Tensorflow Serving with Tensorflow Slim Models

Overview

Here comes the interesting part!

In previous section, we trained, built and served models such as mnist, inception-v3 that comes with the tensorflow serving. In this section, however, we will build and serve customized models.

To keep it simple and clear, we will use pre-defined ./tf_models/research/slim/nets/inception-v4 and ./tf_models/research/slim/nets/inception-resnet-v2 models as examples.

This approach should works with all models defined in ./tf_models/research/slim/nets, such as inception, inception-resnet, resnet, vgg, and mobilenet. A full list of models and versions can be found at https://github.com/tensorflow/models/tree/master/research/slim.

Let's start!

Tensorflow Serving with Slim Inception-V4

Tensorflow Serving with Slim Inception-Resnet-V2

A Unified Slim Client on PredictionService

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