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 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

Inception V3

Inception-ResNet-V1

Pre-trained Models

Pre-trained GoogLeNet models can be found here.