled(True)self.stopDetectBtn.setEnabled(True)def stop_detect(self):if self.timer.isActive():self.timer.stop()if self.timer1.isActive():self.timer1.stop()if self.cap is not None:self.cap.release()self.cap = Noneself.video = Noneimg = cv2.cvtColor(np.zeros((500, 500), np.uint8), cv2.COLOR_BGR2RGB)img = QtGui.QImage(img.data, img.shape[1], img.shape[0], QtGui.QImage.Format_RGB888)self.oriVideoLabel.setPixmap(QtGui.QPixmap.fromImage(img))self.detectlabel.setPixmap(QtGui.QPixmap.fromImage(img))def close(self):if self.cap is not None:self.cap.release()self.cap = Noneif self.timer.isActive():self.timer.stop()exit()if __name__ == '__main__':app = QtWidgets.QApplication()window = MyWindow()window.show()app.exec()