Dive into Deep Learning • Hacker News Board

Re: Dive into Deep Learning

#91

Post by fareesh » Sat, Jan 04, 2020, 7:33 PM UTC

jrumbut wrote: post #61

fareesh wrote: post #30

Earlier quoted context omitted.

Sorry but it was a scenario I imagined and not something that happened in reality. I can't talk about some of the real-world scenarios that I am asked to consult on, so I made up a rather poorly thought-out one.

Something to look at is the classic image processing algorithms that can be effective and more importantly behave predictably. In your example, take a film of the factory floor when it is empty, then once work begins use a approximately human sized/shaped rectangular sliding window and look for areas that exceed a threshold of difference to the image of the empty floor. You can then use that window as input to a clas…

Interesting approach, is this documented in a blog post or tutorial somewhere where something similar is done?

Re: Dive into Deep Learning

#92

Post by fareesh » Sat, Jan 04, 2020, 7:41 PM UTC

asiachick wrote: post #88

newfeatureok wrote: post #28

Earlier quoted context omitted.

I'm somewhat surprised at the responses for this. I believe your issue can be easily solved - have supervisors wear a distinctive color from a non-supervisor. For example let's say it's yellow. OK so now you have yellow wearing supervisors and everyone else. To resolve the issue you have described acquire a month or so of footage, with labels per minute describing how many yellow wearing supervisors and how many peop…

Just passing on info but ANA (the airline company) has colored helmets in their maintenance to facility to distinguish supervisors (color 1) from non supervisors (color 2) and 1st year employees (colors 3) and guests (color 4). I don't know if they do any tracking.

This example was totally made-up.

In my experience related to the type of arrangement you're describing - in reality (at least anecdotally speaking) the helmets are often not worn, or the colors are not enforced, or the colors don't get picked up due to poor quality video.

I deal mostly with third-world countries so safety standards are not always the best.

Re: Dive into Deep Learning

#93

Post by fxtentacle » Mon, Jan 06, 2020, 12:53 PM UTC

rsp1984 wrote: post #81

fxtentacle wrote: post #27

Earlier quoted context omitted.

It used to be. Then the AI fanboys arrived and started treating it like a learning problem. https://arxiv.org/abs/1612.01925 https://arxiv.org/abs/1709.02371 https://arxiv.org/abs/1904.09117 BTW, also the classical algorithms deal very badly with noise and repetitive textures, e.g. a video of a forest in the afternoon.

Ever tried "DIS optical flow" in OpenCV? Works like a charm for me even in challenging conditions.

Not yet, thanks for the suggestion :)

Re: Dive into Deep Learning

#94

Post by Tomte » Fri, Jan 17, 2020, 9:50 AM UTC

dragandj wrote: post #42

mpfundstein wrote: post #41

Earlier quoted context omitted.

Is there a print version (in the planning)? I usually don’t buy ebooks

Only a limited hand-crafted hardcover edition is planned. That being said, you can print a dead tree version from the PDF at your local printing shop (or at home) if you care about the text, and not that much about binding.

If you print technical documents often, I highly recommend a wire-binding machine like this one: https://www.renz-germany.de/produkte/renz-ring-wire/eco-s-36...

I've got a lower-end model, second-hand, still not cheap, but it's so cool.

You get real wire-o binding (not spiral binding!), so your book lays open flat on the table and the pages are right next to each other, not slightly displaced vertically like with spiral binding.