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Facebook open-sources Detectron

research.fb.com

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Re: Facebook open-sources Detectron

#31

Post by linkmotif »

stmw wrote: post #24
stmw wrote: post #11

This is great! I do wish this were written in something other than Python. What is the carbon footprint of all this computer vision, compute-intensive code still being run billions of times a day in Python? Someone should calculate...

It is funny to see this comment get "-4" already... What's so offensive? After all, Facebook has rocksdb in C++, percona in java, and a PHP->C++ compiler, so they clearly have both the belief and the skill in moving away from interpreted programming languages for performance-sensitive code.

For some reason, people are offended by gross misunderstandings. This framework is in Python, but it’s a Python binding that sets up code that runs natively (not even sure the details myself; others are writing CUDA). TensorFlow is the same way. It’s in Python, but the computations are not in Python. As you point out, that wouldn’t make sense.

Re: Facebook open-sources Detectron

#32

Post by fulafel »

xiphias wrote: post #4

I'm happy that tech companies are open sourcing basic research all the time, and thinking a lot about what would have happened if large pharmacy companies did the same thing. I'm just hopeful that with new biotech companies the science behind curing people will get faster as well.

Very sorry to nitpick, but this and pharma research are applied research - basic research is things like string theory and abstract math. See eg http://www.sjsu.edu/people/fred.prochaska/courses/ScWk170/s0...

Companies rarely do basic research, and that's why it's very important to keep up public funding for it.

Re: Facebook open-sources Detectron

#33

Post by sankalp_sans »

stmw wrote: post #24
stmw wrote: post #11

This is great! I do wish this were written in something other than Python. What is the carbon footprint of all this computer vision, compute-intensive code still being run billions of times a day in Python? Someone should calculate...

It is funny to see this comment get "-4" already... What's so offensive? After all, Facebook has rocksdb in C++, percona in java, and a PHP->C++ compiler, so they clearly have both the belief and the skill in moving away from interpreted programming languages for performance-sensitive code.

More downvotes. Tough crowd :)

Re: Facebook open-sources Detectron

#34

Post by [deleted] »

vinniejames wrote: post #23
megous wrote: post #7

So is this the end of Google captchas asking for where the car/sign/whatever is? Will there be a final battle of AIs, where they will kill each other, and the unfettered access to websites over VPN/tor wins and laughs the last laugh?

No, they are like using that data to build self driving car algorithms. I would imagine that's why it's always asking you to detect roadsigns

[deleted]

Re: Facebook open-sources Detectron

#35

Post by jamesmcintyre »

dokument wrote: post #9
megous wrote: post #7

So is this the end of Google captchas asking for where the car/sign/whatever is? Will there be a final battle of AIs, where they will kill each other, and the unfettered access to websites over VPN/tor wins and laughs the last laugh?

Amazon will have a new captcha asking how many boxes of cheeze-itz this person is holding on their way out of a store.

I get it. lol

Re: Facebook open-sources Detectron

#37

Post by m_ke »

franciscop wrote: post #36

Does anyone know an alternative that works on RaspberryPi? This states: "Detectron operators currently do not have CPU implementation; a GPU system is required." Even low FPS (3-5) would be acceptable.

You could try tensorflow object_detection api with tensorflow lite

https://github.com/tensorflow/models/tree/master/research/ob...

google also recently put up their mobilenet v2 paper which handles segmentation https://arxiv.org/abs/1801.04381

Re: Facebook open-sources Detectron

#38

Post by deepGem »

m_ke wrote: post #37
franciscop wrote: post #36

Does anyone know an alternative that works on RaspberryPi? This states: "Detectron operators currently do not have CPU implementation; a GPU system is required." Even low FPS (3-5) would be acceptable.

You could try tensorflow object_detection api with tensorflow lite https://github.com/tensorflow/models/tree/master/research/ob... google also recently put up their mobilenet v2 paper which handles segmentation https://arxiv.org/abs/1801.04381

+1 for the Google object detection API. The trained model is quite huge though. 200 MB based on Resnet faster R-CNN. There are creative ways of chunking this model to keep it small.
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