xml_to_csv.py

#adjusted from: https://github.com/datitran/raccoon_dataset
def xml_to_csv(path):
  classes_names = []
  xml_list = []

  for xml_file in glob.glob(path + '/*.xml'):
    tree = ET.parse(xml_file)
    root = tree.getroot()
    for member in root.findall('object'):
      classes_names.append(member[0].text)
      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) 
  classes_names = list(set(classes_names))
  classes_names.sort()
  return xml_df, classes_names

for label_path in ['train_labels', 'test_labels']:
  image_path = os.path.join(os.getcwd(), label_path)
  xml_df, classes = xml_to_csv(label_path)
  xml_df.to_csv(f'{label_path}.csv', index=None)
  print(f'Successfully converted {label_path} xml to csv.')

label_map_path = os.path.join("label_map.pbtxt")
pbtxt_content = ""

for i, class_name in enumerate(classes):
    pbtxt_content = (
        pbtxt_content
        + "item {{\n    id: {0}\n    name: '{1}'\n}}\n\n".format(i + 1, class_name)
    )
pbtxt_content = pbtxt_content.strip()
with open(label_map_path, "w") as f:
    f.write(pbtxt_content)
    print('Successfully created label_map.pbtxt ')