'IndexError: child index out of range - while converting my XML files to CSV (and TFRecord format)
I'm trying to convert my XML files to CSV. Finally, I need my images and annotations in TFRecord format to use them to train my custom SSD MobileNet V2 320x320 model.
Below is the complete python script I'm using for this process:
""" Sample TensorFlow XML-to-TFRecord converter
usage: generate_tfrecord.py [-h] [-x XML_DIR] [-l LABELS_PATH] [-o OUTPUT_PATH] [-i IMAGE_DIR] [-c CSV_PATH]
optional arguments:
-h, --help show this help message and exit
-x XML_DIR, --xml_dir XML_DIR
Path to the folder where the input .xml files are stored.
-l LABELS_PATH, --labels_path LABELS_PATH
Path to the labels (.pbtxt) file.
-o OUTPUT_PATH, --output_path OUTPUT_PATH
Path of output TFRecord (.record) file.
-i IMAGE_DIR, --image_dir IMAGE_DIR
Path to the folder where the input image files are stored. Defaults to the same directory as XML_DIR.
-c CSV_PATH, --csv_path CSV_PATH
Path of output .csv file. If none provided, then no file will be written.
"""
import os
import glob
import pandas as pd
import io
import xml.etree.ElementTree as ET
import argparse
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # Suppress TensorFlow logging (1)
import tensorflow.compat.v1 as tf
from PIL import Image
from object_detection.utils import dataset_util, label_map_util
from collections import namedtuple
# Initiate argument parser
parser = argparse.ArgumentParser(
description="Sample TensorFlow XML-to-TFRecord converter")
parser.add_argument("-x",
"--xml_dir",
help="Path to the folder where the input .xml files are stored.",
type=str)
parser.add_argument("-l",
"--labels_path",
help="Path to the labels (.pbtxt) file.", type=str)
parser.add_argument("-o",
"--output_path",
help="Path of output TFRecord (.record) file.", type=str)
parser.add_argument("-i",
"--image_dir",
help="Path to the folder where the input image files are stored. "
"Defaults to the same directory as XML_DIR.",
type=str, default=None)
parser.add_argument("-c",
"--csv_path",
help="Path of output .csv file. If none provided, then no file will be "
"written.",
type=str, default=None)
args = parser.parse_args()
if args.image_dir is None:
args.image_dir = args.xml_dir
label_map = label_map_util.load_labelmap(args.labels_path)
label_map_dict = label_map_util.get_label_map_dict(label_map)
def xml_to_csv(path):
"""Iterates through all .xml files (generated by labelImg) in a given directory and combines
them in a single Pandas dataframe.
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 class_text_to_int(row_label):
return label_map_dict[row_label]
def split(df, group):
data = namedtuple('data', ['filename', 'object'])
gb = df.groupby(group)
return [data(filename, gb.get_group(x)) for filename, x in zip(gb.groups.keys(), gb.groups)]
def create_tf_example(group, path):
with tf.gfile.GFile(os.path.join(path, '{}'.format(group.filename)), 'rb') as fid:
encoded_jpg = fid.read()
encoded_jpg_io = io.BytesIO(encoded_jpg)
image = Image.open(encoded_jpg_io)
width, height = image.size
filename = group.filename.encode('utf8')
image_format = b'jpg'
xmins = []
xmaxs = []
ymins = []
ymaxs = []
classes_text = []
classes = []
for index, row in group.object.iterrows():
xmins.append(row['xmin'] / width)
xmaxs.append(row['xmax'] / width)
ymins.append(row['ymin'] / height)
ymaxs.append(row['ymax'] / height)
classes_text.append(row['class'].encode('utf8'))
classes.append(class_text_to_int(row['class']))
tf_example = tf.train.Example(features=tf.train.Features(feature={
'image/height': dataset_util.int64_feature(height),
'image/width': dataset_util.int64_feature(width),
'image/filename': dataset_util.bytes_feature(filename),
'image/source_id': dataset_util.bytes_feature(filename),
'image/encoded': dataset_util.bytes_feature(encoded_jpg),
'image/format': dataset_util.bytes_feature(image_format),
'image/object/bbox/xmin': dataset_util.float_list_feature(xmins),
'image/object/bbox/xmax': dataset_util.float_list_feature(xmaxs),
'image/object/bbox/ymin': dataset_util.float_list_feature(ymins),
'image/object/bbox/ymax': dataset_util.float_list_feature(ymaxs),
'image/object/class/text': dataset_util.bytes_list_feature(classes_text),
'image/object/class/label': dataset_util.int64_list_feature(classes),
}))
return tf_example
def main(_):
writer = tf.python_io.TFRecordWriter(args.output_path)
path = os.path.join(args.image_dir)
examples = xml_to_csv(args.xml_dir)
grouped = split(examples, 'filename')
