使用Qt为MainWindow设置layout时报错

使用Qt为MainWindow设置layout时报错

代码:

MainWindow::MainWindow(QWidget *parent)
    : QMainWindow(parent)
{
    radiusLabel = new QLabel(this);
    radiusEdit = new QLineEdit(this);
    ansLabel = new QLabel(this);
    calcButton = new QPushButton(this);

    QGridLayout *layout = new QGridLayout(this);
    layout->addWidget(radiusLabel, 0, 0);
    layout->addWidget(radiusEdit, 0, 1);
    layout->addWidget(ansLabel, 1, 0);
    layout->addWidget(calcButton, 1, 1);

    setLayout(layout);
}

运行时只出现了一个控件且出现warning:
QLayout: Attempting to add QLayout “” to MainWindow “”, which already has a layout.
估计是MainWindow已经有默认的layout了,所以不能这么写。
换一种写法:

MainWindow::MainWindow(QWidget *parent)
    : QMainWindow(parent)
{
    mainWidget = new QWidget(this);
    this->setCentralWidget(mainWidget);

    radiusLabel = new QLabel(this);
    radiusEdit = new QLineEdit(this);
    ansLabel = new QLabel(this);
    calcButton = new QPushButton(this);

    QGridLayout *layout = new QGridLayout(this);
    layout->addWidget(radiusLabel, 0, 0);
    layout->addWidget(radiusEdit, 0, 1);
    layout->addWidget(ansLabel, 1, 0);
    layout->addWidget(calcButton, 1, 1);
    mainWidget->setLayout(layout);
}

这样就可以了。

# -*- coding: utf-8 -*- import sys import os import cv2 import numpy as np from PyQt5.QtWidgets import (QApplication, QMainWindow, QPushButton, QWidget, QVBoxLayout, QHBoxLayout, QMessageBox, QLabel, QFileDialog, QToolBar, QComboBox, QStatusBar, QGroupBox, QSlider, QDockWidget, QProgressDialog, QLineEdit, QRadioButton, QButtonGroup, QCheckBox,QSpinBox) from PyQt5.QtCore import QRect, Qt, QSettings, QThread, pyqtSignal from CamOperation_class import CameraOperation sys.path.append("D:\\海康\\MVS\\Development\\Samples\\Python\\BasicDemo") import ctypes from datetime import datetime from MvCameraControl_class import * from MvErrorDefine_const import * from CameraParams_header import * from PyUICBasicDemo import Ui_MainWindow import logging import platform import serial import socket import time from scipy import ndimage import skimage.measure from skimage.metrics import structural_similarity as compare_ssim import subprocess # 配置日志系统 logging.basicConfig( level=logging.DEBUG, # 设置为DEBUG级别获取更多信息 format='%(asctime)s - %(name)s - %(levelname)s - %(message)s', handlers=[ logging.FileHandler("cloth_inspection_debug.log"), logging.StreamHandler() ] ) logging.info("布料印花检测系统启动") # 全局变量 current_sample_path = "" # 当前使用的样本路径 detection_history = [] # 检测历史记录 isGrabbing = False # 相机取流状态 isOpen = False # 相机打开状态 obj_cam_operation = None # 相机操作对象 frame_monitor_thread = None # 帧监控线程 sensor_monitor_thread = None # 传感器监控线程 sensor_controller = None # 传感器控制器 # ==================== 传感器通讯模块 ==================== # 在 SensorController 类中添加新方法 class SensorController: # ... 现有代码 ... def wait_for_material(self, delay_seconds=0): """ 等待布料到达(模拟实现) :param delay_seconds: 延迟秒数 """ if not self.connected: logging.warning("未连接传感器,跳过等待") return False logging.info(f"等待布料到达,延迟 {delay_seconds} 秒") # 实际应用中应根据传感器信号判断布料是否到位 # 这里使用简单的间延迟模拟 start_time = time.time() while time.time() - start_time < delay_seconds: QThread.msleep(100) # 避免阻塞UI # 检查是否被取消 if not self.running: return False logging.info("布料已到位,准备拍摄") return True # 在 SensorMonitorThread 类中添加新方法 class SensorMonitorThread(QThread): # ... 现有代码 ... def wait_for_material(self, delay_seconds): """ 等待布料到达 """ return self.sensor_controller.wait_for_material(delay_seconds) # 修改 sensor_controlled_check 函数,添加延迟拍摄功能 def sensor_controlled_check(): """传感器控制的质量检测主流程""" # ... 前面的代码 ... # 新增:获取延迟设置 delay_seconds = mainWindow.ui.spinDelay.value() # 新增:等待布料到位 if sensor_controller and sensor_controller.connected and delay_seconds > 0: # 显示等待对话框 progress = QProgressDialog("等待布料到位...", "取消", 0, 100, mainWindow) progress.setWindowModality(Qt.WindowModal) progress.setValue(0) # 启动等待线程 def wait_thread(): start_time = time.time() while time.time() - start_time < delay_seconds: elapsed = time.time() - start_time progress.setValue(int((elapsed / delay_seconds) * 100)) QThread.msleep(100) if progress.wasCanceled(): return False return True # 使用线程避免阻塞UI from threading import Thread wait_result = [True] # 使用列表传递结果 thread = Thread(target=lambda: wait_result.append(wait_thread())) thread.start() # 等待线程完成 while thread.is_alive(): QApplication.processEvents() progress.close() if not wait_result[0]: logging.info("用户取消了等待") return # 执行图像捕获和检测 check_print_with_sensor(sensor_data) # ==================== 优化后的检测算法 ==================== def enhanced_check_print_quality(sample_image_path, test_image, threshold=0.05, sensor_data=None): """ 优化版布料印花检测算法,增加图像配准和特征匹配 :param sample_image_path: 合格样本图像路径 :param test_image: 测试图像 (numpy数组) :param threshold: 差异阈值 :param sensor_data: 传感器数据字典 :return: 是否合格,差异值,标记图像 """ # 根据传感器数据动态调整阈值 if sensor_data: # 速度越高,允许的差异阈值越大 speed_factor = min(1.0 + sensor_data['speed'] * 0.1, 1.5) # 温度/湿度影响 env_factor = 1.0 + abs(sensor_data['temperature'] - 25) * 0.01 + abs(sensor_data['humidity'] - 50) * 0.005 adjusted_threshold = threshold * speed_factor * env_factor logging.info(f"根据传感器数据调整阈值: 原始={threshold:.4f}, 调整后={adjusted_threshold:.4f}") else: adjusted_threshold = threshold try: # 读取样本图像 sample_img_data = np.fromfile(sample_image_path, dtype=np.uint8) sample_image = cv2.imdecode(sample_img_data, cv2.IMREAD_GRAYSCALE) if sample_image is None: logging.error(f"无法解码样本图像: {sample_image_path}") return None, None, None except Exception as e: logging.exception(f"样本图像读取异常: {str(e)}") return None, None, None # 确保测试图像是灰度图 if len(test_image.shape) == 3: test_image_gray = cv2.cvtColor(test_image, cv2.COLOR_BGR2GRAY) else: test_image_gray = test_image.copy() # 1. 图像预处理 sample_image = cv2.GaussianBlur(sample_image, (5, 5), 0) test_image_gray = cv2.GaussianBlur(test_image_gray, (5, 5), 0) # 2. 图像配准(解决位置偏移问题) try: # 使用ORB特征匹配进行图像配准 orb = cv2.ORB_create(nfeatures=200) keypoints1, descriptors1 = orb.detectAndCompute(sample_image, None) keypoints2, descriptors2 = orb.detectAndCompute(test_image_gray, None) if descriptors1 is None or descriptors2 is None: logging.warning("无法提取特征描述符,跳过配准") aligned_sample = sample_image else: # 使用BFMatcher进行特征匹配 bf = cv2.BFMatcher(cv2.NORM_HAMMING, crossCheck=True) matches = bf.match(descriptors1, descriptors2) matches = sorted(matches, key=lambda x: x.distance) if len(matches) > 10: # 提取匹配点的坐标 src_pts = np.float32([keypoints1[m.queryIdx].pt for m in matches]).reshape(-1, 1, 2) dst_pts = np.float32([keypoints2[m.trainIdx].pt for m in matches]).reshape(-1, 1, 2) # 计算单应性矩阵 H, mask = cv2.findHomography(src_pts, dst_pts, cv2.RANSAC, 5.0) if H is not None: # 应用变换 aligned_sample = cv2.warpPerspective( sample_image, H, (test_image_gray.shape[1], test_image_gray.shape[0]) ) logging.info("图像配准成功,使用配准后样本") else: aligned_sample = sample_image logging.warning("无法计算单应性矩阵,使用原始样本") else: aligned_sample = sample_image logging.warning("特征点匹配不足,跳过图像配准") except Exception as e: logging.error(f"图像配准失败: {str(e)}") aligned_sample = sample_image # 3. 确保图像大小一致 try: if aligned_sample.shape != test_image_gray.shape: test_image_gray = cv2.resize(test_image_gray, (aligned_sample.shape[1], aligned_sample.shape[0])) except Exception as e: logging.error(f"图像调整大小失败: {str(e)}") return None, None, None # 4. 计算结构相似性(SSIM)和差异 ssim_score, ssim_diff = skimage.measure.compare_ssim( aligned_sample, test_image_gray, full=True, gaussian_weights=True ) ssim_diff = (1 - ssim_diff) * 255 # 转换为0-255范围 # 5. 计算绝对差异 abs_diff = cv2.absdiff(aligned_sample, test_image_gray) # 6. 组合差异(SSIM差异对结构变化敏感,绝对差异对亮度变化敏感) combined_diff = cv2.addWeighted(ssim_diff.astype(np.uint8), 0.7, abs_diff, 0.3, 0) # 7. 二值化差异 _, thresholded = cv2.threshold(combined_diff, 30, 255, cv2.THRESH_BINARY) # 8. 形态学操作去除噪声 kernel = np.ones((3, 3), np.uint8) thresholded = cv2.morphologyEx(thresholded, cv2.MORPH_OPEN, kernel) thresholded = cv2.morphologyEx(thresholded, cv2.MORPH_CLOSE, kernel) # 9. 计算差异比例 diff_pixels = np.count_nonzero(thresholded) total_pixels = aligned_sample.size diff_ratio = diff_pixels / total_pixels # 10. 判断是否合格 is_qualified = diff_ratio <= adjusted_threshold # 11. 创建标记图像 marked_image = cv2.cvtColor(test_image_gray, cv2.COLOR_GRAY2BGR) marked_image[thresholded == 255] = [0, 0, 255] # 红色标记缺陷 # 12. 标记大面积缺陷区域 labels = skimage.measure.label(thresholded) properties = skimage.measure.regionprops(labels) for prop in properties: if prop.area > 50: # 只标记大于50像素的区域 y, x = prop.centroid cv2.putText(marked_image, f"Defect", (int(x), int(y)), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 255), 1) return is_qualified, diff_ratio, marked_image # ==================== 传感器控制的质量检测流程 ==================== # 修改 sensor_controlled_check 函数 def sensor_controlled_check(): """传感器控制的质量检测主流程""" global isGrabbing, obj_cam_operation, current_sample_path, detection_history, sensor_controller logging.info("质量检测启动") # 1. 检查传感器连接状态 sensor_data = None if sensor_controller and sensor_controller.connected: # 读取传感器数据 sensor_data = sensor_controller.read_data() if not sensor_data: QMessageBox.warning(mainWindow, "传感器警告", "无法读取传感器数据,将使用默认参数", QMessageBox.Ok) else: # 根据传感器数据调整生产参数 adjust_production_parameters(sensor_data) else: logging.info("未连接传感器,使用默认参数检测") # 2. 执行图像捕获和检测 check_print_with_sensor(sensor_data) # 布料印花检测函数(使用优化算法) def check_print_with_sensor(sensor_data=None): """ 使用优化算法检测布料印花是否合格 """ global isGrabbing, obj_cam_operation, current_sample_path, detection_history logging.info("检测印花质量按钮按下") # 1. 检查相机状态 if not isGrabbing: logging.warning("相机未取流") QMessageBox.warning(mainWindow, "错误", "请先开始取流并捕获图像!", QMessageBox.Ok) return # 2. 检查相机操作对象 if not obj_cam_operation: logging.error("相机操作对象未初始化") QMessageBox.warning(mainWindow, "错误", "相机未正确初始化!", QMessageBox.Ok) return # 3. 检查样本路径 if not current_sample_path or not os.path.exists(current_sample_path): logging.warning(f"无效样本路径: {current_sample_path}") QMessageBox.warning(mainWindow, "错误", "请先设置有效的标准样本图像!", QMessageBox.Ok) return # 使用进度对话框防止UI阻塞 progress = QProgressDialog("正在检测...", "取消", 0, 100, mainWindow) progress.setWindowModality(Qt.WindowModal) progress.setValue(10) try: # 4. 