Live data from Hacker News

How I failed to replicate an $86M project in 1 line of code

medium.com

41–50 of 50 posts

Re: How I failed to replicate an $86M project in 1 line of code

#41
post #39

Earlier quoted context omitted.

The Victorian police system was first running in cars on public roads in 2012. No doubt there are plenty of solutions available today that have been developed since then, but they probably weren't considered at the time. That $86m has covered development of the software and hardware and at least six years of running costs for the program. So yea, I'm sure $86m sounds like a lot when you compare it to some random piec…

The first ALPR systems were deployed in the late 1970s. Fixed camera systems were rolled out in Australia in 2005... So.. ALPR is not new. In 2012 there were multiple systems available. 86MUSD seems like a lot to adapt existing research or existing systems. Even if that includes acquiring/maintaining several vehicles. Maybe the whole project is being mischaracterized. Perhaps it included requirements completely unrel…

For a start, it's not USD (why on earth would an Australian organization talk about costs in USD?). And of course we know it includes requirements completely unrelated to ALPR, it connects to a bunch of existing databases and systems to do live tagging of stolen vehicles, vehicles owned by people with an active warrant or suspended license, etc.

Re: How I failed to replicate an $86M project in 1 line of code

#42
post #39

Earlier quoted context omitted.

The first ALPR systems were deployed in the late 1970s. Fixed camera systems were rolled out in Australia in 2005... So.. ALPR is not new. In 2012 there were multiple systems available. 86MUSD seems like a lot to adapt existing research or existing systems. Even if that includes acquiring/maintaining several vehicles. Maybe the whole project is being mischaracterized. Perhaps it included requirements completely unrel…

For a start, it's not USD (why on earth would an Australian organization talk about costs in USD?). And of course we know it includes requirements completely unrelated to ALPR, it connects to a bunch of existing databases and systems to do live tagging of stolen vehicles, vehicles owned by people with an active warrant or suspended license, etc.

In 2012 USD a Australian dollar were basically 1 to 1 exchange rate. So it doesn't really matter does it? As to why I might expect it, well... USD is pretty much the international standard, so on an international website I often expect things to be quoted in USD...

Right... "connecting to a bunch of existing databases". Does not sound like it's worth 86MUSD to me. But there we go, I guess we just disagree on this point.

Re: How I failed to replicate an $86M project in 1 line of code

#43
post #15

Earlier quoted context omitted.

This requires a vehicle to be right in front of the (police) car. Not very practical as most of the license plates you get to scan will be in other locations of the video - you know, since the car in front of you may be there the next 10 minutes whereas cars drive past you and are parked to the side all the time.

you could narrow it 1/3rd at least without really affecting results at all, then include the 10x improvement from skipping frames, since you really don't need that many. The world doesn't move that fast.

Actually, the world (the part of it you're interested in, i.e. the license plate) does move that fast, relative to the camera, in terms of pixels/s. You need 10fps for patrol car ALPR to work well.

Source: I've worked with ALPR for 7 years.

Re: How I failed to replicate an $86M project in 1 line of code

#44
Whether the actual project is worth exactly $1 or $86 million is not the issue. Not even whether a $1/67 lines of code can replicate a $86 million project.

The real substance -- and the first posts hints at it -- is that government (and private sector) projects are more often than not many times more expensive than they should be.

Sometimes because they are overengineered (in 2005 it would be 200 Java programmers building a EJB/SOAP/XML monster that requires 10 workstations to run), other times just because they can (charge more). The same way health related projects and vendors can charge a ton for trivial stuff (even plain plastic syringes).

In many countries, it's also because the bigger the project, the more greedy intermediaries can get a bite.

Re: How I failed to replicate an $86M project in 1 line of code

#45

Earlier quoted context omitted.

Sounds like you're arguing a different point. My assumption was that 'x' == "86 million" AND 'x' == "the amount it costs to develop the software". So, I would just replace "86 million" with "actual cost of developing the software".

Yes, I was arguing that your assumption was wrong.

"straw man" - an intentionally misrepresented proposition that is set up because it is easier to defeat than an opponent's real argument

Re: How I failed to replicate an $86M project in 1 line of code

#46

What if they created the 57 line project, and spent $86 million to improve OpenALPR?

The problem isn't ALPR, the problem is the imagery. You must calibrate your cameras and take a few steps to get quality images, or it won't matter how what software you use.

Re: How I failed to replicate an $86M project in 1 line of code

#47

Two problems: 1. You've shown the success of OpenALPR isn't perfect, but I'm sure the closed source alternative isn't perfect either. It might be better, but is it $86 million better? 2. If we spent $86 million on developing OpenALPR, it would be an incredible product that everyone could use, without paying so much to the overhead of an executive structure.

YouTube-encoded video is going to give relatively awful results, no matter what vision software you put it through.

Good cameras, lenses, and camera placement will make or break a project like this.

Re: How I failed to replicate an $86M project in 1 line of code

#48

Earlier quoted context omitted.

you could narrow it 1/3rd at least without really affecting results at all, then include the 10x improvement from skipping frames, since you really don't need that many. The world doesn't move that fast.

Actually, the world (the part of it you're interested in, i.e. the license plate) does move that fast, relative to the camera, in terms of pixels/s. You need 10fps for patrol car ALPR to work well. Source: I've worked with ALPR for 7 years.

You just need a short exposure, blur is not related to framerate, it is related to exposure time.

Re: How I failed to replicate an $86M project in 1 line of code

#49

I don't understand the hate that's being directed at this article. This author isn't the person basically said, "LOL. I'll string together some python in an afternoon and do it." This author tried to replicate the "How I replicated an $86 million project in 57 lines of code" article, and unsurprisingly came to the conclusion, "No, he didn't."

Well, YouTube-encoded video is a severe mistake and it was his assumption that this would be representative of video out of a commercial camera.

It is not.

The camera is also not calibrated. Text recognition does not work well on video whose distortion characteristics are not known.

I am not at all surprised that this is his result.

This morning I calibrated my dashcam and used OpenALPR to replicate this, and I got FAR better results than this blogger.

At the end of a 30-minute section of heavy traffic, I had many hundreds of license plates with 95% confidence or better. I do not have a way to verify the plates automatically, so I don't know how many of those are actually correct.

I filmed at 2560x1440 at 30fps.

Re: How I failed to replicate an $86M project in 1 line of code

#50

I don't understand the hate that's being directed at this article. This author isn't the person basically said, "LOL. I'll string together some python in an afternoon and do it." This author tried to replicate the "How I replicated an $86 million project in 57 lines of code" article, and unsurprisingly came to the conclusion, "No, he didn't."

Well, YouTube-encoded video is a severe mistake and it was his assumption that this would be representative of video out of a commercial camera. It is not. The camera is also not calibrated. Text recognition does not work well on video whose distortion characteristics are not known. I am not at all surprised that this is his result. This morning I calibrated my dashcam and used OpenALPR to replicate this, and I got F…

And all of this is true of the original boastful post, but yet no one was suspicious of those results.
Post reply on HN