create_tfrecords.py

from tqdm.notebook import tqdm
import os


# TF Records
dest_path = './tf_records_of_images.tfrecords'

file_writer = tf.io.TFRecordWriter(dest_path)

# source dir
source_dir = '/path/to/images//*' 



import glob
filenames = glob.glob(source_dir)
print("[INFO] Number of files", len(filenames))

# from index 1 we can access each image along with the label
for path in tqdm(filenames, total=len(filenames)):
    
    with tf.io.gfile.GFile(path, 'rb') as fid:
        img = fid.read()
    label = int(os.path.dirname(path).split('/')[-1])


    record_bytes = tf.train.Example(features=tf.train.Features
                                    (feature={
                                                "image": tf.train.Feature(bytes_list=tf.train.BytesList(value=[img])),
                                                "label": tf.train.Feature(int64_list=tf.train.Int64List(value=[label])),
                                             }
                                    )
                                    ).SerializeToString()
    file_writer.write(record_bytes)

file_writer.close()