YOLOv8车牌识别系统 深度学习 LPRNet算法 pytorch 大数据 毕业设计（源码）✅_yolov8 lprnet

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1、项目介绍

技术栈：
Python3.8 YOLOv8 深度学习 LPRNet算法 pytorch

2、项目界面

（1）上传图片进行车牌识别

（2）上传图片进行车牌识别2

（3）多车牌号码进行车牌识别

（4）上传视频进行车牌识别实时检测

（5）连接摄像头进行车牌识别

（6）连接摄像头进行车牌识别2

（7）车牌识别检测

3、项目说明

项目介绍：
基于YOLOv8+LPRNet进行车牌检测及识别，包括对车辆的车牌区域精确定位，利用校正探测器对定位的车牌进行边框校正处理，使用增强神经网络模型对车牌区域进行超分辨率技术处理和光学字符识别。经过多次试验测试，可以对视频中的车辆车牌实时识别以及图片中的车辆车牌进行准确定位和识别，识别速度快，准确率高，比那些传统车牌识别方法效果好很多。

LPRNet由轻量级的卷积神经网络组成，所以它可以采用端到端的方法来进行训练。据我们所知，LPRNet是第一个没有采用RNNs的实时车牌识别系统。因此，LPRNet算法可以为LPR创建嵌入式部署的解决方案，即便是在具有较高挑战性的中文车牌识别上。

4、核心代码

from ultralytics.yolo.engine.predictor import BasePredictor
from ultralytics.yolo.engine.results import Results
from ultralytics.yolo.utils import DEFAULT_CFG, LOGGER, SETTINGS, callbacks, ops
from ultralytics.yolo.utils.plotting import Annotator, colors, save_one_box
from ultralytics.yolo.utils.torch_utils import smart_inference_mode
from ultralytics.yolo.utils.files import increment_path
from ultralytics.yolo.utils.checks import check_imshow
from ultralytics.yolo.cfg import get_cfg
from PySide6.QtWidgets import QApplication, QMainWindow, QFileDialog, QMenu
from PySide6.QtGui import QImage, QPixmap, QColor
from PySide6.QtCore import QTimer, QThread, Signal, QObject, QPoint, Qt
from ui.CustomMessageBox import MessageBox
from ui.home import Ui_MainWindow
from UIFunctions import *
from collections import defaultdict
from pathlib import Path
from utils.capnums import Camera
from utils.rtsp_win import Window

import numpy as np
import time
import json
import torch
import sys
import cv2
import os

from yoloPre import YoloPredictor


class MainWindow(QMainWindow, Ui_MainWindow):

    # 这是一个 PySide6 的信号（Signal）对象，
    # 用于在应用程序中传递消息。在这个场景中，它被用于在主窗口和 YOLO 实例之间传递消息。
    main2yolo_begin_sgl = Signal()  # The main window sends an execution signal to the yolo instance

    def __init__(self, parent=None):
        super(MainWindow, self).__init__(parent)

        # basic interface  【UI初始化！】
        self.setupUi(self)

        self.setAttribute(Qt.WA_TranslucentBackground)  # rounded transparent
        self.setWindowFlags(Qt.FramelessWindowHint)  # Set window flag: hide window borders
        UIFuncitons.uiDefinitions(self)

        # Show module shadows
        UIFuncitons.shadow_style(self, self.Class_QF, QColor(162,129,247))
        UIFuncitons.shadow_style(self, self.Target_QF, QColor(251, 157, 139))
        UIFuncitons.shadow_style(self, self.Fps_QF, QColor(170, 128, 213))
        UIFuncitons.shadow_style(self, self.Model_QF, QColor(64, 186, 193))

        # read model folder  加载模型
        self.pt_list = os.listdir('./models')
        self.pt_list = [file for file in self.pt_list if file.endswith('.pt')]
        self.pt_list.sort(key=lambda x: os.path.getsize('./models/' + x))   # sort by file size
        self.model_box.clear()
        self.model_box.addItems(self.pt_list)
        self.Qtimer_ModelBox = QTimer(self)     # Timer: Monitor model file changes every 2 seconds
        self.Qtimer_ModelBox.timeout.connect(self.ModelBoxRefre)
        self.Qtimer_ModelBox.start(2000)

