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Ask HN: What are the best resources to learn computer vision?

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Re: Ask HN: What are the best resources to learn computer vision?

#51

Post by gmiller123456 »

It's a really broad field, so don't expect to get up to speed very quickly. A lot of people have recommended a lot of books already, and I could add to that list. One thing you might think about is Safari Books Online. You'll notice a lot of the recommended books are there, and even though it's a bit pricey, I think you'll find you'd save money by the time you get enough of the books that seem useful to you. You'll also loose nothing by jumping from book to book because they're too advanced/not advanced enough until you find one that's at your level.

I would recommend starting with one of the many OpenCV tutorial books, and maybe work your way through a few of those. Then move into books that cover more of the algorithms behind the library like "Multiple View Geometry" by Hartley and "Machine Vision" by Davies, among many others.

Re: Ask HN: What are the best resources to learn computer vision?

#52

Post by nojvek »

rsp1984 wrote: post #31

I think the question is a little too unspecific for there to be a good answer. The field is vast and depending on which thing in computer vision you want to tackle the best learning paths may vary greatly. Just to give a bit of an overview: Before the Deep Learning Craze started in 2011 more classical Machine Learning techniques were used in CV: Support Vector Machines, Boosting, Decision Trees, etc.. These were (and…

I absolutely love Adrian's blog. http://www.pyimagesearch.com/

He has articles on solving actual problems with OpenCV, dlib and tensorflow. I subscribe to the blog and try to do some of the tutorials myself.

Udacity is another great resource. Their self driving and robotics nanodegrees are great.

I am on the same path as you trying to pivot my career from full stack engineer and add CV + ML skills to it.

When we have decent robot hardware, I want to be the one programming them, not the one getting replaced by them.

Re: Ask HN: What are the best resources to learn computer vision?

#53

Post by nojvek »

zionsrogue wrote: post #25
sphix0r wrote: post #6

OpenCV and http://www.pyimagesearch.com/ disclaimer: not related to any of these

Adrian here, author of the PyImageSearch blog. Thank you for mentioning it, I appreciate it. If anyone has any questions about computer vision, deep learning, or OpenCV, please let me know. In regards to OPs original question, I'm actually working on solving your very problem right now. About 1.5 years ago I created the PyImageSearch Gurus course ( https://www.pyimagesearch.com/pyimagesearch-gurus/ ) with the aim of…

PyImageSearch is absolutely fantastic. We couldn't have got a top spot in an AI hackathon without your blog: https://www.youtube.com/watch?v=OreCICEcQWY&t=2m45s

Looking forward to your book. Keep up the great work.

Re: Ask HN: What are the best resources to learn computer vision?

#54

Post by goxul »

thinkMOAR wrote: post #42
lightbyte wrote: post #37

Surprised nobody has posted http://course.fast.ai/ yet. I've been following along with it so far for the first 4 lessons and it has been extremely helpful in understanding how deep learning works from the perspective of someone who did not have much of any related baseline knowledge except how to program. Jeremy is an excellent practical teacher.

Happy it is interesting for you. I too got this url referred by somebody, and I got excited after their extended intro why, how etc their course different and better then any other. Though after 5 videos i know nothing more then from any other ML/AI guide on the internet then i did before. 99% is only related to image classifying, and i'm simply seeing too many guides for that. If anybody has some good links/videos o…

The author himself said that DL isn't the best option for structured data.

"Certainly I'd pick DL over more linear models for most problems. But I'd pick random forests over DL for most structured data problems."

"Deep learning is best for unstructured data, like natural language, images, audio, etc. it sounds like you may be dealing more with structured data, in which case the Coursera ML course would be a better option for you"

More discussion here - https://www.reddit.com/r/MachineLearning/comments/5jg7b8/p_d...

Re: Ask HN: What are the best resources to learn computer vision?

#55

Post by speedplane »

deepGem wrote: post #34
amelius wrote: post #24

Earlier quoted context omitted.

Imho, deep learning has little to do with engineering, and more with guessing, hoping and praying. But it seems you can often get something to work if you do those three things hard enough.

