""" Usage: # Create train data: python xml_to_csv.py -i [PATH_TO_IMAGES_FOLDER]/train -o [PATH_TO_ANNOTATIONS_FOLDER]/train_labels.csv # Create test data: python xml_to_csv.py -i [PATH_TO_IMAGES_FOLDER]/test -o [PATH_TO_ANNOTATIONS_FOLDER]/test_labels.csv """ import os import glob import pandas as pd import argparse import xml.etree.ElementTree as ET def xml_to_csv(path): """Iterates through all .xml files (generated by labelImg) in a given directory and combines them in a single Pandas datagrame. Parameters: ---------- path : {str} The path containing the .xml files Returns ------- Pandas DataFrame The produced dataframe """ xml_list = [] for xml_file in glob.glob(path + '/*.xml'): tree = ET.parse(xml_file) root = tree.getroot() for member in root.findall('object'): value = (root.find('filename').text, int(root.find('size')[0].text), int(root.find('size')[1].text), member[0].text, int(member[4][0].text), int(member[4][1].text), int(member[4][2].text), int(member[4][3].text) ) xml_list.append(value) column_name = ['filename', 'width', 'height', 'class', 'xmin', 'ymin', 'xmax', 'ymax'] xml_df = pd.DataFrame(xml_list, columns=column_name) return xml_df def main(): # Initiate argument parser parser = argparse.ArgumentParser( description="Sample TensorFlow XML-to-CSV converter") parser.add_argument("-i", "--inputDir", help="Path to the folder where the input .xml files are stored", type=str) parser.add_argument("-o", "--outputFile", help="Name of output .csv file (including path)", type=str) args = parser.parse_args() if(args.inputDir is None): args.inputDir = os.getcwd() if(args.outputFile is None): args.outputFile = args.inputDir + "/labels.csv" assert(os.path.isdir(args.inputDir)) xml_df = xml_to_csv(args.inputDir) xml_df.to_csv( args.outputFile, index=None) print('Successfully converted xml to csv.') if __name__ == '__main__': main()