image-classifier

This is the code for this video on Youtube by Siraj Raval. Perform image classification using deep neural networks (DNNs) on Intel® Movidius™ Neural Compute Stick (NCS). The NCS developer blog has a step by step tutorial on how to build this project, and also has a detailed explanation of the source code.

Prerequisites

This code example requires that the following components are available:

1. Movidius Neural Compute Stick
2. Movidius Neural Compute SDK

Running this example

mkdir -p ~/workspace
cd ~/workspace
git clone https://github.com/movidius/ncappzoo
cd ~/workspace/ncappzoo/apps/image-classifier/
make run

When the application runs normally and is able to connect to the NCS device, the output will be similar to this:

==============================================================
Top predictions for cat.jpg
Execution time: 95.0071ms
--------------------------------------------------------------
40.4%	n02123159 tiger cat
32.7%	n02123045 tabby, tabby cat
8.9%	n02124075 Egyptian cat
5.0%	n02127052 lynx, catamount
1.2%	n04074963 remote control, remote
1.1%	n02971356 carton
==============================================================

You should also see the image on which inference was performed.

Configuring this example

This example runs GoogLeNet by default, but you can configure it run other pre-trained deep neural networks. Below are some example commands:

AlexNet (Caffe)

python3 image-classifier.py --graph ../../caffe/AlexNet/graph --dim 227 227 --image ../../data/images/pic_053.jpg

SqueezeNet (Caffe)

python3 image-classifier.py --graph ../../caffe/SqueezeNet/graph --dim 227 227 --image ../../data/images/pic_053.jpg

Mobilenet (Tensorflow)

python3 image-classifier.py --graph ../../tensorflow/mobilenets/model/graph --labels ../../tensorflow/mobilenets/model/labels.txt --mean 127.5 --scale 0.00789 --dim 224 224 --colormode="RGB" --image ../../data/images/pic_053.jpg 

Inception (Tensorflow)

python3 image-classifier.py --graph ../../tensorflow/inception/model/v3/graph --labels ../../tensorflow/inception/model/v3/labels.txt --mean 127.5 --scale 0.00789 --dim 299 299 --colormode="RGB" --image ../../data/images/pic_053.jpg 

Customizing this example

You can use this project as a template for your custom image classifier app. Below are some tips to help customize the example.

1. Before attemping to customize, check if the built-in options would suffice. Run python3 image-classifier.py -h to list all available options.
2. Steps 1, 2 and 5 are common across all Neural Compute Stick apps, so you can re-use those fuctions without modifications.
3. Step 3, 'Pre-process the images' is probably the most customizable function. As the name suggests, you can include all image pre-processing tasks in this function. Ex. if you don't want to warp the input image, just crop it before calling skimage.transform.resize.
4. Step 4 should be modified only if there is a need to change the way inference results are read and printed.

Credits

Credits for this code go to Intel