        # Yolo-v8 thread  初始化
     
        self.yolo_predict = YoloPredictor()                           # Create a Yolo instance
        self.select_model = self.model_box.currentText()                   # default model
        self.yolo_predict.new_model_name = "./models/%s" % self.select_model  
        self.yolo_thread = QThread()                                  # Create yolo thread

        # 将 Yolo 类中的信号绑定到主线程的槽函数上
        self.yolo_predict.yolo2main_pre_img.connect(lambda x: self.show_image(x, self.pre_video)) 
        self.yolo_predict.yolo2main_res_img.connect(lambda x: self.show_image(x, self.res_video))
        self.yolo_predict.yolo2main_status_msg.connect(lambda x: self.show_status(x))             
        self.yolo_predict.yolo2main_fps.connect(lambda x: self.fps_label.setText(x))              
        # self.yolo_predict.yolo2main_labels.connect(self.show_labels)
        self.yolo_predict.yolo2main_class_num.connect(lambda x:self.Class_num.setText(str(x)))         
        self.yolo_predict.yolo2main_target_num.connect(lambda x:self.Target_num.setText(str(x)))       
        self.yolo_predict.yolo2main_progress.connect(lambda x: self.progress_bar.setValue(x))

        # 将主线程的信号绑定到 Yolo 类的槽函数上，并启动 Yolo 线程
        self.main2yolo_begin_sgl.connect(self.yolo_predict.run)     
        self.yolo_predict.moveToThread(self.yolo_thread)              

        # Model parameters
        self.model_box.currentTextChanged.connect(self.change_model)     
        self.iou_spinbox.valueChanged.connect(lambda x:self.change_val(x, 'iou_spinbox'))    # iou box
        self.iou_slider.valueChanged.connect(lambda x:self.change_val(x, 'iou_slider'))      # iou scroll bar
        self.conf_spinbox.valueChanged.connect(lambda x:self.change_val(x, 'conf_spinbox'))  # conf box
        self.conf_slider.valueChanged.connect(lambda x:self.change_val(x, 'conf_slider'))    # conf scroll bar
        self.speed_spinbox.valueChanged.connect(lambda x:self.change_val(x, 'speed_spinbox'))# speed box
        self.speed_slider.valueChanged.connect(lambda x:self.change_val(x, 'speed_slider'))  # speed scroll bar

        # Prompt window initialization
        self.Class_num.setText('--')
        self.Target_num.setText('--')
        self.fps_label.setText('--')
        self.Model_name.setText(self.select_model)
        
        # Select detection source
        self.src_file_button.clicked.connect(self.open_src_file)  # select local file
        self.src_cam_button.clicked.connect(self.chose_cam) #chose_camera
        # self.src_rtsp_button.clicked.connect(self.show_status("The function has not yet been implemented."))#chose_rtsp

        # start testing button
        self.run_button.clicked.connect(self.run_or_continue)   # pause/start
        self.stop_button.clicked.connect(self.stop)             # termination

        # Other function buttons
        self.save_res_button.toggled.connect(self.is_save_res)  # save image option
        self.save_txt_button.toggled.connect(self.is_save_txt)  # Save label option

        self.ToggleBotton.clicked.connect(lambda: UIFuncitons.toggleMenu(self, True))   # left navigation button
        self.settings_button.clicked.connect(lambda: UIFuncitons.settingBox(self, True))   # top right settings button
        
        # initialization
        self.load_config()



    # The main window displays the original image and detection results
    @staticmethod
    def show_image(img_src, label):
        try:
            ih, iw, _ = img_src.shape  # 获取原始图像的高度和宽度
            w = label.geometry().width()  # 获取 QLabel 组件的当前宽度
            h = label.geometry().height()  # 获取 QLabel 组件的当前高度

