Machine Learning with TensorFlow 1.x

Understanding the pipeline

Let's start by cloning the models repository into your computer:

git clone https://github.com/tensorflow/models/

Now, let's dive into the pipeline that we got from Google's model repository.

If you look at the folder at this path prefix (models/research/slim) in the repository, you'll see folders named datasets, deployment, nets, preprocessing, and scripts; a bunch of files related to generating the model, plus training and testing pipelines and files related to training the ImageNet dataset, and a dataset named flowers.

We will use the download_and_convert_data.py to build our DR dataset. This image classification model library is built based on the slim library. In this chapter, we will fine-tune the inception ...