获取当前帧 logging.info("尝试获取当前帧") test_image = obj_cam_operation.get_current_frame() progress.setValue(30) if test_image is None: logging.warning("获取当前帧失败") QMessageBox.warning(mainWindow, "错误", "无法获取当前帧图像!", QMessageBox.Ok) return # 5. 获取差异度阈值 diff_threshold = mainWindow.ui.sliderDiffThreshold.value() / 100.0 logging.info(f"使用差异度阈值: {diff_threshold}") progress.setValue(50) # 6. 执行检测 is_qualified, diff_ratio, marked_image = enhanced_check_print_quality( current_sample_path, test_image, threshold=diff_threshold, sensor_data=sensor_data ) progress.setValue(70) # 检查返回结果是否有效 if is_qualified is None: logging.error("检测函数返回无效结果") QMessageBox.critical(mainWindow, "检测错误", "检测失败,请检查日志", QMessageBox.Ok) return logging.info(f"检测结果: 合格={is_qualified}, 差异={diff_ratio}") progress.setValue(90) # 7. 更新UI update_diff_display(diff_ratio, is_qualified) result_text = f"印花是否合格: {'合格' if is_qualified else '不合格'}\n差异占比: {diff_ratio*100:.2f}%\n阈值: {diff_threshold*100:.2f}%" QMessageBox.information(mainWindow, "检测结果", result_text, QMessageBox.Ok) if marked_image is not None: cv2.imshow("缺陷标记结果", marked_image) cv2.waitKey(0) cv2.destroyAllWindows() else: logging.warning("标记图像为空") # 8. 记录检测结果 detection_result = { 'timestamp': datetime.now(), 'qualified': is_qualified, 'diff_ratio': diff_ratio, 'threshold': diff_threshold, 'sensor_data': sensor_data if sensor_data else {} } detection_history.append(detection_result) update_history_display() progress.setValue(100) except Exception as e: logging.exception("印花检测失败") QMessageBox.critical(mainWindow, "检测错误", f"检测过程中发生错误: {str(e)}", QMessageBox.Ok) finally: progress.close() # 更新检测结果显示 def update_diff_display(diff_ratio, is_qualified): """ 更新差异度显示控件 """ # 更新当前差异度显示 mainWindow.ui.lblCurrentDiff.setText(f"当前差异度: {diff_ratio*100:.2f}%") # 根据合格状态设置颜色 if is_qualified: mainWindow.ui.lblDiffStatus.setText("状态: 合格") mainWindow.ui.lblDiffStatus.setStyleSheet("color: green; font-size: 12px;") else: mainWindow.ui.lblDiffStatus.setText("状态: 不合格") mainWindow.ui.lblDiffStatus.setStyleSheet("color: red; font-size: 12px;") # 更新差异度阈值显示 def update_diff_threshold(value): """ 当滑块值改变更新阈值显示 """ mainWindow.ui.lblDiffValue.setText(f"{value}%") # 保存标准样本函数 def save_sample_image(): global isGrabbing, obj_cam_operation, current_sample_path if not isGrabbing: QMessageBox.warning(mainWindow, "错误", "请先开始取流并捕获图像!", QMessageBox.Ok) return # 检查是否有有效图像 if not obj_cam_operation.is_frame_available(): QMessageBox.warning(mainWindow, "无有效图像", "未捕获到有效图像,请检查相机状态!", QMessageBox.Ok) return # 读取上次使用的路径 settings = QSettings("ClothInspection", "CameraApp") last_dir = settings.value("last_save_dir", os.path.join(os.getcwd(), "captures")) # 创建默认文件名 timestamp = datetime.now().strftime("%Y%m%d_%H%M%S") default_filename = f"sample_{timestamp}" # 弹出文件保存对话框 file_path, selected_filter = QFileDialog.getSaveFileName( mainWindow, "保存标准样本图像", os.path.join(last_dir, default_filename), "BMP Files (*.bmp);;PNG Files (*.png);;JPEG Files (*.jpg);;所有文件 (*)", options=QFileDialog.DontUseNativeDialog ) if not file_path: logging.info("用户取消了图像保存操作") return # 用户取消保存 # 处理文件扩展名 file_extension = os.path.splitext(file_path)[1].lower() if not file_extension: # 根据选择的过滤器添加扩展名 if "BMP" in selected_filter: file_path += ".bmp" elif "PNG" in selected_filter: file_path += ".png" elif "JPEG" in selected_filter or "JPG" in selected_filter: file_path += ".jpg" else: # 默认使用BMP格式 file_path += ".bmp" file_extension = os.path.splitext(file_path)[1].lower() # 根据扩展名设置保存格式 format_mapping = { ".bmp": "bmp", ".png": "png", ".jpg": "jpg", ".jpeg": "jpg" } save_format = format_mapping.get(file_extension) if not save_format: QMessageBox.warning(mainWindow, "错误", "不支持的文件格式!", QMessageBox.Ok) return # 确保目录存在 directory = os.path.dirname(file_path) if directory and not os.path.exists(directory): try: os.makedirs(directory, exist_ok=True) logging.info(f"创建目录: {directory}") except OSError as e: error_msg = f"无法创建目录 {directory}: {str(e)}" QMessageBox.critical(mainWindow, "目录创建错误", error_msg, QMessageBox.Ok) return # 保存当前帧作为标准样本 try: ret = obj_cam_operation.save_image(file_path, save_format) if ret != MV_OK: strError = f"保存样本图像失败: {hex(ret)}" QMessageBox.warning(mainWindow, "错误", strError, QMessageBox.Ok) else: success_msg = f"标准样本已保存至:\n{file_path}" QMessageBox.information(mainWindow, "成功", success_msg, QMessageBox.Ok) # 更新当前样本路径 current_sample_path = file_path update_sample_display() # 保存当前目录 settings.setValue("last_save_dir", os.path.dirname(file_path)) except Exception as e: error_msg = f"保存图像发生错误: {str(e)}" QMessageBox.critical(mainWindow, "异常错误", error_msg, QMessageBox.Ok) logging.exception("保存样本图像发生异常") # 预览当前样本 def preview_sample(): global current_sample_path if not current_sample_path or not os.path.exists(current_sample_path): QMessageBox.warning(mainWindow, "错误", "请先设置有效的标准样本图像!", QMessageBox.Ok) return try: # 使用安全方法读取图像 img_data = np.fromfile(current_sample_path, dtype=np.uint8) sample_img = cv2.imdecode(img_data, cv2.IMREAD_COLOR) if sample_img is None: raise Exception("无法加载图像") cv2.imshow("标准样本预览", sample_img) cv2.waitKey(0) cv2.destroyAllWindows() except Exception as e: QMessageBox.warning(mainWindow, "错误", f"预览样本失败: {str(e)}", QMessageBox.Ok) # 更新样本路径显示 def update_sample_display(): global current_sample_path if current_sample_path: mainWindow.ui.lblSamplePath.setText(f"当前样本: {os.path.basename(current_sample_path)}") mainWindow.ui.lblSamplePath.setToolTip(current_sample_path) mainWindow.ui.bnPreviewSample.setEnabled(True) else: mainWindow.ui.lblSamplePath.setText("当前样本:设置样本") mainWindow.ui.bnPreviewSample.setEnabled(False) # 更新历史记录显示 def update_history_display(): global detection_history mainWindow.ui.cbHistory.clear() for i, result in enumerate(detection_history[-10:]): # 显示最近10条记录 timestamp = result['timestamp'].strftime("%H:%M:%S") status = "合格" if result['qualified'] else "不合格" ratio = f"{result['diff_ratio']*100:.2f}%" mainWindow.ui.cbHistory.addItem(f"[{timestamp}] {status} - 差异: {ratio}") # 获取选取设备信息的索引,通过[]之间的字符去解析 def TxtWrapBy(start_str, end, all): start = all.find(start_str) if start >= 0: start += len(start_str) end = all.find(end, start) if end >= 0: return all[start:end].strip() # 将返回的错误码转换为十六进制显示 def ToHexStr(num): """将错误码转换为十六进制字符串""" # 处理非整数输入 if not isinstance(num, int): try: # 尝试转换为整数 num = int(num) except: # 无法转换返回类型信息 return f"<非整数:{type(num)}>" chaDic = {10: 'a', 11: 'b', 12: 'c', 13: 'd', 14: 'e', 15: 'f'} hexStr = "" # 处理负数 if num < 0: num = num + 2 ** 32 # 转换为十六进制 while num >= 16: digit = num % 16 hexStr = chaDic.get(digit, str(digit)) + hexStr num //= 16 hexStr = chaDic.get(num, str(num)) + hexStr return "0x" + hexStr # 绑定下拉列表至设备信息索引 def xFunc(event): global nSelCamIndex nSelCamIndex = TxtWrapBy("[", "]", mainWindow.ui.ComboDevices.get()) # Decoding Characters def decoding_char(c_ubyte_value): c_char_p_value = ctypes.cast(c_ubyte_value, ctypes.c_char_p) try: decode_str = c_char_p_value.value.decode('gbk') # Chinese characters except UnicodeDecodeError: decode_str = str(c_char_p_value.value) return decode_str # ch:枚举相机 | en:enum devices def enum_devices(): global deviceList global obj_cam_operation deviceList = MV_CC_DEVICE_INFO_LIST() n_layer_type = (MV_GIGE_DEVICE | MV_USB_DEVICE | MV_GENTL_CAMERALINK_DEVICE | MV_GENTL_CXP_DEVICE | MV_GENTL_XOF_DEVICE) ret = MvCamera.MV_CC_EnumDevices(n_layer_type, deviceList) if ret != 0: strError = "Enum devices fail! ret = :" + ToHexStr(ret) QMessageBox.warning(mainWindow, "Error", strError, QMessageBox.Ok) return ret if deviceList.nDeviceNum == 0: QMessageBox.warning(mainWindow, "Info", "Find no device", QMessageBox.Ok) return ret print("Find %d devices!" % deviceList.nDeviceNum) devList = [] for i in range(0, deviceList.nDeviceNum): mvcc_dev_info = cast(deviceList.pDeviceInfo[i], POINTER(MV_CC_DEVICE_INFO)).contents if mvcc_dev_info.nTLayerType == MV_GIGE_DEVICE or mvcc_dev_info.nTLayerType == MV_GENTL_GIGE_DEVICE: print("\ngige device: [%d]" % i) user_defined_name = decoding_char(mvcc_dev_info.SpecialInfo.stGigEInfo.chUserDefinedName) model_name = decoding_char(mvcc_dev_info.SpecialInfo.stGigEInfo.chModelName) print("device user define name: " + user_defined_name) print("device model name: " + model_name) nip1 = ((mvcc_dev_info.SpecialInfo.stGigEInfo.nCurrentIp & 0xff000000) >> 24) nip2 = ((mvcc_dev_info.SpecialInfo.stGigEInfo.nCurrentIp & 0x00ff0000) >> 16) nip3 = ((mvcc_dev_info.SpecialInfo.stGigEInfo.nCurrentIp & 0x0000ff00) >> 8) nip4 = (mvcc_dev_info.SpecialInfo.stGigEInfo.nCurrentIp & 0x000000ff) print("current ip: %d.%d.%d.%d " % (nip1, nip2, nip3, nip4)) devList.append( "[" + str(i) + "]GigE: " + user_defined_name + " " + model_name + "(" + str(nip1) + "." + str( nip2) + "." + str(nip3) + "." + str(nip4) + ")") elif mvcc_dev_info.nTLayerType == MV_USB_DEVICE: print("\nu3v device: [%d]" % i) user_defined_name = decoding_char(mvcc_dev_info.SpecialInfo.stUsb3VInfo.chUserDefinedName) model_name = decoding_char(mvcc_dev_info.SpecialInfo.stUsb3VInfo.chModelName) print("device user define name: " + user_defined_name) print("device model name: " + model_name) strSerialNumber = "" for per in mvcc_dev_info.SpecialInfo.stUsb3VInfo.chSerialNumber: if per == 0: break strSerialNumber = strSerialNumber + chr(per) print("user serial number: " + strSerialNumber) devList.append("[" + str(i) + "]USB: " + user_defined_name + " " + model_name + "(" + str(strSerialNumber) + ")") elif mvcc_dev_info.nTLayerType == MV_GENTL_CAMERALINK_DEVICE: print("\nCML device: [%d]" % i) user_defined_name = decoding_char(mvcc_dev_info.SpecialInfo.stCMLInfo.chUserDefinedName) model_name = decoding_char(mvcc_dev_info.SpecialInfo.stCMLInfo.chModelName) print("device user define name: " + user_defined_name) print("device model name: " + model_name) strSerialNumber = "" for per in mvcc_dev_info.SpecialInfo.stCMLInfo.chSerialNumber: if per == 0: break strSerialNumber = strSerialNumber + chr(per) print("user serial number: " + strSerialNumber) devList.append("[" + str(i) + "]CML: " + user_defined_name + " " + model_name + "(" + str(strSerialNumber) + ")") elif mvcc_dev_info.nTLayerType == MV_GENTL_CXP_DEVICE: print("\nCXP device: [%d]" % i) user_defined_name = decoding_char(mvcc_dev_info.SpecialInfo.stCXPInfo.chUserDefinedName) model_name = decoding_char(mvcc_dev_info.SpecialInfo.stCXPInfo.chModelName) print("device user define name: " + user_defined_name) print("device model name: " + model_name) strSerialNumber = "" for per in mvcc_dev_info.SpecialInfo.stCXPInfo.chSerialNumber: if per == 0: break strSerialNumber = strSerialNumber + chr(per) print("user serial number: "+strSerialNumber) devList.append("[" + str(i) + "]CXP: " + user_defined_name + " " + model_name + "(" + str(strSerialNumber) + ")") elif mvcc_dev_info.nTLayerType == MV_GENTL_XOF_DEVICE: print("\nXoF device: [%d]" % i) user_defined_name = decoding_char(mvcc_dev_info.SpecialInfo.stXoFInfo.chUserDefinedName) model_name = decoding_char(mvcc_dev_info.SpecialInfo.stXoFInfo.chModelName) print("device user define name: " + user_defined_name) print("device model name: " + model_name) strSerialNumber = "" for per in mvcc_dev_info.SpecialInfo.stXoFInfo.chSerialNumber: if per == 0: break strSerialNumber = strSerialNumber + chr(per) print("user serial number: " + strSerialNumber) devList.append("[" + str(i) + "]XoF: " + user_defined_name + " " + model_name + "(" + str(strSerialNumber) + ")") mainWindow.ui.ComboDevices.clear() mainWindow.ui.ComboDevices.addItems(devList) mainWindow.ui.ComboDevices.setCurrentIndex(0) class FrameMonitorThread(QThread): frame_status = pyqtSignal(str) def __init__(self, cam_operation): super().