            # 根据原始图像和 QLabel 组件的大小，等比例缩放原始图像
            if iw / w > ih / h:  # 如果原始图像的宽度比高度大，按照宽度比例缩放
                scal = w / iw
                nw = w
                nh = int(scal * ih)
                img_src_ = cv2.resize(img_src, (nw, nh))
            else:  # 如果原始图像的高度比宽度大，按照高度比例缩放
                scal = h / ih
                nw = int(scal * iw)
                nh = h
                img_src_ = cv2.resize(img_src, (nw, nh))

            # 将 OpenCV 图像转换为 QImage 对象，并将其显示在 QLabel 组件中
            frame = cv2.cvtColor(img_src_, cv2.COLOR_BGR2RGB)  # 将图像的颜色空间从 BGR 转换为 RGB
            img = QImage(frame.data, frame.shape[1], frame.shape[0], frame.shape[2] * frame.shape[1],
                         QImage.Format_RGB888)  # 创建 QImage 对象
            label.setPixmap(QPixmap.fromImage(img))  # 将 QImage 对象转换为 QPixmap 对象，并将其显示在 QLabel 组件中


        except Exception as e:
            print(repr(e))

    # Control start/pause
    def run_or_continue(self):

        if self.yolo_predict.source == '':
            print('Please select a video source')
            self.show_status('Please select a video source before starting detection...')
            self.run_button.setChecked(False)
        else:
            self.yolo_predict.stop_dtc = False
            print('start')
            if self.run_button.isChecked():
                self.run_button.setChecked(True)    # start button
                self.save_txt_button.setEnabled(False)  # It is forbidden to check and save after starting the detection
                self.save_res_button.setEnabled(False)
                self.show_status('Detecting...')           
                self.yolo_predict.continue_dtc = True   # Control whether Yolo is paused

                if not self.yolo_thread.isRunning():
                    self.yolo_thread.start()
                    self.main2yolo_begin_sgl.emit()

            else:
                self.yolo_predict.continue_dtc = False
                self.show_status("Pause...")
                self.run_button.setChecked(False)    # start button

    # bottom status bar information
    def show_status(self, msg):
        self.status_bar.setText(msg)
        print(msg)
        if msg == 'Detection completed' or msg == '检测完成':
            self.save_res_button.setEnabled(True)
            self.save_txt_button.setEnabled(True)
            self.run_button.setChecked(False)    
            self.progress_bar.setValue(0)
            if self.yolo_thread.isRunning():
                self.yolo_thread.quit()         # end process
        elif msg == 'Detection terminated!' or msg == '检测终止':
            self.save_res_button.setEnabled(True)
            self.save_txt_button.setEnabled(True)
            self.run_button.setChecked(False)    
            self.progress_bar.setValue(0)
            if self.yolo_thread.isRunning():
                self.yolo_thread.quit()         # end process
            self.pre_video.clear()           # clear image display  
            self.res_video.clear()          
            self.Class_num.setText('--')
            self.Target_num.setText('--')
            self.fps_label.setText('--')

    # select local file
    def open_src_file(self):
        print('local file')
        config_file = 'config/fold.json'    
        config = json.load(open(config_file, 'r', encoding='utf-8'))
        open_fold = config['open_fold']     
        if not os.path.exists(open_fold):
            open_fold = os.getcwd()

  
        name, _ = QFileDialog.getOpenFileName(self, 'Video/image', open_fold, "Pic File(*.mp4 *.mkv *.avi *.flv *.jpg *.png)")
        if name:
            self.yolo_predict.source = name
            self.show_status('Load File：{}'.format(os.path.basename(name))) 
            config['open_fold'] = os.path.dirname(name)
            config_json = json.dumps(config, ensure_ascii=False, indent=2)  
            with open(config_file, 'w', encoding='utf-8') as f:
                f.write(config_json)
            self.stop()             

    # Select camera source----  have one bug
    def chose_cam(self):
        try:
            print('open camera')
            # self.stop()
            # MessageBox(
            #     self.close_button, title='Note', text='loading camera...', time=2000, auto=True).exec()
            # get the number of local cameras
            # _, cams = Camera().get_cam_num()

