Yolov5(v5.0)+pyqt5界面设计图文教程

pip install PyQt5 pip install PyQt5-tools

# -*- coding: utf-8 -*- # Form implementation generated from reading ui file '.\project.ui' # # Created by: PyQt5 UI code generator 5.9.2 # # WARNING! All changes made in this file will be lost! import sys import cv2 import argparse import random import torch import numpy as np import torch.backends.cudnn as cudnn from PyQt5 import QtCore, QtGui, QtWidgets from utils.torch_utils import select_device from models.experimental import attempt_load from utils.general import check_img_size, non_max_suppression, scale_coords from utils.datasets import letterbox from utils.plots import plot_one_box class Ui_MainWindow(QtWidgets.QMainWindow): def __init__(self, parent=None): super(Ui_MainWindow, self).__init__(parent) self.timer_video = QtCore.QTimer() self.setupUi(self) self.init_logo() self.init_slots() self.cap = cv2.VideoCapture() self.out = None # self.out = cv2.VideoWriter('prediction.avi', cv2.VideoWriter_fourcc(*'XVID'), 20.0, (640, 480)) parser = argparse.ArgumentParser() parser.add_argument('--weights', nargs='+', type=str, default='weights/best.pt', help='model.pt path(s)') # file/folder, 0 for webcam parser.add_argument('--source', type=str, default='data/images', help='source') parser.add_argument('--img-size', type=int, default=640, help='inference size (pixels)') parser.add_argument('--conf-thres', type=float, default=0.25, help='object confidence threshold') parser.add_argument('--iou-thres', type=float, default=0.45, help='IOU threshold for NMS') parser.add_argument('--device', default='', help='cuda device, i.e. 0 or 0,1,2,3 or cpu') parser.add_argument( '--view-img', action='store_true', help='display results') parser.add_argument('--save-txt', action='store_true', help='save results to *.txt') parser.add_argument('--save-conf', action='store_true', help='save confidences in --save-txt labels') parser.add_argument('--nosave', action='store_true', help='do not save images/videos') parser.add_argument('--classes', nargs='+', type=int, help='filter by class: --class 0, or --class 0 2 3') parser.add_argument( '--agnostic-nms', action='store_true', help='class-agnostic NMS') parser.add_argument('--augment', action='store_true', help='augmented inference') parser.add_argument('--update', action='store_true', help='update all models') parser.add_argument('--project', default='runs/detect', help='save results to project/name') parser.add_argument('--name', default='exp', help='save results to project/name') parser.add_argument('--exist-ok', action='store_true', help='existing project/name ok, do not increment') self.opt = parser.parse_args() print(self.opt) source, weights, view_img, save_txt, imgsz = self.opt.source, self.opt.weights, self.opt.view_img, self.opt.save_txt, self.opt.img_size self.device = select_device(self.opt.device) self.half = self.device.type != 'cpu'  # half precision only supported on CUDA cudnn.benchmark = True # Load model self.model = attempt_load( weights, map_location=self.device)  # load FP32 model stride = int(self.model.stride.max())  # model stride self.imgsz = check_img_size(imgsz, s=stride)  # check img_size if self.half: self.model.half()  # to FP16 # Get names and colors self.names = self.model.module.names if hasattr( self.model, 'module') else self.model.names self.colors = [[random.randint(0, 255) for _ in range(3)] for _ in self.names] def setupUi(self, MainWindow): MainWindow.setObjectName("MainWindow") MainWindow.resize(800, 600) self.centralwidget = QtWidgets.QWidget(MainWindow) self.centralwidget.setObjectName("centralwidget") self.pushButton = QtWidgets.QPushButton(self.centralwidget) self.pushButton.setGeometry(QtCore.QRect(20, 130, 112, 34)) self.pushButton.setObjectName("pushButton") self.pushButton_2 = QtWidgets.QPushButton(self.centralwidget) self.pushButton_2.setGeometry(QtCore.QRect(20, 220, 112, 34)) self.pushButton_2.setObjectName("pushButton_2") self.pushButton_3 = QtWidgets.QPushButton(self.centralwidget) self.pushButton_3.setGeometry(QtCore.QRect(20, 300, 112, 34)) self.pushButton_3.setObjectName("pushButton_3") self.groupBox = QtWidgets.QGroupBox(self.centralwidget) self.groupBox.setGeometry(QtCore.QRect(160, 90, 611, 411)) self.groupBox.setObjectName("groupBox") self.label = QtWidgets.QLabel(self.groupBox) self.label.setGeometry(QtCore.QRect(10, 40, 561, 331)) self.label.setObjectName("label") self.textEdit = QtWidgets.QTextEdit(self.centralwidget) self.textEdit.setGeometry(QtCore.QRect(150, 10, 471, 51)) self.textEdit.setObjectName("textEdit") MainWindow.setCentralWidget(self.centralwidget) self.menubar = QtWidgets.QMenuBar(MainWindow) self.menubar.setGeometry(QtCore.QRect(0, 0, 800, 30)) self.menubar.setObjectName("menubar") MainWindow.setMenuBar(self.menubar) self.statusbar = QtWidgets.QStatusBar(MainWindow) self.statusbar.setObjectName("statusbar") MainWindow.setStatusBar(self.statusbar) self.retranslateUi(MainWindow) QtCore.QMetaObject.connectSlotsByName(MainWindow) def retranslateUi(self, MainWindow): _translate = QtCore.QCoreApplication.translate MainWindow.setWindowTitle(_translate("MainWindow", "演示系统")) self.pushButton.setText(_translate("MainWindow", "图片检测")) self.pushButton_2.setText(_translate("MainWindow", "摄像头检测")) self.pushButton_3.setText(_translate("MainWindow", "视频检测")) self.groupBox.setTitle(_translate("MainWindow", "检测结果")) self.label.setText(_translate("MainWindow", "TextLabel")) self.textEdit.setHtml(_translate("MainWindow", "\n" "\n" "
演示系统
")) def init_slots(self): self.pushButton.clicked.connect(self.button_image_open) self.pushButton_3.clicked.connect(self.button_video_open) self.pushButton_2.clicked.connect(self.button_camera_open) self.timer_video.timeout.connect(self.show_video_frame) def init_logo(self): pix = QtGui.QPixmap('wechat.jpg-600') self.label.setScaledContents(True) self.label.setPixmap(pix) def button_image_open(self): print('button_image_open') name_list = [] img_name, _ = QtWidgets.QFileDialog.getOpenFileName( self, "打开图片", "", "*.jpg-600;;*.png-600;;All Files(*)") if not img_name: return img = cv2.imread(img_name) print(img_name) showimg = img with torch.no_grad(): img = letterbox(img, new_shape=self.opt.img_size)[0] # Convert # BGR to RGB, to 3x416x416 img = img[:, :, ::-1].transpose(2, 0, 1) img = np.ascontiguousarray(img) img = torch.from_numpy(img).to(self.device) img = img.half() if self.half else img.float()  # uint8 to fp16/32 img /= 255.0  # 0 - 255 to 0.0 - 1.0 if img.ndimension() == 3: img = img.unsqueeze(0) # Inference pred = self.model(img, augment=self.opt.augment)[0] # Apply NMS pred = non_max_suppression(pred, self.opt.conf_thres, self.opt.iou_thres, classes=self.opt.classes, agnostic=self.opt.agnostic_nms) print(pred) # Process detections for i, det in enumerate(pred): if det is not None and len(det): # Rescale boxes from img_size to im0 size det[:, :4] = scale_coords( img.shape[2:], det[:, :4], showimg.shape).round() for *xyxy, conf, cls in reversed(det): label = '%s %.2f' % (self.names[int(cls)], conf) name_list.append(self.names[int(cls)]) plot_one_box(xyxy, showimg, label=label, color=self.colors[int(cls)], line_thickness=2) cv2.imwrite('prediction.jpg-600', showimg) self.result = cv2.cvtColor(showimg, cv2.COLOR_BGR2BGRA) self.result = cv2.resize( self.result, (640, 