智慧改进巡检-YOLO26可运行项目有上百个模块发SCI二区时集成的一些模块适合需要算法创新模块改进的朋友。目标检测语义分割关键点识别通用项目。项目中的所有改进已经按功能类别进行分组可针对你的数据集自己改进:1.GUI界面实现登陆注册图片视频摄像头文件夹识别可定制GUI界面2.轻量化模块3.小目标识别模块4.多尺度模块5.Transformer模块6.频域增强模块7.上采样改进8.下采样改进9.主干网络替换10.Neck网络替换11.数据增强代码map50PR曲线代码等等几乎包含yolo模型改进的所有类别模块内置批量训练模块可助你快速迭代模型提升精度。包含✅ 带登录注册的PySide6 GUI界面✅ 所有模块分组注意力、轻量化、多尺度、频域、上下采样等✅ 批量训练脚本✅ 采油井检测示例✅ 可直接运行、可自定义模块一、项目完整目录结构ultralytics-main/ ├── GUI/ │ ├── run_main_login.py # 带登录的主程序入口 │ ├── run_main_noLogin.py # 无登录的快速入口 │ └── ui_images/ # 界面背景图 ├── models/ │ ├── 11/ # 多尺度模块 │ ├── 12/ # 上采样改进 │ ├── 26/ # YOLO26基础模块 │ ├── Attention/ # 注意力机制模块 │ ├── Backbone/ # 主干网络替换 │ ├── Block/ # C3K2模块替换 │ ├── Downsample/ # 下采样改进 │ ├── Frequency/ # 频域增强模块 │ ├── Lightweight/ # 轻量化模块 │ ├── MS/ # 多尺度改进 │ ├── Neck/ # Neck网络替换 │ ├── Transformer/ # Transformer模块 │ └── Upsample/ # 上采样改进 ├── 数据增强/ │ └── data_augment.py # 数据增强代码 ├── 常用工具/ │ ├── pr_curve.py # PR曲线绘制 │ └── map_calc.py # mAP计算 ├── run_main_login.py # 项目入口 ├── train.py # 单模型训练 ├── train_mult.py # 批量训练脚本 ├── val.py # 验证脚本 ├── predict.py # 推理脚本 ├── requirements.txt # 依赖包 ├── yolo26n.pt # 基础权重文件 └── 运行与配置说明.md # 配置说明二、核心代码实现1. 带登录注册的主程序run_main_login.pyimportsysimportosimportsqlite3importhashlibfromPySide6.QtWidgetsimport*fromPySide6.QtGuiimport*fromPySide6.QtCoreimport*fromultralyticsimportYOLO# ---------------------- 数据库初始化 ----------------------definit_db():connsqlite3.connect(users.db)cconn.cursor()c.execute(CREATE TABLE IF NOT EXISTS users (username TEXT PRIMARY KEY, password TEXT))conn.commit()conn.close()defhash_pwd(pwd):returnhashlib.sha256(pwd.encode()).hexdigest()defregister_user(username,pwd):try:connsqlite3.connect(users.db)cconn.cursor()c.execute(INSERT INTO users VALUES (?, ?),(username,hash_pwd(pwd)))conn.commit()conn.close()returnTrueexceptsqlite3.IntegrityError:returnFalsedeflogin_user(username,pwd):connsqlite3.connect(users.db)cconn.cursor()c.execute(SELECT * FROM users WHERE username? AND password?,(username,hash_pwd(pwd)))resc.fetchone()conn.close()returnresisnotNone# ---------------------- 登录窗口 ----------------------classLoginWindow(QMainWindow):def__init__(self):super().__init__()self.setWindowTitle(YOLO26目标检测系统-登录)self.setFixedSize(800,500)self.init_ui()definit_ui(self):centralQWidget()self.setCentralWidget(central)layoutQHBoxLayout(central)# 左侧手绘背景leftQLabel()left.setPixmap(QPixmap(GUI/ui_images/background_sketch.png).scaled(400,500,Qt.KeepAspectRatioByExpanding))layout.addWidget(left,stretch1)# 右侧登录表单rightQWidget()right_layoutQVBoxLayout(right)right_layout.setAlignment(Qt.AlignCenter)self.user_editQLineEdit()self.user_edit.setPlaceholderText(用户名)self.user_edit.setStyleSheet(padding:10px; border-radius:5px; background:#f0f0f0;)self.pwd_editQLineEdit()self.pwd_edit.setPlaceholderText(密码)self.pwd_edit.setEchoMode(QLineEdit.Password)self.pwd_edit.setStyleSheet(padding:10px; border-radius:5px; background:#f0f0f0;)self.remember_checkQCheckBox(记住密码)self.forget_btnQLabel(a href# stylecolor:#888;忘记密码/a)self.forget_btn.setTextInteractionFlags(Qt.TextBrowserInteraction)form_layoutQHBoxLayout()form_layout.addWidget(self.remember_check)form_layout.addWidget(self.forget_btn)self.login_btnQPushButton(登录)self.login_btn.setStyleSheet(background:#007AFF; color:white; padding:12px; border-radius:8px; font-size:16px;)self.login_btn.clicked.connect(self.login)self.register_btnQLabel(a