# CNTK Examples: Image/Classification/GoogLeNet

## Overview

|Data:     |The ILSVRC2012 dataset (http://www.image-net.org/challenges/LSVRC/2012/) for image classification.
|:---------|:---
|Purpose   |This folder contains examples that demonstrate how to use CNTK to define GoogLeNet (https://arxiv.org/abs/1409.4842) and its derivations for image classification.
|Network   |Deep convolutional neural networks codenamed "Inception" (GoogLeNet).
|Training  |See the details.
|Comments  |See below.

## Running the example

### Getting the data
We use the ILSVRC2012 datasets to demonstrate how to train a GoogLeNet. GoogLeNet was initially published by Researchers at Google Inc., and it is fine-tuned to have excellent classification accuracy and low computation cost. It won first place in the [ILSVRC](http://www.image-net.org/challenges/LSVRC/) 2014 detection challenge.


ILSVRC2012 datasets are not included in the CNTK distribution. You may obtain it through http://image-net.org.

## Details

We currently offer the BN-Inception (https://arxiv.org/abs/1502.03167) and Inception V3 (https://arxiv.org/abs/1512.00567), Inception-ResNet-V1 (https://arxiv.org/abs/1602.07261) models.

### [BN-Inception](./BN-Inception)

### [Inception V3](./InceptionV3)

### [Inception-ResNet-V1](./Inception-ResNet-V1)

## Pre-trained Models

Pre-trained GoogLeNet models can be found [here](../../../../PretrainedModels/Image.md#googlenet).