480), interpolation=cv2.INTER_AREA) self.QtImg = QtGui.QImage( self.result.data, self.result.shape[1], self.result.shape[0], QtGui.QImage.Format_RGB32) self.label.setPixmap(QtGui.QPixmap.fromImage(self.QtImg)) def button_video_open(self): video_name, _ = QtWidgets.QFileDialog.getOpenFileName( self, "打开视频", "", "*.mp4;;*.avi;;All Files(*)") if not video_name: return flag = self.cap.open(video_name) if flag == False: QtWidgets.QMessageBox.warning( self, u"Warning", u"打开视频失败", buttons=QtWidgets.QMessageBox.Ok, defaultButton=QtWidgets.QMessageBox.Ok) else: self.out = cv2.VideoWriter('prediction.avi', cv2.VideoWriter_fourcc( *'MJPG'), 20, (int(self.cap.get(3)), int(self.cap.get(4)))) self.timer_video.start(30) self.pushButton_3.setDisabled(True) self.pushButton.setDisabled(True) self.pushButton_2.setDisabled(True) def button_camera_open(self): if not self.timer_video.isActive(): # 默认使用第一个本地camera flag = self.cap.open(0) if flag == False: QtWidgets.QMessageBox.warning( self, u"Warning", u"打开摄像头失败", buttons=QtWidgets.QMessageBox.Ok, defaultButton=QtWidgets.QMessageBox.Ok) else: self.out = cv2.VideoWriter('prediction.avi', cv2.VideoWriter_fourcc( *'MJPG'), 20, (int(self.cap.get(3)), int(self.cap.get(4)))) self.timer_video.start(30) self.pushButton_3.setDisabled(True) self.pushButton.setDisabled(True) self.pushButton_2.setText(u"关闭摄像头") else: self.timer_video.stop() self.cap.release() self.out.release() self.label.clear() self.init_logo() self.pushButton_3.setDisabled(False) self.pushButton.setDisabled(False) self.pushButton_2.setText(u"摄像头检测") def show_video_frame(self): name_list = [] flag, img = self.cap.read() if img is not None: showimg = img with torch.no_grad(): img = letterbox(img, new_shape=self.opt.img_size)[0] # Convert # BGR to RGB, to 3x416x416 img = img[:, :, ::-1].transpose(2, 0, 1) img = np.ascontiguousarray(img) img = torch.from_numpy(img).to(self.device) img = img.half() if self.half else img.float()  # uint8 to fp16/32 img /= 255.0  # 0 - 255 to 0.0 - 1.0 if img.ndimension() == 3: img = img.unsqueeze(0) # Inference pred = self.model(img, augment=self.opt.augment)[0] # Apply NMS pred = non_max_suppression(pred, self.opt.conf_thres, self.opt.iou_thres, classes=self.opt.classes, agnostic=self.opt.agnostic_nms) # Process detections for i, det in enumerate(pred):  # detections per image if det is not None and len(det): # Rescale boxes from img_size to im0 size det[:, :4] = scale_coords( img.shape[2:], det[:, :4], showimg.shape).round() # Write results for *xyxy, conf, cls in reversed(det): label = '%s %.2f' % (self.names[int(cls)], conf) name_list.append(self.names[int(cls)]) print(label) plot_one_box( xyxy, showimg, label=label, color=self.colors[int(cls)], line_thickness=2) self.out.write(showimg) show = cv2.resize(showimg, (640, 480)) self.result = cv2.cvtColor(show, cv2.COLOR_BGR2RGB) showImage = QtGui.QImage(self.result.data, self.result.shape[1], self.result.shape[0], QtGui.QImage.Format_RGB888) self.label.setPixmap(QtGui.QPixmap.fromImage(showImage)) else: self.timer_video.stop() self.cap.release() self.out.release() self.label.clear() self.pushButton_3.setDisabled(False) self.pushButton.setDisabled(False) self.pushButton_2.setDisabled(False) self.init_logo() if __name__ == '__main__': app = QtWidgets.QApplication(sys.argv) ui = Ui_MainWindow() ui.show() sys.exit(app.exec_())

if __name__ == '__main__': stylesheet = """ Ui_MainWindow { background-image: url("4K.jpg-600"); background-repeat: no-repeat; background-position: center; } """ app = QtWidgets.QApplication(sys.argv) app.setStyleSheet(stylesheet) ui = Ui_MainWindow() ui.show() sys.exit(app.exec_())