href# stylecolor:#007AFF;注册账号/a)self.register_btn.setTextInteractionFlags(Qt.TextBrowserInteraction)self.register_btn.linkActivated.connect(self.show_register)right_layout.addWidget(self.user_edit)right_layout.addWidget(self.pwd_edit)right_layout.addLayout(form_layout)right_layout.addWidget(self.login_btn)right_layout.addWidget(self.register_btn,alignmentQt.AlignCenter)layout.addWidget(right,stretch1)deflogin(self):userself.user_edit.text()pwdself.pwd_edit.text()iflogin_user(user,pwd):self.main_winMainWindow()self.main_win.show()self.close()else:QMessageBox.warning(self,错误,用户名或密码错误)defshow_register(self):reg_dialogRegisterDialog(self)reg_dialog.exec()classRegisterDialog(QDialog):def__init__(self,parentNone):super().__init__(parent)self.setWindowTitle(注册账号)self.setFixedSize(300,200)self.init_ui()definit_ui(self):layoutQVBoxLayout(self)self.user_editQLineEdit(placeholderText用户名)self.pwd_editQLineEdit(placeholderText密码,echoModeQLineEdit.Password)self.confirm_editQLineEdit(placeholderText确认密码,echoModeQLineEdit.Password)self.register_btnQPushButton(注册,clickedself.do_register)layout.addWidget(self.user_edit)layout.addWidget(self.pwd_edit)layout.addWidget(self.confirm_edit)layout.addWidget(self.register_btn)defdo_register(self):userself.user_edit.text()pwdself.pwd_edit.text()confirmself.confirm_edit.text()ifpwd!confirm:QMessageBox.warning(self,错误,两次密码不一致)returnifregister_user(user,pwd):QMessageBox.information(self,成功,注册成功)self.accept()else:QMessageBox.warning(self,错误,用户名已存在)# ---------------------- 主检测窗口 ----------------------classMainWindow(QMainWindow):def__init__(self):super().__init__()self.setWindowTitle(YOLO26目标检测系统)self.setFixedSize(1300,800)self.modelNoneself.init_ui()self.load_model()definit_ui(self):centralQWidget()self.setCentralWidget(central)layoutQHBoxLayout(central)# 左侧检测画面leftQWidget()left_layoutQVBoxLayout(left)self.img_labelQLabel(等待检测...)self.img_label.setAlignment(Qt.AlignCenter)self.img_label.setStyleSheet(background:#222; border-radius:5px;)left_layout.addWidget(self.img_label)layout.addWidget(left,stretch3)# 右侧控制面板rightQWidget()right_layoutQVBoxLayout(right)# 模型设置model_groupQGroupBox(模型设置)model_layoutQFormLayout(model_group)self.conf_spinQDoubleSpinBox(range(0.01,1.0),value0.3)self.iou_spinQDoubleSpinBox(range(0.01,1.0),value0.45)model_layout.addRow(置信度(conf):,self.conf_spin)model_layout.addRow(IOU阈值:,self.iou_spin)right_layout.addWidget(model_group)# 检测模式func_groupQGroupBox(检测模式)func_layoutQVBoxLayout(func_group)self.btn_imgQPushButton(选择图片,clickedself.open_image)self.btn_folderQPushButton(选择文件夹,clickedself.open_folder)self.btn_videoQPushButton(选择视频,clickedself.open_video)self.btn_cameraQPushButton(打开摄像头,clickedself.open_camera)self.btn_stopQPushButton(停止检测,clickedself.stop_detect)func_layout.addWidget(self.btn_img)func_layout.addWidget(self.btn_folder)func_layout.addWidget(self.btn_video)func_layout.addWidget(self.btn_camera)func_layout.addWidget(self.btn_stop)right_layout.addWidget(func_group)# 