This has been my experience as well :). Deep learning is a lot of random guesswork, trial and error. I am almost always in the 'brute force' mode. However, in this course, you learn more about the fundamentals of convolutions and backprop. You have to implement your own backprop - not sure of what use that is, given that it's a one line code in TensorFlow

I watched a great video on Tensorflow (link below). It mostly introduces very basic deep learning concepts, but there are a few key moments in the 2 hour+ video, where he explains what to do if something goes wrong. It's definitely not a "science", but with enough experience in deep learning, you can intuit what's going on inside the black box, and there are best practices on what to try next.

For example, he goes through a few examples where a neural net has too many weights, or too little data or improperly connected nodes. All three result in problems, but the problems exhibit themselves in slightly different ways and with expertise you can start identifying them.

https://www.youtube.com/watch?v=vq2nnJ4g6N0

Re: Ask HN: What are the best resources to learn computer vision?

#56

Post by thinkMOAR »

goxul wrote: post #54
thinkMOAR wrote: post #42

Earlier quoted context omitted.

Happy it is interesting for you. I too got this url referred by somebody, and I got excited after their extended intro why, how etc their course different and better then any other. Though after 5 videos i know nothing more then from any other ML/AI guide on the internet then i did before. 99% is only related to image classifying, and i'm simply seeing too many guides for that. If anybody has some good links/videos o…

The author himself said that DL isn't the best option for structured data. "Certainly I'd pick DL over more linear models for most problems. But I'd pick random forests over DL for most structured data problems." "Deep learning is best for unstructured data, like natural language, images, audio, etc. it sounds like you may be dealing more with structured data, in which case the Coursera ML course would be a better op…

many thanks! much appreciated, will read it over the weekend.

Re: Ask HN: What are the best resources to learn computer vision?

#57

Post by Trun_wal »

zionsrogue wrote: post #44
zelon88 wrote: post #41

PyImageSearch by Adrian Rosebrock. http://www.pyimagesearch.com/

Adrian here, author of PyImageSearch. Thanks for mentioning the blog. If anyone has any questions regarding learning computer vision, please see my reply to "sphix0r" below.

Hey, amazing blogs. Currently working on degraded scanned documents. Are there algorithms distinguishable for documents and natural images?

I am using open cv to process the documents, curious if I am missing out chunk of cv algorithms specially for scanned administrative documents (financial,personal documents)?

Re: Ask HN: What are the best resources to learn computer vision?

#58

Post by zionsrogue »

Trun_wal wrote: post #57
zionsrogue wrote: post #44

Earlier quoted context omitted.

Adrian here, author of PyImageSearch. Thanks for mentioning the blog. If anyone has any questions regarding learning computer vision, please see my reply to "sphix0r" below.

Hey, amazing blogs. Currently working on degraded scanned documents. Are there algorithms distinguishable for documents and natural images? I am using open cv to process the documents, curious if I am missing out chunk of cv algorithms specially for scanned administrative documents (financial,personal documents)?

I'm not sure what you mean by "algorithms distinguishable for documents and natural images" -- can you elaborate? OpenCV itself doesn't have builtin functionality to take documents and fit them to a pre-defined template, that tends to be part of a specific use-case/niche of computer vision for document processing. The general idea is to take a document a user has filled out and "fit" it to a blank template, where you know exactly where each field is. That way you can exact the information from the document.

Re: Ask HN: What are the best resources to learn computer vision?

#59

Post by Trun_wal »

zionsrogue wrote: post #58
Trun_wal wrote: post #57

Earlier quoted context omitted.

Hey, amazing blogs. Currently working on degraded scanned documents. Are there algorithms distinguishable for documents and natural images? I am using open cv to process the documents, curious if I am missing out chunk of cv algorithms specially for scanned administrative documents (financial,personal documents)?

I'm not sure what you mean by "algorithms distinguishable for documents and natural images" -- can you elaborate? OpenCV itself doesn't have builtin functionality to take documents and fit them to a pre-defined template, that tends to be part of a specific use-case/niche of computer vision for document processing. The general idea is to take a document a user has filled out and "fit" it to a blank template, where you…

"The general idea is to take a document a user has filled out and "fit" it to a blank template" - I agree point to point. However, I am struggling with templatization due to poor quality of the document images. To process those documents (denoise, super resolution, HE - etc. etc.), the OpenCV algorithms are not working good enough, requires a lot of tuning varying with each document.

So, I was wondering if those algorithms work better for natural images (buildings, people, things etc) than document images (text, graphics) and if so, there must exist algorithms to process such documents I am unaware of.

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