Created
February 19, 2021 05:07
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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() |
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