结果显示self.result_textQTextEdit(readOnlyTrue)right_layout.addWidget(QLabel(检测结果))right_layout.addWidget(self.result_text)layout.addWidget(right,stretch1)defload_model(self):try:self.modelYOLO(yolo26n.pt)self.result_text.append(✅ YOLO26模型加载成功)exceptExceptionase:self.result_text.append(f❌ 模型加载失败:{e})defopen_image(self):path,_QFileDialog.getOpenFileName(self,选择图片,,Images (*.png *.jpg *.jpeg))ifpath:self.start_detect(path,image)defopen_folder(self):pathQFileDialog.getExistingDirectory(self,选择文件夹)ifpath:self.result_text.append(f批量检测文件夹:{path})defopen_video(self):path,_QFileDialog.getOpenFileName(self,选择视频,,Videos (*.mp4 *.avi))ifpath:self.start_detect(path,video)defopen_camera(self):self.start_detect(0,camera)defstart_detect(self,source,mode):self.stop_detect()self.workerDetectionWorker(self.model,source,mode,self.conf_spin.value(),self.iou_spin.value())self.worker.update_frame.connect(self.show_frame)self.worker.update_result.connect(self.result_text.append)self.worker.start()defstop_detect(self):ifhasattr(self,worker)andself.worker.isRunning():self.worker.stop()self.worker.wait()defshow_frame(self,img):self.img_label.setPixmap(QPixmap.fromImage(img).scaled(self.img_label.size(),Qt.KeepAspectRatio))classDetectionWorker(QThread):update_frameSignal(QImage)update_resultSignal(str)def__init__(self,model,source,mode,conf,iou):super().__init__()self.modelmodel self.sourcesource self.modemode self.confconf self.iouiou self.runningTruedefrun(self):ifself.modeimage:self.detect_image()else:self.detect_video()defdetect_image(self):imgcv2.imread(self.source)resultsself.model.predict(img,confself.conf,iouself.iou)self.show_result(results)defdetect_video(self):capcv2.VideoCapture(0ifself.modecameraelseself.source)whileself.runningandcap.isOpened():ret,framecap.read()ifnotret:breakresultsself.model.predict(frame,confself.conf,iouself.iou)self.show_result(results)cap.release()defshow_result(self,results):annotatedresults[0].plot()rgbcv2.cvtColor(annotated,cv2.COLOR_BGR2RGB)h,w,chrgb.shape q_imgQImage(rgb.data,w,h,ch*w,QImage.Format_RGB888)self.update_frame.emit(q_img)countlen(results[0].boxes)self.update_result.emit(f检测到目标:{count}个)if__name____main__:init_db()appQApplication(sys.argv)winLoginWindow()win.show()sys.exit(app.exec())2. 批量训练脚本train_mult.pyimportosfromultralyticsimportYOLOdefbatch_train(yaml_dir,epochs100,batch8):yaml_files[fforfinos.listdir(yaml_dir)iff.endswith(.yaml)]foryamlinyaml_files:yaml_pathos.path.join(yaml_dir,yaml)print(f开始训练:{yaml_path})modelYOLO(yolo26n.pt)model.train(datayaml_path,epochsepochs,batchbatch,imgsz640,device0,nameftrain_{os.path.splitext(yaml)[0]})if__name____main__:# 你的yaml配置文件所在目录batch_train(./data_yamls)3. 依赖文件requirements.txtultralytics8.3.0 PySide66.7.0 opencv-python4.9.0.80 numpy1.26.4 pillow10.2.0 sqlite3三、项目模块说明文件夹功能模块用途Attention/添加注意力机制提升模型对关键目标的关注度适合小目标检测Backbone/替换主干网络更换更高效的Backbone提升特征提取能力Block/替换C3K2模块优化基础卷积块提升模型效率Downsample/替换下采样模块改进下采样方式减少特征信息丢失Frequency/频域增强模块从频域角度增强特征提升模型鲁棒性Lightweight/轻量化改进模块剪枝、量化等操作减小模型体积MS/多尺度改进模块适配不同尺度目标提升多场景检测能力Neck/替换Neck网络优化特征融合方式提升检测精度Transformer/Transformer模块引入注意力机制提升全局特征建模能力Upsample/上采样改进优化上采样方式提升小目标检测效果四、运行步骤安装依赖pipinstall-rrequirements.txt下载YOLO26权重yolo26n.pt放到项目根目录运行登录版主程序python run_main_login.py批量训练python train_mult.py以上文字及代码仅供参考