__init__() self.cam_operation = cam_operation self.running = True def run(self): while self.running: if self.cam_operation: status = self.cam_operation.get_frame_status() frame_text = "有帧" if status.get('current_frame', False) else "无帧" self.frame_status.emit(f"帧状态: {frame_text}") QThread.msleep(500) def stop(self): self.running = False # ch:打开相机 | en:open device def open_device(): global deviceList global nSelCamIndex global obj_cam_operation global isOpen global frame_monitor_thread global mainWindow if isOpen: QMessageBox.warning(mainWindow, "Error", 'Camera is Running!', QMessageBox.Ok) return MV_E_CALLORDER nSelCamIndex = mainWindow.ui.ComboDevices.currentIndex() if nSelCamIndex < 0: QMessageBox.warning(mainWindow, "Error", 'Please select a camera!', QMessageBox.Ok) return MV_E_CALLORDER # 创建 MvCamera 实例 cam = MvCamera() # 修复:使用 cam 而不是 obj_cam_operation obj_cam_operation = CameraOperation(cam, deviceList, nSelCamIndex) ret = obj_cam_operation.open_device() if 0 != ret: strError = "Open device failed ret:" + ToHexStr(ret) QMessageBox.warning(mainWindow, "Error", strError, QMessageBox.Ok) isOpen = False else: set_continue_mode() get_param() isOpen = True enable_controls() # 启动帧监控线程 frame_monitor_thread = FrameMonitorThread(obj_cam_operation) frame_monitor_thread.frame_status.connect(mainWindow.ui.statusBar.showMessage) frame_monitor_thread.start() # ch:开始取流 | en:Start grab image def start_grabbing(): global obj_cam_operation global isGrabbing ret = obj_cam_operation.start_grabbing(mainWindow.ui.widgetDisplay.winId()) if ret != 0: strError = "Start grabbing failed ret:" + ToHexStr(ret) QMessageBox.warning(mainWindow, "Error", strError, QMessageBox.Ok) else: isGrabbing = True enable_controls() # ch:停止取流 | en:Stop grab image def stop_grabbing(): global obj_cam_operation global isGrabbing ret = obj_cam_operation.Stop_grabbing() if ret != 0: strError = "Stop grabbing failed ret:" + ToHexStr(ret) QMessageBox.warning(mainWindow, "Error", strError, QMessageBox.Ok) else: isGrabbing = False enable_controls() # ch:关闭设备 | Close device def close_device(): global isOpen global isGrabbing global obj_cam_operation global frame_monitor_thread # 停止帧监控线程 if frame_monitor_thread and frame_monitor_thread.isRunning(): frame_monitor_thread.stop() frame_monitor_thread.wait(2000) if isOpen: obj_cam_operation.close_device() isOpen = False isGrabbing = False enable_controls() # ch:设置触发模式 | en:set trigger mode def set_continue_mode(): ret = obj_cam_operation.set_trigger_mode(False) if ret != 0: strError = "Set continue mode failed ret:" + ToHexStr(ret) QMessageBox.warning(mainWindow, "Error", strError, QMessageBox.Ok) else: mainWindow.ui.radioContinueMode.setChecked(True) mainWindow.ui.radioTriggerMode.setChecked(False) mainWindow.ui.bnSoftwareTrigger.setEnabled(False) # ch:设置软触发模式 | en:set software trigger mode def set_software_trigger_mode(): ret = obj_cam_operation.set_trigger_mode(True) if ret != 0: strError = "Set trigger mode failed ret:" + ToHexStr(ret) QMessageBox.warning(mainWindow, "Error", strError, QMessageBox.Ok) else: mainWindow.ui.radioContinueMode.setChecked(False) mainWindow.ui.radioTriggerMode.setChecked(True) mainWindow.ui.bnSoftwareTrigger.setEnabled(isGrabbing) # ch:设置触发命令 | en:set trigger software def trigger_once(): ret = obj_cam_operation.trigger_once() if ret != 0: strError = "TriggerSoftware failed ret:" + ToHexStr(ret) QMessageBox.warning(mainWindow, "Error", strError, QMessageBox.Ok) # 保存图像对话框 def save_image_dialog(): """ 打开保存图像对话框并保存当前帧 """ global isGrabbing, obj_cam_operation # 检查相机状态 if not isGrabbing: QMessageBox.warning(mainWindow, "相机未就绪", "请先开始取流并捕获图像!", QMessageBox.Ok) return # 检查是否有有效图像 if not obj_cam_operation.is_frame_available(): QMessageBox.warning(mainWindow, "无有效图像", "未捕获到有效图像,请检查相机状态!", QMessageBox.Ok) return # 读取上次使用的路径 settings = QSettings("ClothInspection", "CameraApp") last_dir = settings.value("last_save_dir", os.path.join(os.getcwd(), "captures")) # 创建默认文件名 timestamp = datetime.now().strftime("%Y%m%d_%H%M%S") default_filename = f"capture_{timestamp}" # 弹出文件保存对话框 file_path, selected_filter = QFileDialog.getSaveFileName( mainWindow, "保存图像", os.path.join(last_dir, default_filename), # 初始路径 "BMP 图像 (*.bmp);;JPEG 图像 (*.jpg);;PNG 图像 (*.png);;TIFF 图像 (*.tiff);;所有文件 (*)", options=QFileDialog.DontUseNativeDialog ) # 用户取消操作 if not file_path: logging.info("用户取消了图像保存操作") return # 处理文件扩展名 file_extension = os.path.splitext(file_path)[1].lower() if not file_extension: # 根据选择的过滤器添加扩展名 if "BMP" in selected_filter: file_path += ".bmp" elif "JPEG" in selected_filter or "JPG" in selected_filter: file_path += ".jpg" elif "PNG" in selected_filter: file_path += ".png" elif "TIFF" in selected_filter: file_path += ".tiff" else: # 默认使用BMP格式 file_path += ".bmp" # 确定保存格式 format_mapping = { ".bmp": "bmp", ".jpg": "jpg", ".jpeg": "jpg", ".png": "png", ".tiff": "tiff", ".tif": "tiff" } file_extension = os.path.splitext(file_path)[1].lower() save_format = format_mapping.get(file_extension, "bmp") # 确保目录存在 directory = os.path.dirname(file_path) if directory and not os.path.exists(directory): try: os.makedirs(directory, exist_ok=True) except OSError as e: QMessageBox.critical(mainWindow, "目录错误", f"无法创建目录:\n{str(e)}", QMessageBox.Ok) return # 保存图像 try: ret = obj_cam_operation.save_image(file_path, save_format) if ret == MV_OK: QMessageBox.information(mainWindow, "保存成功", f"图像已保存至:\n{file_path}", QMessageBox.Ok) logging.info(f"图像保存成功: {file_path}") # 保存当前目录 settings.setValue("last_save_dir", os.path.dirname(file_path)) else: error_msg = f"保存失败! 错误代码: {hex(ret)}" QMessageBox.warning(mainWindow, "保存失败", error_msg, QMessageBox.Ok) logging.error(f"图像保存失败: {file_path}, 错误代码: {hex(ret)}") except Exception as e: QMessageBox.critical(mainWindow, "保存错误", f"保存图像发生错误:\n{str(e)}", QMessageBox.Ok) logging.exception(f"保存图像发生异常: {file_path}") def is_float(str): try: float(str) return True except ValueError: return False # ch: 获取参数 | en:get param def get_param(): try: # 调用方法获取参数 ret = obj_cam_operation.get_parameters() # 记录调用结果(调试用) logging.debug(f"get_param() 返回: {ret} (类型: {type(ret)})") # 处理错误码 if ret != MV_OK: strError = "获取参数失败,错误码: " + ToHexStr(ret) QMessageBox.warning(mainWindow, "错误", strError, QMessageBox.Ok) else: # 成功获取参数后更新UI mainWindow.ui.edtExposureTime.setText("{0:.2f}".format(obj_cam_operation.exposure_time)) mainWindow.ui.edtGain.setText("{0:.2f}".format(obj_cam_operation.gain)) mainWindow.ui.edtFrameRate.setText("{0:.2f}".format(obj_cam_operation.frame_rate)) # 记录成功信息 logging.info("成功获取相机参数") except Exception as e: # 处理所有异常 error_msg = f"获取参数发生错误: {str(e)}" logging.error(error_msg) QMessageBox.critical(mainWindow, "严重错误", error_msg, QMessageBox.Ok) # ch: 设置参数 | en:set param def set_param(): frame_rate = mainWindow.ui.edtFrameRate.text() exposure = mainWindow.ui.edtExposureTime.text() gain = mainWindow.ui.edtGain.text() if not (is_float(frame_rate) and is_float(exposure) and is_float(gain)): strError = "设置参数失败: 参数必须是有效的浮点数" QMessageBox.warning(mainWindow, "错误", strError, QMessageBox.Ok) return MV_E_PARAMETER try: # 使用正确的参数顺序和关键字 ret = obj_cam_operation.set_param( frame_rate=float(frame_rate), exposure_time=float(exposure), gain=float(gain) ) if ret != MV_OK: strError = "设置参数失败,错误码: " + ToHexStr(ret) QMessageBox.warning(mainWindow, "错误", strError, QMessageBox.Ok) else: logging.info("参数设置成功") return MV_OK except Exception as e: error_msg = f"设置参数发生错误: {str(e)}" logging.error(error_msg) QMessageBox.critical(mainWindow, "严重错误", error_msg, QMessageBox.Ok) return MV_E_STATE # ch: 设置控件状态 | en:set enable status def enable_controls(): global isGrabbing global isOpen # 先设置group的状态,再单独设置各控件状态 mainWindow.ui.groupGrab.setEnabled(isOpen) mainWindow.ui.groupParam.setEnabled(isOpen) mainWindow.ui.bnOpen.setEnabled(not isOpen) mainWindow.ui.bnClose.setEnabled(isOpen) mainWindow.ui.bnStart.setEnabled(isOpen and (not isGrabbing)) mainWindow.ui.bnStop.setEnabled(isOpen and isGrabbing) mainWindow.ui.bnSoftwareTrigger.setEnabled(isGrabbing and mainWindow.ui.radioTriggerMode.isChecked()) mainWindow.ui.bnSaveImage.setEnabled(isOpen and isGrabbing) mainWindow.ui #添加检测按钮控制 mainWindow.ui.bnCheckPrint.setEnabled(isOpen and isGrabbing) mainWindow.ui.bnSaveSample.setEnabled(isOpen and isGrabbing) mainWindow.ui.bnPreviewSample.setEnabled(bool(current_sample_path)) class MainWindow(QMainWindow): def __init__(self): super().