Machine Learning with TensorFlow 1.x

Preparing the dataset

Now, let's start preparing the dataset of our network.

For this inception network, we'll use the TFRecord class to manage our dataset. The output dataset files after the preprocessing will be protofiles, which TFRecord can read, and it's just our data stored in a serialized format for faster reading speed. Each protofile has some information stored within it, which is information such as image size and format.

The reason we are doing this is that the size of the dataset is too large and we cannot load the entire dataset into memory (RAM) as it will take up a huge amount of space. Therefore, to manage efficient RAM usage, we have to load the images in batches and delete the previously loaded images that are not being ...