            # self.viewer = CameraViewer()  # 创建新的 CameraViewer 类的对象
            # self.viewer.show()  # 显示 CameraViewer 类的 GUI 界面

            self.yolo_predict.camera_run()



        except Exception as e:
            print(e)
            self.show_status('%s' % e)

    # select network source
    def chose_rtsp(self):
        self.rtsp_window = Window()
        config_file = 'config/ip.json'
        if not os.path.exists(config_file):
            ip = "rtsp://admin:admin888@192.168.1.2:555"
            new_config = {"ip": ip}
            new_json = json.dumps(new_config, ensure_ascii=False, indent=2)
            with open(config_file, 'w', encoding='utf-8') as f:
                f.write(new_json)
        else:
            config = json.load(open(config_file, 'r', encoding='utf-8'))
            ip = config['ip']
        self.rtsp_window.rtspEdit.setText(ip)
        self.rtsp_window.show()
        self.rtsp_window.rtspButton.clicked.connect(lambda: self.load_rtsp(self.rtsp_window.rtspEdit.text()))
    
    # load network sources
    def load_rtsp(self, ip):
        try:
            self.stop()
            MessageBox(
                self.close_button, title='提示', text='加载 rtsp...', time=1000, auto=True).exec()
            self.yolo_predict.source = ip
            new_config = {"ip": ip}
            new_json = json.dumps(new_config, ensure_ascii=False, indent=2)
            with open('config/ip.json', 'w', encoding='utf-8') as f:
                f.write(new_json)
            self.show_status('Loading rtsp：{}'.format(ip))
            self.rtsp_window.close()
        except Exception as e:
            self.show_status('%s' % e)

    # Save test result button--picture/video
    def is_save_res(self):
        if self.save_res_button.checkState() == Qt.CheckState.Unchecked:
            self.show_status('NOTE: Run image results are not saved.')
            self.yolo_predict.save_res = False
        elif self.save_res_button.checkState() == Qt.CheckState.Checked:
            self.show_status('NOTE: Run image results will be saved.')
            self.yolo_predict.save_res = True
    
    # Save test result button -- label (txt)
    def is_save_txt(self):
        if self.save_txt_button.checkState() == Qt.CheckState.Unchecked:
            self.show_status('NOTE: Labels results are not saved.')
            self.yolo_predict.save_txt = False
        elif self.save_txt_button.checkState() == Qt.CheckState.Checked:
            self.show_status('NOTE: Labels results will be saved.')
            self.yolo_predict.save_txt = True

    # Configuration initialization  ~~~wait to change~~~
    def load_config(self):
        config_file = 'config/setting.json'
        if not os.path.exists(config_file):
            iou = 0.26
            conf = 0.33   
            rate = 10
            save_res = 0   
            save_txt = 0    
            new_config = {"iou": iou,
                          "conf": conf,
                          "rate": rate,
                          "save_res": save_res,
                          "save_txt": save_txt
                          }
            new_json = json.dumps(new_config, ensure_ascii=False, indent=2)
            with open(config_file, 'w', encoding='utf-8') as f:
                f.write(new_json)
        else:
            config = json.load(open(config_file, 'r', encoding='utf-8'))
            if len(config) != 5:
                iou = 0.26
                conf = 0.33
                rate = 10
                save_res = 0
                save_txt = 0
            else:
                iou = config['iou']
                conf = config['conf']
                rate = config['rate']
                save_res = config['save_res']
                save_txt = config['save_txt']
        self.save_res_button.setCheckState(Qt.CheckState(save_res))
        self.yolo_predict.save_res = (False if save_res==0 else True )
        self.save_txt_button.setCheckState(Qt.CheckState(save_txt)) 
        self.yolo_predict.save_txt = (False if save_txt==0 else True )
        self.run_button.setChecked(False)  
        self.show_status("Welcome~")

