Sample

In this sample we will go through typical steps required to evaluate DL topologies.

We will try to evaluate SampLeNet topology as an example.

Do not forget to run git lfs pull, to download model and dataset files.

1. Extract dataset

In this sample we will use toy dataset which we refer to as sample dataset, which contains 10k images of 10 different classes (classification problem), which is actually CIFAR10 dataset converted to png.

tar xvf sample/sample_dataset.tar.gz -C sample

2. Evaluate sample topology

Typically you need to write configuration file, describing evaluation process of your topology. There is already config file for evaluating SampLeNet using Caffe framework, read it carefully.

accuracy_check -c sample/sample_config.yml -m data/test_models -s sample

Used options: -c path to evaluation config, -m directory where models are stored, -s directory where source data (datasets).

If everything worked correctly, you should be able to get 75.02% accuracy.

Now try edit config, to run SampLeNet on Inference Engine, or go directly to your topology!