import os import sys from PyQt5.QtCore import * from PyQt5.QtWidgets import * from PyQt5.QtGui import * from PyQt5 import uic import pandas as pd import shutil import subprocess # from inference import run_AI def resource_path(relative_path): base_path = getattr( sys, "_MEIPASS", os.path.dirname(os.path.abspath(__file__)) ) return os.path.join(base_path, relative_path) form = resource_path("input_output.ui") form_class = uic.loadUiType(form)[0] class WindowClass(QMainWindow, form_class): def __init__(self): super().__init__() self.setupUi(self) self.btnInput.clicked.connect(self.fileload) self.btnAI.clicked.connect(self.AIDetection) self.btnExcelDownload.clicked.connect(self.downloadTable) self.btnCADDownload.clicked.connect(self.downloadCAD) self.imageList = [] def fileload(self): for i in reversed(range(self.inputImages.count())): widget = self.inputImages.itemAt(i).widget() self.inputImages.removeWidget(widget) widget.setParent(None) image_filter = "이미지 파일 (*.png *.jpg *.bmp *.gif *.jpeg, *.tiff, *.tif)" self.imageList, _ = QFileDialog.getOpenFileNames(self, "이미지 파일 업로드", filter=image_filter) self.inputImageWidget = QWidget() self.inputImageLayout = QGridLayout(self.inputImageWidget) row, col = 0, 0 for image_path in self.imageList: pixmap = QPixmap(image_path) label = QLabel() label.setPixmap(pixmap) label.setScaledContents(True) label.setFixedSize(300, 250) file_name_label = QLabel(os.path.basename(image_path)) self.inputImageLayout.addWidget(label, row, col) self.inputImageLayout.addWidget(file_name_label, row + 1, col) col += 1 if col == 2: col = 0 row += 2 scrollArea = QScrollArea() scrollArea.setWidgetResizable(True) scrollArea.setWidget(self.inputImageWidget) self.inputImages.addWidget(scrollArea) def AIDetection(self): if not self.imageList: QMessageBox.warning(self, "알림", "이미지 파일을 업로드해주세요.", QMessageBox.Ok) return self.outputImages.clear() # The path where you want to save the text file output_file_path = "./image_paths.txt" with open(output_file_path, "w") as file: for path in self.imageList: file.write(path + "\n") # run_AI() subprocess.run(['python', 'inference.py']) ## 1. stitching ## stitching_img_path = './results/data1/panorama.jpg' image_label = QLabel() pixmap = QPixmap(stitching_img_path) image_label.setPixmap(pixmap) image_label.setScaledContents(True) image_label.setAlignment(Qt.AlignCenter) self.outputImages.addTab(image_label, 'Stitching') ## 2. detection ## detection_img_path = './results/data1/panorama_detected.jpg' image_label = QLabel() pixmap = QPixmap(detection_img_path) image_label.setPixmap(pixmap) image_label.setScaledContents(True) image_label.setAlignment(Qt.AlignCenter) self.outputImages.addTab(image_label, 'Detection') ## 3. contour ## detection_img_path = './results/data1/contour_panorama_detected.jpg' image_label = QLabel() pixmap = QPixmap(detection_img_path) image_label.setPixmap(pixmap) image_label.setScaledContents(True) image_label.setAlignment(Qt.AlignCenter) self.outputImages.addTab(image_label, 'Contour') ## 4. CAD ## image_path = './results/data1/CAD_FORMAT.svg' image_label = QLabel() pixmap = QPixmap(image_path) image_label.setPixmap(pixmap) image_label.setScaledContents(True) image_label.setAlignment(Qt.AlignCenter) self.outputImages.addTab(image_label, 'CAD') ## 5. Table ## # Table csv_path = './results/data1/detection_coor.csv' df = pd.read_csv(csv_path) class_data = {'class_1': {'count': 0, 'areas': 0}, 'class_2': {'count': 0, 'areas': 0}, 'class_3': {'count': 0, 'areas': 0}, 'class_4': {'count': 0, 'areas': 0}} for idx, row in df.iterrows(): label = row['label'] area = (row['x2'] - row['x1']) * (row['y2'] - row['y1']) class_data[label]['count'] += 1 class_data[label]['areas'] += area for col_idx, value in enumerate(class_data.values()): item_count = QTableWidgetItem(str(value['count'])) item_areas = QTableWidgetItem(str(value['areas'])) self.outputTable.setItem(0, col_idx, item_count) self.outputTable.setItem(1, col_idx, item_areas) def downloadTable(self): file_path, _ = QFileDialog.getSaveFileName(self, "Download Excel", "excel_file.xlsx", "Excel Files (*.xlsx)") if file_path: # Gather data from the table data = [] for row in range(self.outputTable.rowCount()): row_data = [] for column in range(self.outputTable.columnCount()): item = self.outputTable.item(row, column) row_data.append(item.text() if item is not None else '') data.append(row_data) # Create DataFrame df = pd.DataFrame(data, columns=['균열', '박리/박락', '백태', '철근 노출']) # Check if the DataFrame has exactly two rows if len(df) == 2: df.index = ['수량', '총면적(pixel)'] else: # Handle the case where the number of rows is not two print("Error: DataFrame does not have exactly two rows.") return # Create a Pandas Excel writer using XlsxWriter as the engine with pd.ExcelWriter(file_path, engine='xlsxwriter') as writer: # Write DataFrame to the Excel file df.to_excel(writer, sheet_name='Crack Result') # Get the xlsxwriter workbook and worksheet objects worksheet = writer.sheets['Crack Result'] # Set the column width for i in range(df.shape[1] + 1): # +1 to include the index column worksheet.set_column(i, i, 15) def downloadCAD(self): file_path = './results/data1/dxf_file.dxf' download_path, _ = QFileDialog.getSaveFileName(self, "Download DXF", "cad_file.dxf", "DXF Files (*.dxf)") if download_path: try: shutil.copyfile(file_path, download_path) print(f"다운로드 성공: {download_path}") except Exception as e: print(f"다운로드 실패: {e}") if __name__ == "__main__": app = QApplication(sys.argv) myWindow = WindowClass() myWindow.setWindowTitle("SSIMS (Auto concrete damage detector)") myWindow.show() app.exec_()