for group in grouped:
tf_example = create_tf_example(group, path)
writer.write(tf_example.SerializeToString())
writer.close()
print('Successfully created the TFRecord file: {}'.format(args.output_path))
if args.csv_path is not None:
examples.to_csv(args.csv_path, index=None)
print('Successfully created the CSV file: {}'.format(args.csv_path))
if __name__ == '__main__':
tf.app.run()
Below is an example of my XML file:
<annotation>
<folder></folder>
<filename>20210401_135713_jpg.rf.c3433a47627088aa68da9693635476d7.jpg</filename>
<path>20210401_135713_jpg.rf.c3433a47627088aa68da9693635476d7.jpg</path>
<source>
<database>roboflow.ai</database>
</source>
<size>
<width>800</width>
<height>600</height>
<depth>3</depth>
</size>
<segmented>0</segmented>
<object>
<name>orange</name>
<pose>Unspecified</pose>
<truncated>0</truncated>
<difficult>0</difficult>
<occluded>0</occluded>
<bndbox>
<xmin>167</xmin>
<xmax>278</xmax>
<ymin>162</ymin>
<ymax>264</ymax>
</bndbox>
</object>
</annotation>
I'm getting the following error:
Traceback (most recent call last):
File "Tensorflow\scripts\generate_tfrecord.py", line 168, in <module>
tf.app.run()
File "C:\Users\a\Documents\Capstone\Cuisine_Vision\Detection\cuisinevision\lib\site-packages\tensorflow\python\platform\app.py", line 40, in run
_run(main=main, argv=argv, flags_parser=_parse_flags_tolerate_undef)
File "C:\Users\a\Documents\Capstone\Cuisine_Vision\Detection\cuisinevision\lib\site-packages\absl\app.py", line 303, in run
_run_main(main, args)
File "C:\Users\a\Documents\Capstone\Cuisine_Vision\Detection\cuisinevision\lib\site-packages\absl\app.py", line 251, in _run_main
sys.exit(main(argv))
File "Tensorflow\scripts\generate_tfrecord.py", line 155, in main
examples = xml_to_csv(args.xml_dir)
File "Tensorflow\scripts\generate_tfrecord.py", line 88, in xml_to_csv
int(member[4][0].text),
IndexError: child index out of range
Traceback (most recent call last):
File "Tensorflow\scripts\generate_tfrecord.py", line 168, in <module>
tf.app.run()
File "C:\Users\a\Documents\Capstone\Cuisine_Vision\Detection\cuisinevision\lib\site-packages\tensorflow\python\platform\app.py", line 40, in run
_run(main=main, argv=argv, flags_parser=_parse_flags_tolerate_undef)
File "C:\Users\a\Documents\Capstone\Cuisine_Vision\Detection\cuisinevision\lib\site-packages\absl\app.py", line 303, in run
_run_main(main, args)
File "C:\Users\a\Documents\Capstone\Cuisine_Vision\Detection\cuisinevision\lib\site-packages\absl\app.py", line 251, in _run_main
sys.exit(main(argv))
File "Tensorflow\scripts\generate_tfrecord.py", line 155, in main
examples = xml_to_csv(args.xml_dir)
File "Tensorflow\scripts\generate_tfrecord.py", line 88, in xml_to_csv
int(member[4][0].text),
IndexError: child index out of range
Can anyone come up with a solution for this issue? Thank you!
Solution 1:[1]
you need just to index inside nested for loop of xml_to_csv(path):
Before:
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)
)
After:
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[5][0].text),
int(member[5][1].text),
int(member[5][2].text),
int(member[5][3].text)
)
since it looks for bndbox of the object which is 6th in order but you start count from 0 so you get 5.
Solution 2:[2]
I think the below is what you are looking for
import xml.etree.ElementTree as ET
xml = '''<annotation>
<folder></folder>
<filename>20210401_135713_jpg.rf.c3433a47627088aa68da9693635476d7.jpg</filename>
<path>20210401_135713_jpg.rf.c3433a47627088aa68da9693635476d7.jpg</path>
<source>
<database>roboflow.ai</database>
</source>
<size>
<width>800</width>
<height>600</height>
<depth>3</depth>
</size>
<segmented>0</segmented>
<object>
<name>orange</name>
<pose>Unspecified</pose>
<truncated>11</truncated>
<difficult>12</difficult>
<occluded>13</occluded>
<bndbox>
<xmin>167</xmin>
<xmax>278</xmax>
<ymin>162</ymin>
<ymax>264</ymax>
</bndbox>
</object>
</annotation>'''
xml_list = []
root = ET.fromstring(xml)
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,
member[1].text,
int(member[2].text),
int(member[3].text),
int(member[4].text)
)
xml_list.append(value)
print(xml_list)
output
[('20210401_135713_jpg.rf.c3433a47627088aa68da9693635476d7.jpg', 800, 600, 'orange', 'Unspecified', 11, 12, 13)]
Sources
This article follows the attribution requirements of Stack Overflow and is licensed under CC BY-SA 3.0.
Source: Stack Overflow
| Solution | Source |
|---|---|
| Solution 1 | Dharman |
| Solution 2 | balderman |