How to rapidly prototype an image recognition application using Machine learning & neural network?

Question

Known that I'm very new in Machine learning.

I was thinking about a real world example of using Machine Learning and Neural network in an application and I want to try it with a mobile application who can handle image recognition with the front camera after make an image of something(A cat for exemple).

I really need advice of tools to use to rapidly make a prototype of this application with a python backend that I will call via rest.

Thanks in advance.

Answer 1

I suggest if you are new to the machine learning algorithms, that you use an API from Google or Microsoft and get in touch with the flow and how it works .. Once you understand what are the inputs and outputs, you can try to replace the API for you own neural net, try to train it properly and collect results ..

Machine learning is not an easy concept and if you start big, there is a good chance that you'll get discouraged before you finish building it ... The API will provide you with a functional prototype very quickly and thus help you stay motivated to pursue it more ..

But to answer your question more directly, TensorFlow by Google is probably the most sophisticated tool for machine learning in general right now..

There is an excellent course for deep learning with TensorFlow made by Google on Udacity ..

Answer 2

I have done something similar for our company website. It is based on caffe though. You can go through the source code here

However, it is a segmentation demo. You need to modify it a little.

Answer 3

Use an image recognition API, like google vision.
It is easy and fast to put in an application, and a lot more effective if you do not have experience and ressources in ML

Answer 4

You can follow PyImageSearch. It has lot of stuff related image processiong like face recognition and license Plate Recognition system. It also use neural networks.