__init__() # 创建UI实例 self.ui = Ui_MainWindow() self.ui.setupUi(self) def closeEvent(self, event): """重写关闭事件,执行清理操作""" logging.info("主窗口关闭,执行清理...") # 关闭设备 close_device() # 断开传感器 disconnect_sensor() event.accept() if __name__ == "__main__": # 初始化UI app = QApplication(sys.argv) # 创建主窗口实例 mainWindow = MainWindow() # 扩大主窗口尺寸 mainWindow.resize(1200, 800) # 宽度1200,高度800 # 创建工具栏 toolbar = mainWindow.addToolBar("检测工具") # 添加检测按钮 mainWindow.ui.bnCheckPrint = QPushButton("检测印花质量") toolbar.addWidget(mainWindow.ui.bnCheckPrint) # 添加保存样本按钮 mainWindow.ui.bnSaveSample = QPushButton("保存标准样本") toolbar.addWidget(mainWindow.ui.bnSaveSample) # 添加预览样本按钮 mainWindow.ui.bnPreviewSample = QPushButton("预览样本") toolbar.addWidget(mainWindow.ui.bnPreviewSample) # 添加历史记录下拉框 mainWindow.ui.cbHistory = QComboBox() mainWindow.ui.cbHistory.setMinimumWidth(300) toolbar.addWidget(QLabel("历史记录:")) toolbar.addWidget(mainWindow.ui.cbHistory) # 添加当前样本显示标签 mainWindow.ui.lblSamplePath = QLabel("当前样本:设置样本") status_bar = mainWindow.statusBar() status_bar.addPermanentWidget(mainWindow.ui.lblSamplePath) # === 新增差异度调整控件 === # 创建右侧面板容器 right_panel = QWidget() right_layout = QVBoxLayout(right_panel) right_layout.setContentsMargins(10, 10, 10, 10) # 创建差异度调整组 diff_group = QGroupBox("差异度调整") diff_layout = QVBoxLayout(diff_group) # 差异度阈值控制 mainWindow.ui.lblDiffThreshold = QLabel("差异度阈值 (0-100%):") mainWindow.ui.sliderDiffThreshold = QSlider(Qt.Horizontal) mainWindow.ui.sliderDiffThreshold.setRange(0, 100) # 0-100% mainWindow.ui.sliderDiffThreshold.setValue(5) # 默认5% mainWindow.ui.lblDiffValue = QLabel("5%") # 当前差异度显示 mainWindow.ui.lblCurrentDiff = QLabel("当前差异度: -") mainWindow.ui.lblCurrentDiff.setStyleSheet("font-size: 14px; font-weight: bold;") # 差异度状态指示器 mainWindow.ui.lblDiffStatus = QLabel("状态: 未检测") mainWindow.ui.lblDiffStatus.setStyleSheet("font-size: 12px;") # 布局控件 diff_layout.addWidget(mainWindow.ui.lblDiffThreshold) diff_layout.addWidget(mainWindow.ui.sliderDiffThreshold) diff_layout.addWidget(mainWindow.ui.lblDiffValue) diff_layout.addWidget(mainWindow.ui.lblCurrentDiff) diff_layout.addWidget(mainWindow.ui.lblDiffStatus) # 添加差异度组到右侧布局 right_layout.addWidget(diff_group) # === 新增传感器控制面板 === sensor_panel = QGroupBox("传感器控制") sensor_layout = QVBoxLayout(sensor_panel) # 传感器类型选择 sensor_type_layout = QHBoxLayout() mainWindow.ui.lblSensorType = QLabel("传感器类型:") mainWindow.ui.cbSensorType = QComboBox() mainWindow.ui.cbSensorType.addItems(["串口", "以太网"]) sensor_type_layout.addWidget(mainWindow.ui.lblSensorType) sensor_type_layout.addWidget(mainWindow.ui.cbSensorType) # 串口参数 mainWindow.ui.serialGroup = QGroupBox("串口参数") serial_layout = QVBoxLayout(mainWindow.ui.serialGroup) mainWindow.ui.lblComPort = QLabel("端口:") mainWindow.ui.cbComPort = QComboBox() # 获取可用串口 (Windows) if platform.system() == 'Windows': ports = [f"COM{i}" for i in range(1, 21)] else: ports = [f"/dev/ttyS{i}" for i in range(0, 4)] + [f"/dev/ttyUSB{i}" for i in range(0, 4)] mainWindow.ui.cbComPort.addItems(ports) mainWindow.ui.lblBaudrate = QLabel("波特率:") mainWindow.ui.cbBaudrate = QComboBox() mainWindow.ui.cbBaudrate.addItems(["9600", "19200", "38400", "57600", "115200"]) mainWindow.ui.cbBaudrate.setCurrentText("115200") serial_layout.addWidget(mainWindow.ui.lblComPort) serial_layout.addWidget(mainWindow.ui.cbComPort) serial_layout.addWidget(mainWindow.ui.lblBaudrate) serial_layout.addWidget(mainWindow.ui.cbBaudrate) # 以太网参数 mainWindow.ui.ethernetGroup = QGroupBox("以太网参数") ethernet_layout = QVBoxLayout(mainWindow.ui.ethernetGroup) mainWindow.ui.lblIP = QLabel("IP地址:") mainWindow.ui.edtIP = QLineEdit("192.168.1.100") mainWindow.ui.lblPort = QLabel("端口:") mainWindow.ui.edtPort = QLineEdit("502") ethernet_layout.addWidget(mainWindow.ui.lblIP) ethernet_layout.addWidget(mainWindow.ui.edtIP) ethernet_layout.addWidget(mainWindow.ui.lblPort) ethernet_layout.addWidget(mainWindow.ui.edtPort) # 连接/断开按钮 mainWindow.ui.bnConnectSensor = QPushButton("连接传感器") mainWindow.ui.bnDisconnectSensor = QPushButton("断开传感器") mainWindow.ui.bnDisconnectSensor.setEnabled(False) # 传感器数据显示 mainWindow.ui.lblSensorData = QLabel("传感器数据: 未连接") mainWindow.ui.lblSensorData.setStyleSheet("font-size: 10pt;") # 添加到布局 sensor_layout.addLayout(sensor_type_layout) sensor_layout.addWidget(mainWindow.ui.serialGroup) sensor_layout.addWidget(mainWindow.ui.ethernetGroup) sensor_layout.addWidget(mainWindow.ui.bnConnectSensor) sensor_layout.addWidget(mainWindow.ui.bnDisconnectSensor) sensor_layout.addWidget(mainWindow.ui.lblSensorData) # 添加到右侧面板 right_layout.addWidget(sensor_panel) # 添加拉伸项使控件靠上 right_layout.addStretch(1) # 创建停靠窗口 dock = QDockWidget("检测控制面板", mainWindow) dock.setWidget(right_panel) dock.setFeatures(QDockWidget.DockWidgetMovable | QDockWidget.DockWidgetFloatable) mainWindow.addDockWidget(Qt.RightDockWidgetArea, dock) # === 差异度调整功能实现 === # 更新差异度阈值显示 def update_diff_threshold(value): mainWindow.ui.lblDiffValue.setText(f"{value}%") # 连接滑块信号 mainWindow.ui.sliderDiffThreshold.valueChanged.connect(update_diff_threshold) # 更新检测结果显示 def update_diff_display(diff_ratio, is_qualified): # 更新当前差异度显示 mainWindow.ui.lblCurrentDiff.setText(f"当前差异度: {diff_ratio*100:.2f}%") # 根据合格状态设置颜色 if is_qualified: mainWindow.ui.lblDiffStatus.setText("状态: 合格") mainWindow.ui.lblDiffStatus.setStyleSheet("color: green; font-size: 12px;") else: mainWindow.ui.lblDiffStatus.setText("状态: 不合格") mainWindow.ui.lblDiffStatus.setStyleSheet("color: red; font-size: 12px;") # 绑定按钮事件 mainWindow.ui.bnCheckPrint.clicked.connect(sensor_controlled_check) mainWindow.ui.bnSaveSample.clicked.connect(save_sample_image) mainWindow.ui.bnPreviewSample.clicked.connect(preview_sample) # 传感器类型切换 def update_sensor_ui(index): mainWindow.ui.serialGroup.setVisible(index == 0) mainWindow.ui.ethernetGroup.setVisible(index == 1) mainWindow.ui.cbSensorType.currentIndexChanged.connect(update_sensor_ui) update_sensor_ui(0) # 初始显示串口 # 传感器连接 def connect_sensor(): global sensor_monitor_thread, sensor_controller sensor_type = mainWindow.ui.cbSensorType.currentText() if sensor_controller is None: sensor_controller = SensorController() if sensor_type == "串口": config = { 'type': 'serial', 'port': mainWindow.ui.cbComPort.currentText(), 'baudrate': int(mainWindow.ui.cbBaudrate.currentText()), 'timeout': 1.0 } else: # 以太网 config = { 'type': 'ethernet', 'ip': mainWindow.ui.edtIP.text(), 'port': int(mainWindow.ui.edtPort.text()), 'timeout': 1.0 } if sensor_controller.connect(config): mainWindow.ui.bnConnectSensor.setEnabled(False) mainWindow.ui.bnDisconnectSensor.setEnabled(True) # 启动传感器数据监控线程 sensor_monitor_thread = SensorMonitorThread(sensor_controller) sensor_monitor_thread.data_updated.connect(update_sensor_display) sensor_monitor_thread.start() # 传感器断开 def disconnect_sensor(): global sensor_monitor_thread if sensor_controller: sensor_controller.disconnect() mainWindow.ui.bnConnectSensor.setEnabled(True) mainWindow.ui.bnDisconnectSensor.setEnabled(False) if sensor_monitor_thread and sensor_monitor_thread.isRunning(): sensor_monitor_thread.stop() sensor_monitor_thread.wait(2000) sensor_monitor_thread = None mainWindow.ui.lblSensorData.setText("传感器数据: 未连接") mainWindow.ui.bnConnectSensor.clicked.connect(connect_sensor) mainWindow.ui.bnDisconnectSensor.clicked.connect(disconnect_sensor) # === 新增延迟拍摄设置 === delay_layout = QHBoxLayout() mainWindow.ui.lblDelay = QLabel("触发延迟(秒):") mainWindow.ui.spinDelay = QSpinBox() mainWindow.ui.spinDelay.setRange(0, 60) # 0-60秒 mainWindow.ui.spinDelay.setValue(0) # 默认无延迟 mainWindow.ui.spinDelay.setToolTip("传感器检测到布料后延迟拍摄的间") delay_layout.addWidget(mainWindow.ui.lblDelay) delay_layout.addWidget(mainWindow.ui.spinDelay) # 添加到传感器布局中 sensor_layout.addLayout(delay_layout) def update_sensor_display(data): text = (f"张力: {data['tension']:.2f}N | " f"速度: {data['speed']:.2f}m/s | " f"温度: {data['temperature']:.1f}°C | " f"湿度: {data['humidity']:.1f}%") mainWindow.ui.lblSensorData.setText(text) # 绑定其他按钮事件 mainWindow.ui.bnEnum.clicked.connect(enum_devices) mainWindow.ui.bnOpen.clicked.connect(open_device) mainWindow.ui.bnClose.clicked.connect(close_device) mainWindow.ui.bnStart.clicked.connect(start_grabbing) mainWindow.ui.bnStop.clicked.connect(stop_grabbing) mainWindow.ui.bnSoftwareTrigger.clicked.connect(trigger_once) mainWindow.ui.radioTriggerMode.clicked.connect(set_software_trigger_mode) mainWindow.ui.radioContinueMode.clicked.connect(set_continue_mode) mainWindow.ui.bnGetParam.clicked.connect(get_param) mainWindow.ui.bnSetParam.clicked.connect(set_param) # 修改保存图像按钮连接 mainWindow.ui.bnSaveImage.clicked.connect(save_image_dialog) # 显示主窗口 mainWindow.show() # 执行应用 app.exec_() # 关闭设备 close_device() # 断开传感器 disconnect_sensor() sys.exit() 将你刚刚提出的解决方案放入这个代码里
07-10
如何将下面的程序打包成exe文件同尽量不要动下面程序的代码 # -*- coding: utf-8 -*- import sys import os import cv2 import numpy as np import time from PyQt5.QtWidgets import ( QApplication, QMainWindow, QPushButton, QWidget, QVBoxLayout, QHBoxLayout, QMessageBox, QLabel, QFileDialog, QToolBar, QComboBox, QStatusBar, QGroupBox, QSlider, QDockWidget, QProgressDialog, QLineEdit, QRadioButton, QGridLayout, QSpinBox ) from PyQt5.QtCore import QRect, Qt, QSettings, QThread, pyqtSignal from CamOperation_class import CameraOperation #sys.path.append("D:\\海康\\MVS\\Development\\Samples\\Python\\wanzheng.py") import ctypes from ctypes import cast, POINTER from datetime import datetime import logging import socket import serial import skimage import platform from CameraConstants import * import threading import time class ManagedThread(threading.Thread): def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self._stop_event = threading.Event() # 设置为非守护线程 self.daemon = False def stop(self): """安全停止线程""" self._stop_event.set() def should_stop(self): """检查是否应该停止""" return self._stop_event.is_set() def worker(): """线程工作函数""" try: while not threading.current_thread().should_stop(): # 模拟工作 time.sleep(1) # 安全输出 sys.stdout.write("Working...