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TFRecord Example

# Description

  • "Generate_TFRecord.py" is to generate tfrecords from flowers dataset.
  • "Read_TFRecord.py" is to read tfrecords (tf.data API)
  • "Read_Threading.py" is to read tfrecords (Threading)

# Experiments

  • batch size is 64.
  • Weakly Augmentation is flip and random crop.
  • Strongly Augmentation is RandAugment.
Preprocessing tf.data API (ms/64 images) Threading API (ms/64 images)
No Augmentation 20~30ms 20~30ms
Weakly Augmentation 30~40ms 40~50ms
Strongly Augmentation 2400~2500ms 4300~4600ms

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