I am not impressed, they could cut 1000% by using: big bawl, pipe, simple mechanical sorting mechanism, and electronic counter.
A Japanese company cut 80% of the time needed to manually count pearls
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Re: A Japanese company cut 80% of the time needed to manually count pearls
#142Nobody cares that this is just an ad? It's got too many paragraphs of bullshit filler for something that's basically "they're taking pictures and counting the pearls using machine learning".
Re: A Japanese company cut 80% of the time needed to manually count pearls
#143I am not impressed, they could cut 1000% by using: big bawl, pipe, simple mechanical sorting mechanism, and electronic counter.
I am not familiar with pearls, but a mechanical sorting mechanism could damage them I think. Also, how is a mechanical sorting mechanism or an electronic counter simpler, cheaper or faster than a photo?
Re: A Japanese company cut 80% of the time needed to manually count pearls
#144Wow, this is such a simple application of ML and it is incredibly valuable. On their website, they charge $100/month per device or $1000/year per device [0] and I bet they're making a killing. [0] https://countthings.com/en/
I wish I could get a bead on how useful ML is. Hackernews makes me think it’s all hype.
Google, the world's most used search engine, uses BERT to power it's queries.
Re: A Japanese company cut 80% of the time needed to manually count pearls
#145Earlier quoted context omitted.
There’s also a technique called “weighing”. It’s a transformation which, by assuming the items are identical, turns quantity from a discrete value to a continuous one with some loss of precision. In many cases measurement times can be reduced my more than 99%.
Cut the snark. And if you check the link, the assumption that items are identical is far off.
Yeah I know. And the use cases of people on a beach, crowded theater, trees in the woods, etc. don't lend themselves to weighing.
Honestly didn't intend to come off as snarky, just clever and amusing. Tough to convey tone -- risk I take I guess. Oh well.
Re: A Japanese company cut 80% of the time needed to manually count pearls
#146The tray used in the demonstration is almost white (beige?). Wouldn’t a black tray (hence darker background and higher contrast) increase accuracy?
Re: A Japanese company cut 80% of the time needed to manually count pearls
#147Wow, this is such a simple application of ML and it is incredibly valuable. On their website, they charge $100/month per device or $1000/year per device [0] and I bet they're making a killing. [0] https://countthings.com/en/
I would not say it's that simple, they do have many trained models with high accuracy. https://countthings.com/en/counting-templates
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Re: A Japanese company cut 80% of the time needed to manually count pearls
#148Hi, there! I'm one of the project managers at CountThings, I'll try to respond to comments here but I guess you can AMA.
What approach does it use? Does it use image segmentation (e.g. U-net) followed by classic image analysis? Or does it get the counts directly from the network?
Re: A Japanese company cut 80% of the time needed to manually count pearls
#149In a an image with sufficient contrast between the foreground and the background, thresholding and using the fast radial symmetry transform[1] should do the trick. I have some really old code that I wrote a few years back that does something similar. I was able to use the same algorithm for counting objects in images captured from a Neubauer chamber [2] and saved countless man hours at my university. Disclaimer: the…
Would a solution like that work for a video feed where you need to make sure you're not double counting as objects move along?
Re: A Japanese company cut 80% of the time needed to manually count pearls
#150Wow, this is such a simple application of ML and it is incredibly valuable. On their website, they charge $100/month per device or $1000/year per device [0] and I bet they're making a killing. [0] https://countthings.com/en/
I wish I could get a bead on how useful ML is. Hackernews makes me think it’s all hype.
Machine Learning is not a single thing that can be useful or not.
It is more like the scientific method. It depends on the data available, and whether something in the arsenal can create something useful.
Most experiments yield absolutely nothing, and some achieve delightfully counter-intuitive useful results.
The criticism on HN -- perhaps correct(1) -- is not that it is hype but that it is not new. Is statistics great? of course, but its been around for decades, perhaps centuries, so it seems strange to proclaim how it will solve problems now.
(1) ML can be distinguished from statistics if you want to. I am not interested in this particular debate myself.