    # Terminate button and associated state
    def stop(self):
        print('stop')
        if self.yolo_thread.isRunning():
            self.yolo_thread.quit()         # end thread
        self.yolo_predict.stop_dtc = True
        self.run_button.setChecked(False)    # start key recovery
        self.save_res_button.setEnabled(True)   # Ability to use the save button
        self.save_txt_button.setEnabled(True)   # Ability to use the save button
        self.pre_video.clear()           # clear image display
        self.res_video.clear()           # clear image display
        self.progress_bar.setValue(0)
        self.Class_num.setText('--')
        self.Target_num.setText('--')
        self.fps_label.setText('--')

    # Change detection parameters
    def change_val(self, x, flag):
        if flag == 'iou_spinbox':
            self.iou_slider.setValue(int(x*100))    # The box value changes, changing the slider
        elif flag == 'iou_slider':
            self.iou_spinbox.setValue(x/100)        # The slider value changes, changing the box
            self.show_status('IOU Threshold: %s' % str(x/100))
            self.yolo_predict.iou_thres = x/100
        elif flag == 'conf_spinbox':
            self.conf_slider.setValue(int(x*100))
        elif flag == 'conf_slider':
            self.conf_spinbox.setValue(x/100)
            self.show_status('Conf Threshold: %s' % str(x/100))
            self.yolo_predict.conf_thres = x/100
        elif flag == 'speed_spinbox':
            self.speed_slider.setValue(x)
        elif flag == 'speed_slider':
            self.speed_spinbox.setValue(x)
            self.show_status('Delay: %s ms' % str(x))
            self.yolo_predict.speed_thres = x  # ms
            
    # change model 【更换模型】
    def change_model(self,x):
        self.select_model = self.model_box.currentText()
        self.yolo_predict.new_model_name = "./models/%s" % self.select_model
        self.show_status('Change Model：%s' % self.select_model)
        self.Model_name.setText(self.select_model)

    # label result
    # def show_labels(self, labels_dic):
    #     try:
    #         self.result_label.clear()
    #         labels_dic = sorted(labels_dic.items(), key=lambda x: x[1], reverse=True)
    #         labels_dic = [i for i in labels_dic if i[1]>0]
    #         result = [' '+str(i[0]) + '：' + str(i[1]) for i in labels_dic]
    #         self.result_label.addItems(result)
    #     except Exception as e:
    #         self.show_status(e)

    # Cycle monitoring model file changes
    def ModelBoxRefre(self):
        pt_list = os.listdir('./models')
        pt_list = [file for file in pt_list if file.endswith('.pt')]
        pt_list.sort(key=lambda x: os.path.getsize('./models/' + x))
        # It must be sorted before comparing, otherwise the list will be refreshed all the time
        if pt_list != self.pt_list:
            self.pt_list = pt_list
            self.model_box.clear()
            self.model_box.addItems(self.pt_list)

    # Get the mouse position (used to hold down the title bar and drag the window)
    def mousePressEvent(self, event):
        p = event.globalPosition()
        globalPos = p.toPoint()
        self.dragPos = globalPos

    # Optimize the adjustment when dragging the bottom and right edges of the window size
    def resizeEvent(self, event):
        # Update Size Grips
        UIFuncitons.resize_grips(self)

    # Exit Exit thread, save settings
    def closeEvent(self, event):
        config_file = 'config/setting.json'
        config = dict()
        config['iou'] = self.iou_spinbox.value()
        config['conf'] = self.conf_spinbox.value()
        config['rate'] = self.speed_spinbox.value()
        config['save_res'] = (0 if self.save_res_button.checkState()==Qt.Unchecked else 2)
        config['save_txt'] = (0 if self.save_txt_button.checkState()==Qt.Unchecked else 2)
        config_json = json.dumps(config, ensure_ascii=False, indent=2)
        with open(config_file, 'w', encoding='utf-8') as f:
            f.write(config_json)
        # Exit the process before closing
        if self.yolo_thread.isRunning():
            self.yolo_predict.stop_dtc = True
            self.yolo_thread.quit()
            MessageBox(
                self.close_button, title='Note', text='Exiting, please wait...', time=3000, auto=True).exec()
            sys.exit(0)
        else:
            sys.exit(0)


if __name__ == "__main__":
    app = QApplication(sys.argv)
    Home = MainWindow()
    Home.show()
    sys.exit(app.exec())  
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