Trying to generate tfrecord but I, m getting this error “filenotfounderror: [errno 2] no such file or directory”

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Python

detection

I'm following this link, https://colab.research.google.com/drive/11ko0DBnI1QLxVoJQR8gt9b4JDcvbCrtU#scrollTo=A_tyvKnBP6qD to build my object detector. I am using Google collab. My workspace structure is exactly as followed in this link. Everything was going fine until this block of code:

from object_detection.utils import dataset_util
%cd /content/drive/MyDrive/Gun_Detection/models

data_base_url = '/content/drive/MyDrive/Gun_Detection/data'
image_dir = data_base_url + 'images/'

def class_text_to_int(row_label):
        if row_label == 'pistol':
                return 1
        else:
                None


def split(df, group):
        data = namedtuple('data', ['filename', 'object']) #we wanna group by
        gb = df.groupby(group) #split data into group data by splitting, applying n combining
        return [data(filename, gb.get_group(x)) 
  for filename, x in zip(gb.groups.keys(), gb.groups)] #add group keys to index to identify pieces.

def create_tf_example(group, path):
        with tf.io.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

for csv in ['train_labels', 'test_labels']:
  writer = tf.io.TFRecordWriter(data_base_url + csv + '.record')
  path = os.path.join(image_dir)
  examples = pd.read_csv(data_base_url + csv + '.csv')
  grouped = split(examples, 'filename')
  for group in grouped:
      tf_example = create_tf_example(group, path)
      writer.write(tf_example.SerializeToString())
    
  writer.close()
  output_path = os.path.join(os.getcwd(), data_base_url + csv + '.record')
  print('Successfully created the TFRecords: {}'.format(data_base_url + csv + '.record'))

After this error, datatrain_label.record got generated in my Gun Detection folder in my drive. I am confused 😕 I can't proceed further. Please help!

N.B: I am not pro with python and am still learning. Trying hard to understand the code but I honestly don't.

This is the error message I'm getting:

<pre>/content/drive/MyDrive/Gun_Detection/models

---------------------------------------------------------------------------

FileNotFoundError                         Traceback (most recent call last)

<ipython-input-33-b566ecc28dcc> in <module>()
     61   writer = tf.io.TFRecordWriter(data_base_url + csv + '.record')
     62   path = os.path.join(image_dir)
---> 63   examples = pd.read_csv(data_base_url + csv + '.csv')
     64   grouped = split(examples, 'filename')
     65   for group in grouped:

4 frames

/usr/local/lib/python3.7/dist-packages/pandas/io/parsers.py in __init__(self, src, **kwds)
   2008         kwds["usecols"] = self.usecols
   2009 
-> 2010         self._reader = parsers.TextReader(src, **kwds)
   2011         self.unnamed_cols = self._reader.unnamed_cols
   2012 

pandas/_libs/parsers.pyx in pandas._libs.parsers.TextReader.__cinit__()

pandas/_libs/parsers.pyx in pandas._libs.parsers.TextReader._setup_parser_source()

FileNotFoundError: [Errno 2] No such file or directory: '/content/drive/MyDrive/Gun_Detection/datatrain_labels.csv'

What I have tried:

I have googled alot on this error but all in vain.