DeepBeliefSDK: image recognition framework for iOS

https://github.com/jetpacapp/DeepBeliefSDK/tree/master

by gmac • 12 years ago

56 13 12 years ago

github.com

arb99• 12 years ago

This looks really cool and something that will be fun to play with.

jetpac looks interesting too.

Any idea why they released this framework?

ilikerice• 12 years ago

Did you even read the readme.md? 6 lines from the top

"We're releasing this framework because we're excited by the power of this approach for general image recognition, especially when it can run locally on low-power devices. It gives your iPhone the ability to see, and I can't wait to see what applications that helps you build."

utopkara• 12 years ago

No source. I am glad you have a great looking product.

jayrparro• 12 years ago

looks great! is the image processing done in the server-side?

supercoder• 12 years ago

Where's the source

emsy• 12 years ago

The name fits: You've got to have a deep belief if you trust a 3rd Party binary.

epaga• 12 years ago

Why all the negativity, everyone? This is an impressive little framework - if you need to have the source code, it's not for you, but as-is, it is already useful for - at the very least - personal image recognition projects.

I love his excitement in his blog post and video about it where he trains a program to recognize his cat: http://petewarden.com/2014/04/08/how-to-add-a-brain-to-your-...

gress• 12 years ago

The negativity is because it's not open source, and HN is against anything that isn't open source.

sanxiyn• 12 years ago

If you are looking for an open source version, libccv was previously discussed here: https://news.ycombinator.com/item?id=7480380

mrfusion2• 12 years ago

Just curious, Is this the best algorithm to use for image recognition? What's a good library to use on the raspberry pi?

therobot24• 12 years ago

recognition and detection are two different things - for detection deep networks are performing as state of the art. Recent for recognition they are also doing well. However, one main difference is that many recognition tasks traditionally have very few images per object/user (especially when you're testing over hundreds or thousands of subjects). DeepFace by facebook showed that deep nets can be useful in recognition but set a rather unreal (at the moment) president that 100s-1000s of images can be used per subject.

mrfusion2• 12 years ago

So what's the difference between recognition and detection?

MrGando• 12 years ago

Loved this line of code:

NSString *networkPath = ....

if (networkPath == NULL) { // <- :)

Cheers!

DeepBeliefSDK: image recognition framework for iOS

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