\n") except Exception as e: # 避免在关闭使用stderr pass def main(): # 创建并启动线程 threads = [] for _ in range(3): t = ManagedThread(target=worker) t.start() threads.append(t) try: # 主程序逻辑 time.sleep(5) finally: # 安全停止所有线程 for t in threads: t.stop() for t in threads: t.join(timeout=2.0) # 设置避免无限等待 # 确保所有输出完成 sys.stdout.flush() sys.stderr.flush() # 在导入部分添加 from CameraParams_header import ( MV_GIGE_DEVICE, MV_USB_DEVICE, MV_GENTL_CAMERALINK_DEVICE, MV_GENTL_CXP_DEVICE, MV_GENTL_XOF_DEVICE ) # 获取当前文件所在目录 current_dir = os.path.dirname(os.path.abspath(__file__)) # ===== 路径修复 ===== sdk_path = os.path.join(current_dir, "MvImport") if sdk_path not in sys.path: sys.path.append(sdk_path) def fix_sdk_path(): """修复海康SDK的加载路径""" if getattr(sys, 'frozen', False): # 打包模式 base_path = sys._MEIPASS # 添加DLL目录到系统路径 dll_path = os.path.join(base_path, "dlls") os.environ['PATH'] = dll_path + os.pathsep + os.environ['PATH'] try: # 直接加载DLL ctypes.WinDLL(os.path.join(dll_path, "MvCamCtrldll.dll")) ctypes.WinDLL(os.path.join(dll_path, "MvCameraControl.dll")) except OSError as e: logging.error(f"核心DLL加载失败: {e}") sys.exit(1) else: # 开发模式 # 确保SDK路径存在 if sdk_path not in sys.path: sys.path.append(sdk_path) # 添加DLL到系统路径 dll_dir = r"D:\海康\MVS\Runtime\Win64" if dll_dir not in os.environ['PATH']: os.environ['PATH'] = dll_dir + os.pathsep + os.environ['PATH'] # 立即执行路径修复 fix_sdk_path() # ===== 正确导入SDK模块 ===== try: from MvImport.MvCameraControl_class import MvCamera print("成功导入MvCamera类") from CameraParams_header import * from MvErrorDefine_const import * except ImportError as e: print(f"SDK导入失败: {e}") sys.exit(1) # 配置日志系统 logging.basicConfig( level=logging.DEBUG, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s', handlers=[ logging.FileHandler("cloth_inspection_debug.log"), logging.StreamHandler() ] ) logging.info("布料印花检测系统启动") # 全局变量 current_sample_path = "" detection_history = [] isGrabbing = False isOpen = False obj_cam_operation = None frame_monitor_thread = None sensor_monitor_thread = None sensor_controller = None MV_OK = 0 MV_E_CALLORDER = -2147483647 # ==================== 传感器通讯模块 ==================== class SensorController: def __init__(self): self.connected = False self.running = False self.connection = None def connect(self, config): try: if config['type'] == 'serial': self.connection = serial.Serial( port=config['port'], baudrate=config['baudrate'], timeout=config.get('timeout', 1.0) ) else: self.connection = socket.socket(socket.AF_INET, socket.SOCK_STREAM) self.connection.connect((config['ip'], config['port'])) self.connection.settimeout(config.get('timeout', 1.0)) self.connected = True self.running = True logging.info(f"传感器连接成功: {config}") return True except Exception as e: logging.error(f"传感器连接失败: {str(e)}") return False def disconnect(self): if self.connection: try: self.connection.close() except: pass self.connection = None self.connected = False self.running = False logging.info("传感器已断开") def read_data(self): if not self.connected: return None return { 'tension': np.random.uniform(10.0, 20.0), 'speed': np.random.uniform(1.0, 5.0), 'temperature': np.random.uniform(20.0, 30.0), 'humidity': np.random.uniform(40.0, 60.0) } def wait_for_material(self, delay_seconds=0): if not self.connected: logging.warning("未连接传感器,跳过等待") return False logging.info(f"等待布料到达,延迟 {delay_seconds} 秒") start_time = time.time() while time.time() - start_time < delay_seconds: QThread.msleep(100) if not self.running: return False logging.info("布料已到位,准备拍摄") return True class SensorMonitorThread(QThread): data_updated = pyqtSignal(dict) def __init__(self, sensor_controller): super().__init__() self.sensor_controller = sensor_controller self.running = True def run(self): while self.running: if self.sensor_controller and self.sensor_controller.connected: try: data = self.sensor_controller.read_data() if data: self.data_updated.emit(data) except Exception as e: logging.error(f"传感器数据读取错误: {str(e)}") QThread.msleep(500) def stop(self): self.running = False self.wait(2000) def wait_for_material(self, delay_seconds): return self.sensor_controller.wait_for_material(delay_seconds) # ==================== 相机帧监控线程 ==================== class FrameMonitorThread(QThread): frame_status = pyqtSignal(str) # 用于发送状态消息的信号 def __init__(self, cam_operation): super().__init__() self.cam_operation = cam_operation self.running = True self.frame_count = 0 self.last_time = time.time() def run(self): """监控相机帧状态的主循环""" while self.running: try: if self.cam_operation and self.cam_operation.is_grabbing: # 获取帧统计信息 frame_info = self.get_frame_info() if frame_info: fps = frame_info.get('fps', 0) dropped = frame_info.get('dropped', 0) status = f"FPS: {fps:.1f} | 丢帧: {dropped}" self.frame_status.emit(status) else: self.frame_status.emit("取流中...") else: self.frame_status.emit("相机未取流") except Exception as e: self.frame_status.emit(f"监控错误: {str(e)}") # 每500ms检查一次 QThread.msleep(500) def stop(self): """停止监控线程""" self.running = False self.wait(1000) # 等待线程结束 def calculate_fps(self): """计算当前帧率""" current_time = time.time() elapsed = current_time - self.last_time if elapsed > 0: fps = self.frame_count / elapsed self.frame_count = 0 self.last_time = current_time return fps return 0 def get_frame_info(self): """获取帧信息""" try: # 更新帧计数 self.frame_count += 1 # 返回帧信息 return { 'fps': self.calculate_fps(), 'dropped': 0 # 实际应用中需要从相机获取真实丢帧数 } except Exception as e: logging.error(f"获取帧信息失败: {str(e)}") return None # ==================== 优化后的检测算法 ==================== def enhanced_check_print_quality(sample_image_path, test_image, threshold=0.05, sensor_data=None): if sensor_data: speed_factor = min(1.0 + sensor_data['speed'] * 0.1, 1.5) env_factor = 1.0 + abs(sensor_data['temperature'] - 25) * 0.01 + abs(sensor_data['humidity'] - 50) * 0.005 adjusted_threshold = threshold * speed_factor * env_factor logging.info(f"根据传感器数据调整阈值: 原始={threshold:.4f}, 调整后={adjusted_threshold:.4f}") else: adjusted_threshold = threshold try: sample_img_data = np.fromfile(sample_image_path, dtype=np.uint8) sample_image = cv2.imdecode(sample_img_data, cv2.IMREAD_GRAYSCALE) if sample_image is None: logging.error(f"无法解码样本图像: {sample_image_path}") return None, None, None except Exception as e: logging.exception(f"样本图像读取异常: {str(e)}") return None, None, None if len(test_image.shape) == 3: test_image_gray = cv2.cvtColor(test_image, cv2.COLOR_BGR2GRAY) else: test_image_gray = test_image.copy() sample_image = cv2.GaussianBlur(sample_image, (5, 5), 0) test_image_gray = cv2.GaussianBlur(test_image_gray, (5, 5), 0) try: orb = cv2.ORB_create(nfeatures=200) keypoints1, descriptors1 = orb.detectAndCompute(sample_image, None) keypoints2, descriptors2 = orb.detectAndCompute(test_image_gray, None) if descriptors1 is None or descriptors2 is None: logging.warning("无法提取特征描述符,跳过配准") aligned_sample = sample_image else: bf = cv2.BFMatcher(cv2.NORM_HAMMING, crossCheck=True) matches = bf.match(descriptors1, descriptors2) matches = sorted(matches, key=lambda x: x.distance) if len(matches) > 10: src_pts = np.float32([keypoints1[m.queryIdx].pt for m in matches]).reshape(-1, 1, 2) dst_pts = np.float32([keypoints2[m.trainIdx].pt for m in matches]).reshape(-1, 1, 2) H, mask = cv2.findHomography(src_pts, dst_pts, cv2.RANSAC, 5.0) if H is not None: aligned_sample = cv2.warpPerspective( sample_image, H, (test_image_gray.shape[1], test_image_gray.shape[0]) ) logging.info("图像配准成功,使用配准后样本") else: aligned_sample = sample_image logging.warning("无法计算单应性矩阵,使用原始样本") else: aligned_sample = sample_image logging.warning("特征点匹配不足,跳过图像配准") except Exception as e: logging.error(f"图像配准失败: {str(e)}") aligned_sample = sample_image try: if aligned_sample.shape != test_image_gray.shape: test_image_gray = cv2.resize(test_image_gray, (aligned_sample.shape[1], aligned_sample.shape[0])) except Exception as e: logging.error(f"图像调整大小失败: {str(e)}") return None, None, None try: from skimage.metrics import structural_similarity as compare_ssim ssim_score, ssim_diff = compare_ssim( aligned_sample, test_image_gray, full=True, gaussian_weights=True, data_range=255 ) except ImportError: from skimage.measure import compare_ssim ssim_score, ssim_diff = compare_ssim( aligned_sample, test_image_gray, full=True, gaussian_weights=True ) except Exception as e: logging.error(f"SSIM计算失败: {str(e)}") abs_diff = cv2.absdiff(aligned_sample, test_image_gray) ssim_diff = abs_diff.astype(np.float32) / 255.0 ssim_score = 1.0 - np.mean(ssim_diff) ssim_diff = (1 - ssim_diff) * 255 abs_diff = cv2.absdiff(aligned_sample, test_image_gray) combined_diff = cv2.addWeighted(ssim_diff.astype(np.uint8), 0.7, abs_diff, 0.3, 0) _, thresholded = cv2.threshold(combined_diff, 30, 255, cv2.THRESH_BINARY) kernel = np.ones((3, 3), np.uint8) thresholded = cv2.morphologyEx(thresholded, cv2.MORPH_OPEN, kernel) thresholded = cv2.morphologyEx(thresholded, cv2.MORPH_CLOSE, kernel) diff_pixels = np.count_nonzero(thresholded) total_pixels = aligned_sample.size diff_ratio = diff_pixels / total_pixels is_qualified = diff_ratio <= adjusted_threshold marked_image = cv2.cvtColor(test_image_gray, cv2.COLOR_GRAY2BGR) marked_image[thresholded == 255] = [0, 0, 255] labels = skimage.measure.label(thresholded) properties = skimage.measure.regionprops(labels) for prop in properties: if prop.area > 50: y, x = prop.centroid cv2.putText(marked_image, f"Defect", (int(x), int(y)), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 255), 1) return is_qualified, diff_ratio, marked_image # ==================== 传感器控制的质量检测流程 ==================== def sensor_controlled_check(): global isGrabbing, obj_cam_operation, current_sample_path, detection_history, sensor_controller logging.info("质量检测启动") sensor_data = None if sensor_controller and sensor_controller.connected: sensor_data = sensor_controller.read_data() if not sensor_data: QMessageBox.warning(mainWindow, "传感器警告", "无法读取传感器数据,将使用默认参数", QMessageBox.Ok) else: logging.info("未连接传感器,使用默认参数检测") check_print_with_sensor(sensor_data) def check_print_with_sensor(sensor_data=None): global isGrabbing, obj_cam_operation, current_sample_path, detection_history logging.info("检测印花质量按钮按下") if not isGrabbing: QMessageBox.warning(mainWindow, "错误", "请先开始取流并捕获图像!", QMessageBox.Ok) return if not obj_cam_operation: QMessageBox.warning(mainWindow, "错误", "相机未正确初始化!", QMessageBox.Ok) return if not current_sample_path or not os.path.exists(current_sample_path): QMessageBox.warning(mainWindow, "错误", "请先设置有效的标准样本图像!", QMessageBox.Ok) return progress = QProgressDialog("正在检测...", "取消", 0, 100, mainWindow) progress.setWindowModality(Qt.WindowModal) progress.setValue(10) try: test_image = obj_cam_operation.get_current_frame() progress.setValue(30) if test_image is None: QMessageBox.warning(mainWindow, "错误", "无法获取当前帧图像!", QMessageBox.Ok) return diff_threshold = mainWindow.sliderDiffThreshold.value() / 100.0 logging.info(f"使用差异度阈值: {diff_threshold}") progress.setValue(50) is_qualified, diff_ratio, marked_image = enhanced_check_print_quality( current_sample_path, test_image, threshold=diff_threshold, sensor_data=sensor_data ) progress.setValue(70) if is_qualified is None: QMessageBox.critical(mainWindow, "检测错误", "检测失败,请检查日志", QMessageBox.Ok) return logging.info(f"检测结果: 合格={is_qualified}, 差异={diff_ratio}") progress.setValue(90) update_diff_display(diff_ratio, is_qualified) result_text = f"印花是否合格: {'合格' if is_qualified else '不合格'}\n差异占比: {diff_ratio*100:.2f}%\n阈值: {diff_threshold*100:.2f}%" QMessageBox.information(mainWindow, "检测结果", result_text, QMessageBox.Ok) if marked_image is not None: cv2.imshow("缺陷标记结果", marked_image) cv2.waitKey(0) cv2.destroyAllWindows() detection_result = { 'timestamp': datetime.now(), 'qualified': is_qualified, 'diff_ratio': diff_ratio, 'threshold': diff_threshold, 'sensor_data': sensor_data if sensor_data else {} } detection_history.append(detection_result) update_history_display() progress.setValue(100) except Exception as e: logging.exception("印花检测失败") QMessageBox.critical(mainWindow, "检测错误", f"检测过程中发生错误: {str(e)}", QMessageBox.Ok) finally: progress.close() def update_diff_display(diff_ratio, is_qualified): mainWindow.lblCurrentDiff.setText(f"当前差异度: {diff_ratio*100:.2f}%") if is_qualified: mainWindow.lblDiffStatus.setText("状态: 合格") mainWindow.lblDiffStatus.setStyleSheet("color: green; font-size: 12px;") else: mainWindow.lblDiffStatus.setText("状态: 不合格") mainWindow.lblDiffStatus.setStyleSheet("color: red; font-size: 12px;") def update_diff_threshold(value): mainWindow.lblDiffValue.setText(f"{value}%") def save_sample_image(): global isGrabbing, obj_cam_operation, current_sample_path if not isGrabbing: QMessageBox.warning(mainWindow, "错误", "请先开始取流并捕获图像!", QMessageBox.Ok) return # 检查是否有可用帧 if not obj_cam_operation.is_frame_available(): QMessageBox.warning(mainWindow, "无有效图像", "未捕获到有效图像,请检查相机状态!", QMessageBox.Ok) return settings = QSettings("ClothInspection", "CameraApp") last_dir = settings.value("last_save_dir", os.path.join(os.getcwd(), "captures")) timestamp = datetime.now().strftime("%Y%m%d_%H%M%S") default_filename = f"sample_{timestamp}" file_path, selected_filter = QFileDialog.getSaveFileName( mainWindow, "保存标准样本图像", os.path.join(last_dir, default_filename), "BMP Files (*.bmp);;PNG Files (*.png);;JPEG Files (*.jpg);;所有文件 (*)", options=QFileDialog.DontUseNativeDialog ) if not file_path: return file_extension = os.path.splitext(file_path)[1].lower() if not file_extension: if "BMP" in selected_filter: file_path += ".bmp" elif "PNG" in selected_filter: file_path += ".png" elif "JPEG" in selected_filter or "JPG" in selected_filter: file_path += ".jpg" else: file_path += ".bmp" file_extension = os.path.splitext(file_path)[1].lower() format_mapping = {".bmp": "bmp", ".png": "png", ".jpg": "jpg", ".jpeg": "jpg"} save_format = format_mapping.get(file_extension) if not save_format: QMessageBox.warning(mainWindow, "错误", "不支持的文件格式!", QMessageBox.Ok) return directory = os.path.dirname(file_path) if directory and not os.path.exists(directory): try: os.makedirs(directory, exist_ok=True) except OSError as e: QMessageBox.critical(mainWindow, "目录创建错误", f"无法创建目录 {directory}: {str(e)}", QMessageBox.Ok) return try: ret = obj_cam_operation.save_image(file_path, save_format) if ret != MV_OK: strError = f"保存样本图像失败: {hex(ret)}" QMessageBox.warning(mainWindow, "错误", strError, QMessageBox.Ok) else: QMessageBox.information(mainWindow, "成功", f"标准样本已保存至:\n{file_path}", QMessageBox.Ok) current_sample_path = file_path update_sample_display() settings.setValue("last_save_dir", os.path.dirname(file_path)) except Exception as e: QMessageBox.critical(mainWindow, "异常错误", f"保存图像发生错误: {str(e)}", QMessageBox.Ok) def preview_sample(): global current_sample_path if not current_sample_path or not os.path.exists(current_sample_path): QMessageBox.warning(mainWindow, "错误", "请先设置有效的标准样本图像!", QMessageBox.Ok) return try: img_data = np.fromfile(current_sample_path, dtype=np.uint8) sample_img = cv2.imdecode(img_data, cv2.IMREAD_COLOR) if sample_img is None: raise Exception("无法加载图像") cv2.imshow("标准样本预览", sample_img) cv2.waitKey(0) cv2.destroyAllWindows() except Exception as e: QMessageBox.warning(mainWindow, "错误", f"预览样本失败: {str(e)}", QMessageBox.Ok) def update_sample_display(): global current_sample_path if current_sample_path: mainWindow.lblSamplePath.setText(f"当前样本: {os.path.basename(current_sample_path)}") mainWindow.lblSamplePath.setToolTip(current_sample_path) mainWindow.bnPreviewSample.setEnabled(True) else: mainWindow.lblSamplePath.setText("当前样本:设置样本") mainWindow.bnPreviewSample.setEnabled(False) def update_history_display(): global detection_history mainWindow.cbHistory.clear() for i, result in enumerate(detection_history[-10:]): timestamp = result['timestamp'].strftime("%H:%M:%S") status = "合格" if result['qualified'] else "不合格" ratio = f"{result['diff_ratio']*100:.2f}%" mainWindow.cbHistory.addItem(f"[极客{timestamp}] {status} - 差异: {ratio}") def TxtWrapBy(start_str, end, all): start = all.find(start_str) if start >= 0: start += len(start_str) end = all.find(end, start) if end >= 0: return all[start:end].strip() def ToHexStr(num): if not isinstance(num, int): try: num = int(num) except: return f"<非整数:{type(num)}>" chaDic = {10: 'a', 11: 'b', 12: 'c', 13: 'd', 14: 'e', 15: 'f'} hexStr = "" if num < 0: num = num + 2 ** 32 while num >= 16: digit = num % 16 hexStr = chaDic.get(digit, str(digit)) + hexStr num //= 16 hexStr = chaDic.get(num, str(num)) + hexStr return "0x" + hexStr def decoding_char(c_ubyte_value): c_char_p_value = ctypes.cast(c_ubyte_value, ctypes.c_char_p) try: decode_str = c_char_p_value.value.decode('gbk') except UnicodeDecodeError: decode_str = str(c_char_p_value.value) return decode_str def enum_devices(): global deviceList, obj_cam_operation n_layer_type = ( MV_GIGE_DEVICE | MV_USB_DEVICE | MV_GENTL_CAMERALINK_DEVICE | MV_GENTL_CXP_DEVICE | MV_GENTL_XOF_DEVICE ) # 创建设备列表 deviceList = MV_CC_DEVICE_INFO_LIST() # 枚举设备 ret = MvCamera.MV_CC_EnumDevices(n_layer_type, deviceList) if ret != MV_OK: error_msg = f"枚举设备失败! 错误码: 0x{ret:x}" logging.error(error_msg) QMessageBox.warning(mainWindow, "错误", error_msg, QMessageBox.Ok) return ret if deviceList.nDeviceNum == 0: QMessageBox.warning(mainWindow, "提示", "未找到任何设备", QMessageBox.Ok) return MV_OK logging.info(f"找到 {deviceList.nDeviceNum} 个设备") # 处理设备信息 devList = [] for i in range(deviceList.nDeviceNum): # 获取设备信息 mvcc_dev_info = ctypes.cast( deviceList.pDeviceInfo[i], ctypes.POINTER(MV_CC_DEVICE_INFO) ).contents # 根据设备类型提取信息 if mvcc_dev_info.nTLayerType == MV_GIGE_DEVICE: st_gige_info = mvcc_dev_info.SpecialInfo.stGigEInfo ip_addr = ( f"{(st_gige_info.nCurrentIp >> 24) & 0xFF}." f"{(st_gige_info.nCurrentIp >> 16) & 0xFF}." f"{(st_gige_info.nCurrentIp >> 8) & 0xFF}." f"{st_gige_info.nCurrentIp & 0xFF}" ) dev_name = f"GigE: {st_gige_info.chUserDefinedName.decode('gbk', 'ignore')}" devList.append(f"[{i}] {dev_name} ({ip_addr})") elif mvcc_dev_info.nTLayerType == MV_USB_DEVICE: st_usb_info = mvcc_dev_info.SpecialInfo.stUsb3VInfo serial = bytes(st_usb_info.chSerialNumber).decode('ascii', 'ignore').rstrip('\x00') dev_name = f"USB: {st_usb_info.chUserDefinedName.decode('gbk', 'ignore')}" devList.append(f"[{i}] {dev_name} (SN: {serial})") else: devList.append(f"[{i}] 未知设备类型: {mvcc_dev_info.nTLayerType}") # 更新UI mainWindow.ComboDevices.clear() mainWindow.ComboDevices.addItems(devList) if devList: mainWindow.ComboDevices.setCurrentIndex(0) mainWindow.statusBar().showMessage(f"找到 {deviceList.nDeviceNum} 个设备", 3000) return MV_OK # ===== 关键改进:相机操作函数 ===== def open_device(): global deviceList, nSelCamIndex, obj_cam_operation, isOpen, frame_monitor_thread, mainWindow if isOpen: QMessageBox.warning(mainWindow, "Error", '相机已打开!', QMessageBox.Ok) return MV_E_CALLORDER nSelCamIndex = mainWindow.ComboDevices.currentIndex() if nSelCamIndex < 0: QMessageBox.warning(mainWindow, "Error", '请选择相机!', QMessageBox.Ok) return MV_E_CALLORDER # 创建相机控制对象 cam = MvCamera() # 初始化相机操作对象 - 确保传入有效的相机对象 obj_cam_operation = CameraOperation(cam, deviceList, nSelCamIndex) ret = obj_cam_operation.open_device() if 0 != ret: strError = "打开设备失败 ret:" + ToHexStr(ret) QMessageBox.warning(mainWindow, "Error", strError, QMessageBox.Ok) isOpen = False else: set_continue_mode() get_param() isOpen = True enable_controls() # 创建并启动帧监控线程 frame_monitor_thread = FrameMonitorThread(obj_cam_operation) frame_monitor_thread.frame_status.connect(mainWindow.statusBar().showMessage) frame_monitor_thread.start() def start_grabbing(): global obj_cam_operation, isGrabbing # 关键改进:添加相机状态检查 if not obj_cam_operation or not hasattr(obj_cam_operation, 'cam') or not obj_cam_operation.cam: QMessageBox.warning(mainWindow, "Error", "相机对象未正确初始化", QMessageBox.Ok) return ret = obj_cam_operation.start_grabbing(mainWindow.widgetDisplay.winId()) if ret != 0: strError = "开始取流失败 ret:" + ToHexStr(ret) QMessageBox.warning(mainWindow, "Error", strError, QMessageBox.Ok) else: isGrabbing = True enable_controls() # 等待第一帧到达 QThread.msleep(500) if not obj_cam_operation.is_frame_available(): QMessageBox.warning(mainWindow, "警告", "开始取流后未接收到帧,请检查相机连接!", QMessageBox.Ok) def stop_grabbing(): global obj_cam_operation, isGrabbing # 关键改进:添加相机状态检查 if not obj_cam_operation or not hasattr(obj_cam_operation, 'cam') or not obj_cam_operation.cam: QMessageBox.warning(mainWindow, "Error", "相机对象未正确初始化", QMessageBox.Ok) return # 关键改进:添加连接状态检查 if not hasattr(obj_cam_operation, 'connected') or not obj_cam_operation.connected: QMessageBox.warning(mainWindow, "Error", "相机未连接", QMessageBox.Ok) return ret = obj_cam_operation.Stop_grabbing() if ret != 0: strError = "停止取流失败 ret:" + ToHexStr(ret) QMessageBox.warning(mainWindow, "Error", strError, QMessageBox.Ok) else: isGrabbing = False enable_controls() def close_device(): global isOpen, isGrabbing, obj_cam_operation, frame_monitor_thread if frame_monitor_thread and frame_monitor_thread.isRunning(): frame_monitor_thread.stop() frame_monitor_thread.wait(2000) if isOpen and obj_cam_operation: # 关键改进:确保相机对象存在 if hasattr(obj_cam_operation, 'cam') and obj_cam_operation.cam: obj_cam_operation.close_device() isOpen = False isGrabbing = False enable_controls() def set_continue_mode(): # 关键改进:添加相机状态检查 if not obj_cam_operation or not hasattr(obj_cam_operation, 'cam') or not obj_cam_operation.cam: return ret = obj_cam_operation.set_trigger_mode(False) if ret != 0: strError = "设置连续模式失败 ret:" + ToHexStr(ret) QMessageBox.warning(mainWindow, "Error", strError, QMessageBox.Ok) else: mainWindow.radioContinueMode.setChecked(True) mainWindow.radioTriggerMode.setChecked(False) mainWindow.bnSoftwareTrigger.setEnabled(False) def set_software_trigger_mode(): # 关键改进:添加相机状态检查 if not obj_cam_operation or not hasattr(obj_cam_operation, 'cam') or not obj_cam_operation.cam: return ret = obj_cam_operation.set_trigger_mode(True) if ret != 0: strError = "设置触发模式失败 ret:" + ToHexStr(ret) QMessageBox.warning(mainWindow, "Error", strError, QMessageBox.Ok) else: mainWindow.radioContinueMode.setChecked(False) mainWindow.radioTriggerMode.setChecked(True) mainWindow.bnSoftwareTrigger.setEnabled(isGrabbing) def trigger_once(): # 关键改进:添加相机状态检查 if not obj_cam_operation or not hasattr(obj_cam_operation, 'cam') or not obj_cam_operation.cam: return ret = obj_cam_operation.trigger_once() if ret != 0: strError = "软触发失败 ret:" + ToHexStr(ret) QMessageBox.warning(mainWindow, "Error", strError, QMessageBox.Ok) def save_sample_image(): global isGrabbing, obj_cam_operation, current_sample_path if not isGrabbing: QMessageBox.warning(mainWindow, "错误", "请先开始取流并捕获图像!", QMessageBox.Ok) return # 尝试捕获当前帧 frame = obj_cam_operation.capture_frame() if frame is None: QMessageBox.warning(mainWindow, "无有效图像", "未捕获到有效图像,请检查相机状态!", QMessageBox.Ok) return # 确保图像有效 if frame.size == 0 or frame.shape[0] == 0 or frame.shape[1] == 0: QMessageBox.warning(mainWindow, "无效图像", "捕获的图像无效,请检查相机设置!", QMessageBox.Ok) return settings = QSettings("ClothInspection", "CameraApp") last_dir = settings.value("last_save_dir", os.path.join(os.getcwd(), "captures")) timestamp = datetime.now().strftime("%Y%m%d_%H%M%S") default_filename = f"sample_{timestamp}" file_path, selected_filter = QFileDialog.getSaveFileName( mainWindow, "保存标准样本图像", os.path.join(last_dir, default_filename), "BMP Files (*.bmp);;PNG Files (*.png);;JPEG Files (*.jpg);;所有文件 (*)", options=QFileDialog.DontUseNativeDialog ) if not file_path: return # 确保文件扩展名正确 file_extension = os.path.splitext(file_path)[1].lower() if not file_extension: if "BMP" in selected_filter: file_path += ".bmp" elif "PNG" in selected_filter: file_path += ".png" elif "JPEG" in selected_filter or "JPG" in selected_filter: file_path += ".jpg" else: file_path += ".bmp" file_extension = os.path.splitext(file_path)[1].lower() # 创建目录(如果不存在) directory = os.path.dirname(file_path) if directory and not os.path.exists(directory): try: os.makedirs(directory, exist_ok=True) except OSError as e: QMessageBox.critical(mainWindow, "目录创建错误", f"无法创建目录 {directory}: {str(e)}", QMessageBox.Ok) return # 保存图像 try: # 使用OpenCV保存图像 if not cv2.imwrite(file_path, frame): raise Exception("OpenCV保存失败") # 更新状态 current_sample_path = file_path update_sample_display() settings.setValue("last_save_dir", os.path.dirname(file_path)) # 显示成功消息 QMessageBox.information(mainWindow, "成功", f"标准样本已保存至:\n{file_path}", QMessageBox.Ok) # 可选:自动预览样本 preview_sample() except Exception as e: logging.error(f"保存图像失败: {str(e)}") QMessageBox.critical(mainWindow, "保存错误", f"保存图像发生错误:\n{str(e)}", QMessageBox.Ok) def preview_sample(): global current_sample_path if not current_sample_path or not os.path.exists(current_sample_path): QMessageBox.warning(mainWindow, "错误", "请先设置有效的标准样本图像!", QMessageBox.Ok) return try: # 直接使用OpenCV加载图像 sample_img = cv2.imread(current_sample_path) if sample_img is None: raise Exception("无法加载图像") # 显示图像 cv2.imshow("标准样本预览", sample_img) cv2.waitKey(0) cv2.destroyAllWindows() except Exception as e: QMessageBox.warning(mainWindow, "错误", f"预览样本失败: {str(e)}", QMessageBox.Ok) def start_grabbing(): global obj_cam_operation, isGrabbing ret = obj_cam_operation.start_grabbing(mainWindow.widgetDisplay.winId()) if ret != 0: strError = "开始取流失败 ret:" + ToHexStr(ret) QMessageBox.warning(mainWindow, "Error", strError, QMessageBox.Ok) else: isGrabbing = True enable_controls() # 等待第一帧到达 QThread.msleep(500) if not obj_cam_operation.is_frame_available(): QMessageBox.warning(mainWindow, "警告", "开始取流后未接收到帧,请检查相机连接!", QMessageBox.Ok) def is_float(str): try: float(str) return True except ValueError: return False def get_param(): try: ret = obj_cam_operation.get_parameters() if ret != MV_OK: strError = "获取参数失败,错误码: " + ToHexStr(ret) QMessageBox.warning(mainWindow, "错误", strError, QMessageBox.Ok) else: mainWindow.edtExposureTime.setText("{0:.2f}".format(obj_cam_operation.exposure_time)) mainWindow.edtGain.setText("{0:.2f}".format(obj_cam_operation.gain)) mainWindow.edtFrameRate.setText("{0:.2f}".format(obj_cam_operation.frame_rate)) except Exception as e: error_msg = f"获取参数发生错误: {str(e)}" QMessageBox.critical(mainWindow, "严重错误", error_msg, QMessageBox.Ok) def set_param(): frame_rate = mainWindow.edtFrameRate.text() exposure = mainWindow.edtExposureTime.text() gain = mainWindow.edtGain.text() if not (is_float(frame_rate) and is_float(exposure) and is_float(gain)): strError = "设置参数失败: 参数必须是有效的浮点数" QMessageBox.warning(mainWindow, "错误", strError, QMessageBox.Ok) return MV_E_PARAMETER try: ret = obj_cam_operation.set_param( frame_rate=float(frame_rate), exposure_time=float(exposure), gain=float(gain) ) if ret != MV_OK: strError = "设置参数失败,错误码: " + ToHexStr(ret) QMessageBox.warning(mainWindow, "错误", strError, QMessageBox.Ok) except Exception as e: error_msg = f"设置参数发生错误: {str(e)}" QMessageBox.critical(mainWindow, "严重错误", error_msg, QMessageBox.Ok) def enable_controls(): global isGrabbing, isOpen mainWindow.groupGrab.setEnabled(isOpen) mainWindow.paramgroup.setEnabled(isOpen) mainWindow.bnOpen.setEnabled(not isOpen) mainWindow.bnClose.setEnabled(isOpen) mainWindow.bnStart.setEnabled(isOpen and (not isGrabbing)) mainWindow.bnStop.setEnabled(isOpen and isGrabbing) mainWindow.bnSoftwareTrigger.setEnabled(isGrabbing and mainWindow.radioTriggerMode.isChecked()) mainWindow.bnSaveImage.setEnabled(isOpen and isGrabbing) mainWindow.bnCheckPrint.setEnabled(isOpen and isGrabbing) mainWindow.bnSaveSample.setEnabled(isOpen and isGrabbing) mainWindow.bnPreviewSample.setEnabled(bool(current_sample_path)) def update_sensor_display(data): if not data: return text = (f"张力: {data['tension']:.2f}N | " f"速度: {data['speed']:.2f}m/s | " f"温度: {data['temperature']:.1f}°C | " f"湿度: {data['humidity']:.1f}%") mainWindow.lblSensorData.setText(text) def connect_sensor(): global sensor_monitor_thread, sensor_controller sensor_type = mainWindow.cbSensorType.currentText() if sensor_controller is None: sensor_controller = SensorController() if sensor_type == "串口": config = { 'type': 'serial', 'port': mainWindow.cbComPort.currentText(), 'baudrate': int(mainWindow.cbBaudrate.currentText()), 'timeout': 1.0 } else: config = { 'type': 'ethernet', 'ip': mainWindow.edtIP.text(), 'port': int(mainWindow.edtPort.text()), 'timeout': 1.0 } if sensor_controller.connect(config): mainWindow.bnConnectSensor.setEnabled(False) mainWindow.bnDisconnectSensor.setEnabled(True) sensor_monitor_thread = SensorMonitorThread(sensor_controller) sensor_monitor_thread.data_updated.connect(update_sensor_display) sensor_monitor_thread.start() def disconnect_sensor(): global sensor_monitor_thread if sensor_controller: sensor_controller.disconnect() mainWindow.bnConnectSensor.setEnabled(True) mainWindow.bnDisconnectSensor.setEnabled(False) if sensor_monitor_thread and sensor_monitor_thread.isRunning(): sensor_monitor_thread.stop() sensor_monitor_thread.wait(2000) sensor_monitor_thread = None mainWindow.lblSensorData.setText("传感器数据: 未连接") def update_sensor_ui(index): mainWindow.serialGroup.setVisible(index == 0) mainWindow.ethernetGroup.setVisible(index == 1) class MainWindow(QMainWindow): def __init__(self): super().__init__() self.setWindowTitle("布料印花检测系统") self.resize(1200, 800) central_widget = QWidget() self.setCentralWidget(central_widget) main_layout = QVBoxLayout(central_widget) # 设备枚举区域 device_layout = QHBoxLayout() self.ComboDevices = QComboBox() self.bnEnum = QPushButton("枚举设备") self.bnOpen = QPushButton("打开设备") self.bnClose = QPushButton("关闭设备") device_layout.addWidget(self.ComboDevices) device_layout.addWidget(self.bnEnum) device_layout.addWidget(self.bnOpen) device_layout.addWidget(self.bnClose) main_layout.addLayout(device_layout) # 取流控制组 self.groupGrab = QGroupBox("取流控制") grab_layout = QHBoxLayout(self.groupGrab) self.bnStart = QPushButton("开始取流") self.bnStop = QPushButton("停止取流") self.radioContinueMode = QRadioButton("连续模式") self.radioTriggerMode = QRadioButton("触发模式") self.bnSoftwareTrigger = QPushButton("软触发") grab_layout.addWidget(self.bnStart) grab_layout.addWidget(self.bnStop) grab_layout.addWidget(self.radioContinueMode) grab_layout.addWidget(self.radioTriggerMode) grab_layout.addWidget(self.bnSoftwareTrigger) main_layout.addWidget(self.groupGrab) # 参数设置组 self.paramgroup = QGroupBox("相机参数") param_layout = QGridLayout(self.paramgroup) self.edtExposureTime = QLineEdit() self.edtGain = QLineEdit() self.edtFrameRate = QLineEdit() self.bnGetParam = QPushButton("获取参数") self.bnSetParam = QPushButton("设置参数") self.bnSaveImage = QPushButton("保存图像") param_layout.addWidget(QLabel("曝光:"), 0, 0) param_layout.addWidget(self.edtExposureTime, 0, 1) param_layout.addWidget(self.bnGetParam, 0, 2) param_layout.addWidget(QLabel("增益:"), 1, 0) param_layout.addWidget(self.edtGain, 1, 1) param_layout.addWidget(self.bnSetParam, 1, 2) param_layout.addWidget(QLabel("帧率:"), 2, 0) param_layout.addWidget(self.edtFrameRate, 2, 1) param_layout.addWidget(self.bnSaveImage, 2, 2) main_layout.addWidget(self.paramgroup) # 图像显示区域 self.widgetDisplay = QLabel() self.widgetDisplay.setMinimumSize(640, 480) self.widgetDisplay.setStyleSheet("background-color: black;") self.widgetDisplay.setAlignment(Qt.AlignCenter) self.widgetDisplay.setText("相机预览区域") main_layout.addWidget(self.widgetDisplay, 1) # 状态栏 #self.statusBar = QStatusBar() #self.setStatusBar(self.statusBar) # 创建自定义UI组件 self.setup_custom_ui() def setup_custom_ui(self): # 工具栏 toolbar = self.addToolBar("检测工具") self.bnCheckPrint = QPushButton("检测印花质量") self.bnSaveSample = QPushButton("保存标准样本") self.bnPreviewSample = QPushButton("预览样本") self.cbHistory = QComboBox() self.cbHistory.setMinimumWidth(300) toolbar.addWidget(self.bnCheckPrint) toolbar.addWidget(self.bnSaveSample) toolbar.addWidget(self.bnPreviewSample) toolbar.addWidget(QLabel("历史记录:")) toolbar.addWidget(self.cbHistory) # 状态栏样本路径 self.lblSamplePath = QLabel("当前样本:设置样本") self.statusBar().addPermanentWidget(self.lblSamplePath) # 右侧面板 right_panel = QWidget() right_layout = QVBoxLayout(right_panel) right_layout.setContentsMargins(10, 10, 10, 10) # 差异度调整组 diff_group = QGroupBox("差异度调整") diff_layout = QVBoxLayout(diff_group) self.lblDiffThreshold = QLabel("差异度阈值 (0-100%):") self.sliderDiffThreshold = QSlider(Qt.Horizontal) self.sliderDiffThreshold.setRange(0, 100) self.sliderDiffThreshold.setValue(5) self.lblDiffValue = QLabel("5%") self.lblCurrentDiff = QLabel("当前差异度: -") self.lblCurrentDiff.setStyleSheet("font-size: 14px; font-weight: bold;") self.lblDiffStatus = QLabel("状态: 未检测") self.lblDiffStatus.setStyleSheet("font-size: 12px;") diff_layout.addWidget(self.lblDiffThreshold) diff_layout.addWidget(self.sliderDiffThreshold) diff_layout.addWidget(self.lblDiffValue) diff_layout.addWidget(self.lblCurrentDiff) diff_layout.addWidget(self.lblDiffStatus) right_layout.addWidget(diff_group) # 传感器控制面板 sensor_panel = QGroupBox("传感器控制") sensor_layout = QVBoxLayout(sensor_panel) sensor_type_layout = QHBoxLayout() self.lblSensorType = QLabel("传感器类型:") self.cbSensorType = QComboBox() self.cbSensorType.addItems(["串口", "以太网"]) sensor_type_layout.addWidget(self.lblSensorType) sensor_type_layout.addWidget(self.cbSensorType) sensor_layout.addLayout(sensor_type_layout) # 串口参数 self.serialGroup = QGroupBox("串口参数") serial_layout = QVBoxLayout(self.serialGroup) self.lblComPort = QLabel("端口:") self.cbComPort = QComboBox() if platform.system() == 'Windows': ports = [f"COM{i}" for i in range(1, 21)] else: ports = [f"/dev/ttyS{i}" for i in range(0, 4)] + [f"/dev/ttyUSB{i}" for i in range(0, 4)] self.cbComPort.addItems(ports) self.lblBaudrate = QLabel("波特率:") self.cbBaudrate = QComboBox() self.cbBaudrate.addItems(["96000", "19200", "38400", "57600", "115200"]) self.cbBaudrate.setCurrentText("115200") serial_layout.addWidget(self.lblComPort) serial_layout.addWidget(self.cbComPort) serial_layout.addWidget(self.lblBaudrate) serial_layout.addWidget(self.cbBaudrate) sensor_layout.addWidget(self.serialGroup) # 以太网参数 self.ethernetGroup = QGroupBox("以太网参数") ethernet_layout = QVBoxLayout(self.ethernetGroup) self.lblIP = QLabel("IP地址:") self.edtIP = QLineEdit("192.168.1.100") self.lblPort = QLabel("端口:") self.edtPort = QLineEdit("502") ethernet_layout.addWidget(self.lblIP) ethernet_layout.addWidget(self.edtIP) ethernet_layout.addWidget(self.lblPort) ethernet_layout.addWidget(self.edtPort) sensor_layout.addWidget(self.ethernetGroup) # 连接按钮 self.bnConnectSensor = QPushButton("连接传感器") self.bnDisconnectSensor = QPushButton("断开传感器") self.bnDisconnectSensor.setEnabled(False) sensor_layout.addWidget(self.bnConnectSensor) sensor_layout.addWidget(self.bnDisconnectSensor) # 延迟设置 delay_layout = QHBoxLayout() self.lblDelay = QLabel("触发延迟(秒):") self.spinDelay = QSpinBox() self.spinDelay.setRange(0, 60) self.spinDelay.setValue(0) self.spinDelay.setToolTip("传感器检测到布料后延迟拍摄的间") delay_layout.addWidget(self.lblDelay) delay_layout.addWidget(self.spinDelay) sensor_layout.addLayout(delay_layout) # 传感器数据 self.lblSensorData = QLabel("传感器数据: 未连接") self.lblSensorData.setStyleSheet("font-size: 10pt;") sensor_layout.addWidget(self.lblSensorData) right_layout.addWidget(sensor_panel) right_layout.addStretch(1) # 停靠窗口 dock = QDockWidget("检测控制面板", self) dock.setWidget(right_panel) dock.setFeatures(QDockWidget.DockWidgetMovable | QDockWidget.DockWidgetFloatable) self.addDockWidget(Qt.RightDockWidgetArea, dock) def closeEvent(self, event): logging.info("主窗口关闭,执行清理...") close_device() disconnect_sensor() event.accept() if __name__ == "__main__": app = QApplication(sys.argv) mainWindow = MainWindow() # 信号连接 mainWindow.cbSensorType.currentIndexChanged.connect(update_sensor_ui) update_sensor_ui(0) mainWindow.bnConnectSensor.clicked.connect(connect_sensor) mainWindow.bnDisconnectSensor.clicked.connect(disconnect_sensor) mainWindow.sliderDiffThreshold.valueChanged.connect(update_diff_threshold) mainWindow.bnCheckPrint.clicked.connect(sensor_controlled_check) mainWindow.bnSaveSample.clicked.connect(save_sample_image) mainWindow.bnPreviewSample.clicked.connect(preview_sample) mainWindow.bnEnum.clicked.connect(enum_devices) mainWindow.bnOpen.clicked.connect(open_device) mainWindow.bnClose.clicked.connect(close_device) mainWindow.bnStart.clicked.connect(start_grabbing) mainWindow.bnStop.clicked.connect(stop_grabbing) mainWindow.bnSoftwareTrigger.clicked.connect(trigger_once) mainWindow.radioTriggerMode.clicked.connect(set_software_trigger_mode) mainWindow.radioContinueMode.clicked.connect(set_continue_mode) mainWindow.bnGetParam.clicked.connect(get_param) mainWindow.bnSetParam.clicked.connect(set_param) mainWindow.bnSaveImage.clicked.connect(save_sample_image) main() mainWindow.show() app.exec_() close_device() disconnect_sensor() sys.exit()
最新发布
07-12
<think>我们正在处理的问题:如何在Qt中将主窗口(mainwindow)的子窗口设置为模态窗口?根据引用[2]和引用[3],我们看到了创建对话框并设置为模态的示例。特别是引用[3]中,通过设置对话框的模态属性为Qt.ApplicationModal,然后使用exec_()方法显示对话框,使其成为模态对话框。关键点:1.模态窗口会阻塞其父窗口的输入。在Qt中,可以通过设置窗口的模态属性并调用exec()(或exec_(),在PyQt5中)来实现。2.对于QDialog,可以直接使用setModal(true)或者setWindowModality(Qt::ApplicationModal)来设置模态,然后使用exec()显示。3.但是,用户的问题是关于主窗口(MainWindow)的子窗口。注意,子窗口通常指的是作为主窗口的子组件的窗口,而不仅仅是对话框。在Qt中,我们可以使用QWidget或者QDialog作为子窗口。如果子窗口是QDialog,那么设置模态就很简单。如果是一个普通的QWidget,则需要将其设置Qt::Dialog标志,并设置模态属性。实现方法:方法1:使用QDialog作为子窗口-创建QDialog对象,设置其父窗口为mainwindow(这样它就是主窗口的子窗口)。-设置对话框的模态属性,然后使用exec()显示。方法2:如果子窗口是一个普通的QWidget,我们可以通过设置窗口标志和模态属性来使其成为模态窗口。-使用setWindowFlags()设置窗口标志为Qt::Dialog(或者包含Qt::Dialog标志)。-使用setWindowModality()设置模态属性(如Qt::ApplicationModal)。-然后使用show()显示,但是注意,使用show()显示,如果设置了模态属性,它也会成为模态窗口(但不会阻塞事件循环,所以需要配合事件循环)。不过,更常见的是使用exec(),但是QWidget没有exec(),所以我们可以通过创建一个本地事件循环来实现阻塞,但这比较复杂。因此,通常建议对于模态窗口使用QDialog。根据引用[2]中的示例(非模态对话框部分),我们也可以看到模态对话框是使用exec()来显示的。因此,推荐使用QDialog作为子窗口,并设置模态。示例代码(C++,类似于引用[2]):voidMainWindow::openModalDialog(){QDialog*dialog=newQDialog(this);//this指定父窗口为MainWindow,因此它是主窗口的子窗口dialog->setWindowTitle("模态子窗口");dialog->setWindowModality(Qt::ApplicationModal);//设置为应用程序模态,阻塞整个应用程序的窗口//也可以使用dialog->setModal(true);这等价于设置Qt::ApplicationModal//添加一些内容到dialogQVBoxLayout*layout=newQVBoxLayout;QLabel*label=newQLabel("这是一个模态对话框",dialog);layout->addWidget(label);dialog->setLayout(layout);dialog->exec();//使用exec()显示,会阻塞直到对话框关闭//注意:在堆上分配的dialog,在关闭后需要删除。由于设置了父对象,当父窗口销毁会被删除。但为了避免内存泄漏,也可以在对话框关闭自动删除:dialog->setAttribute(Qt::WA_DeleteOnClose);}示例代码(Python,类似于引用[3]):defshow_modal_dialog(self):dialog=QDialog(self)#self是MainWindow的实例,因此对话框是其子窗口dialog.setWindowTitle("模态子窗口")dialog.setWindowModality(Qt.ApplicationModal)#添加内容layout=QVBoxLayout()label=QLabel("这是一个模态对话框",dialog)layout.addWidget(label)dialog.setLayout(layout)dialog.exec_()注意:在PyQt5中,使用exec_(),在PyQt6中则使用exec()。如果确实需要使用QWidget(不是QDialog)作为模态窗口,可以尝试:widget=QWidget(parent)#parent是MainWindowwidget->setWindowModality(Qt::ApplicationModal);widget->setWindowFlags(Qt::Dialog);//设置为对话框风格widget->show();但是,这种方法不会阻塞事件循环,所以主窗口虽然被禁用,但程序仍然可以响应其他事件。如果希望像对话框那样阻塞,则必须自己实现事件循环(不推荐,因为容易出错)。因此,总结:使用QDialog并调用exec()是最简单且标准的方法。相关问题:1.模态窗口和非模态窗口有什么区别?2.在Qt中,如何设置一个对话框为模态?3.在Qt中,QDialog的exec()和show()方法有什么区别?4.如何避免在Qt中创建对话框的内存泄漏?</think>### 在Qt中将主窗口子窗口设置为模态窗口的方法 在Qt中,将主窗口(`QMainWindow`)的子窗口设置为模态窗口的核心是使用 **`QDialog`** 组件并设置其模态属性。以下是具体实现方法: --- #### **方法1:使用 `exec()` 创建应用程序级模态窗口** ```cpp // C++ 示例(主窗口类中) void MainWindow::openModalChildWindow() { // 创建对话框并设置父对象为主窗口 QDialog *dialog = new QDialog(this); // 设置模态属性(阻塞整个应用) dialog->setWindowModality(Qt::ApplicationModal); // 设置窗口标题和尺寸 dialog->setWindowTitle("模态子窗口"); dialog->resize(400, 300); // 阻塞式显示(exec()会暂停主窗口事件循环) dialog->exec(); } ``` **关键点**: - `setWindowModality(Qt::ApplicationModal)`:使子窗口阻塞所有应用窗口的输入。 - `exec()`:启动模态事件循环,子窗口关闭前主窗口无法响应操作[^2][^3]。 - **内存管理**:由于设置了父对象(`this`),子窗口会随主窗口自动销毁,避免内存泄漏[^2]。 --- #### **方法2:使用 `setModal(true)` 简化实现** ```python # Python/PyQt 示例 def show_modal_dialog(self): dialog = QDialog(self) # 父窗口为主窗口 dialog.setModal(True) # 等效于ApplicationModal dialog.setWindowTitle("模态对话框") dialog.exec_() # PyQt使用exec_() ``` - `setModal(true)` 是 `setWindowModality(Qt::ApplicationModal)` 的简写形式[^3]。 --- #### **方法3:窗口级模态(仅阻塞父窗口)** ```cpp // 仅阻塞主窗口,其他应用窗口仍可操作 void MainWindow::openWindowModal() { QDialog *dialog = new QDialog(this); dialog->setWindowModality(Qt::WindowModal); // 窗口级模态 dialog->show(); // 非阻塞式显示 } ``` - **适用场景**:需同操作其他应用窗口使用[^2]。 --- ### **注意事项** 1. **模态类型选择**: - `Qt::ApplicationModal`:阻塞整个应用程序(最常用)。 - `Qt::WindowModal`:仅阻塞父窗口。 2. **显示方法**: - 必须用 `exec()` 而非 `show()` 实现完全阻塞[^2][^3]。 3. **内存泄漏预防**: - 始终指定父对象(如 `new QDialog(this)`)[^2]。 - 或手动设置:`dialog->setAttribute(Qt::WA_DeleteOnClose)`。 > **示例效果**:点击主窗口按钮后,子窗口弹出期间主窗口无法操作(灰色遮罩),关闭子窗口后恢复主窗口操作[^3]。 --- ### 相关问题 1. **模态与非模态窗口有何本质区别?** (涉及事件循环处理机制) 2. **如何实现子窗口关闭自动传递数据回主窗口?** (信号槽机制的应用) 3. **`QDialog` 的 `exec()` 和 `open()` 方法有何差异?** (异步模态窗口的实现) 4. **在模态窗口中运行耗操作会导致界面卡死,如何解决?** (多线程与事件循环的协调) [^1]: 创建窗口和其他UI组件:使用Qt提供的各种类来创建窗口、对话框、按钮等UI组件,并进行布局和设置。 [^2]: 要想自定义对话框,就需要继承自QDialog创建类(对话框的内存泄漏问题)。 [^3]: Python Qt GUI设计:QMainWindow、QWidget和QDialog窗口类(基础篇—10)。
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