Review: INSTABRICK part identification system
Posted by Huw,
INSTABRICK is a part identification system that was successfully crowdfunded in 2019. Units were shipped to backers early in 2020 and it can now be purchased by anyone.
We did some tests with a prototype unit (when it was called PIQABRICK) a while ago and we've now been sent a final production version to evaluate. As it's not something I'd get a lot of use out of, I sent it to Martin, aka CCC, an expert in part identification. He has conducted some very thorough tests to determine whether it actually works and if it's worth spending €149 on it:
When Huw said that he had an INSTABRICK to review I jumped at the chance. I have been a BrickLink user for about 10 years now and consider myself very good to expert when it comes to searching for previously unidentified parts, especially printed parts and minifigure parts.
So the question of whether a machine is better (both in terms of speed and accuracy) than a human eye is clearly of interest to me. INSTABRICK’s webpage claims that it'll identify any brick in a blank of an eye, so we’ll be testing whether this can be done.
Inside the box
Before we run the tests, let’s look at what you get. In the pack there is an INSTABRICK Top, a USB type-C cable, a piece of off-white greyish card and another piece of card with minimal instructions and a QR code. Further instructions are available after you register and log in. The software is all online, run through a browser. The instructions also indicate that you need to sit the INSTABRICK top on a 16x16 structure built with three walls, 11 bricks high. We’ll come back to those walls and the height later on.
The top itself has seen some changes from those shown during the crowdfunding campaigns. First of all, the camera has been changed from a 5MP autofocus to a 3MP fixed focus (although their website still incorrectly claims it is 5MP).
Looking online, I notice there had been some complaints about this, but this seems reasonable to me. For anyone that has sat in a Zoom meeting where someone’s autofocus webcam has lost focus and continually scans without finding focus, the fixed focus lens seems a good idea especially as the distance between the camera and the objects in the box is fixed.
The 3MP camera also seems to have good enough resolution to work fine for this application. Another obvious change is that the LED lights are now in a circle and pointing downwards rather than on the edges and pointing across. They also shine through a translucent plastic diffuser, presumably to spread the light more evenly across the box.
For my first box, I went with what looks like an albino hedgehog, constructed using mainly very cheap white 1x2 bricks with a pin on the side. Once constructed you put the top on your box, plug in the USB-C cable and connect to your PC/Mac and you are ready to go. You need to register an account on the website and put in the card with the QR code on it, then scan it and the registration process completes.
You then replace the QR card with the off-white greyish card that provides the correct background for the images. It does not work properly if you do not do this. You then put a part into the box, hit scan and it does its magic. Once the box is built, it is up and running within a few minutes. Probably 95% of the total set-up time is spent building the box for it.
Another change from the crowdfunding stage is that it only works with a PC/Mac and does not work with a smartphone or tablet as originally claimed. Luckily, I have a PC not too far from my build / play area and another near my BrickLink storage, although I always use a tablet when it comes to picking orders. This does seem to be a bit of a downside compared to the originally advertised spec but not too bad to overcome.
The tests
On to the tests. Each of my tests will have a number of images associated with it. These are snapshots of the browser window and show what the user sees after scanning the part. Let’s start with some torsos. Given the Italian origin of INSTABRICK, the first one to try is an obvious choice. Here we have the Vitruvian Man torso that was available in the Build-a-Minifigure stations in LEGO stores.
When aligned inside the device, with the arms neatly by the sides, it identifies it with a perfect match. This is a close-up of what is contained in the information box: 
Let’s make it a bit harder on the next few tries by not being so careful …
Clearly, at least in this case, having the torso less well aligned inside the box, or raising one or both arms, or pulling one arm off or even flipping it over all lead to positive results. There are occasionally other parts that it thinks might match, but it gets the correct one each time. Excellent! The database has enough images to work out what we have no matter how it is put into the device.
Let’s try another one, this time J.B. Watt’s torso from Hidden Side, but we’ll also include some other bits this time to see if it gets confused.
In each case, it recognises the torso and also shows a possible match to the figure (although whoever entered the name was a bit lazy), even when a completely different head is on the torso. However, it does not recognise the head when imaged by itself.
Let’s try to confuse it further. The next torso should have dark bluish grey arms, let’s replace them with light bluish grey instead. PS. I am a Bricklink user, so I use their naming conventions.
Again, the results are very good. It found the correct torso (without arms) as the top ranked match. The torso assembly (with DBG arms) was found at position 6 on the list so there was clearly a lowering of the match due to the wrong colour arms. The parts/figures in positions 2-5 were wrong, but at least the torso in the first place is a good start to identifying what we have. Another success.
Let’s give it some more torsos from across a range of themes…
The torsos of Samwise Gamgee (even with incorrect white hands!), Scuba Robin and Obi Wan were correctly identified. The surgeon’s torso was not identified so is presumably missing in the database, but the full figure was identified, so at least that is a partial success and gives a good indication of what we have. I found this was often the case for CMF parts.
However, the torsos of Luke, Leia, Cinderella and Elrond were not identified. Although I have shown a number of successes so far, failures are more common. I tried out over 100 different torsos and about 25% were correctly identified and for another 10% or so the character they came from was identified even if the torso was not. The hit rate for Collectable Minifigures was particularly high.
It does quite well on torsos when they are in the database but then torso assemblies are quite quick and easy to manually search for at BrickLink (as long as they are not modified by switching parts) just by using colours and maybe a couple of descriptors. For example, the last one above (Elrond’s) is pearl gold, has pearl gold arms and light nougat hands, so a BrickLink search for pearl gold torso “pearl gold arms” “light nougat hands” (note the careful use of quotes) cuts down the number of torsos to search through to just 7 as shown below! It is easy to do such a search in under 30 seconds on BrickLink.
However, heads are much harder to search for at BrickLink as they typically only have a single base colour, and the colours of print are often not so easy to identify and coming up with useful search terms is more difficult. So this is where the INSTABRICK might come into its own by massively speeding up searches for random heads.
Unfortunately, this wasn’t the case. I tried 40 different heads and only got 5 positive matches. Few of them seem to be in the database.
Now for some older used 1980’s figures, the sort of thing that frequently come from bulk used lots and are often missing pieces or have had parts swapped out or have been drawn on or prints rubbed off.
The red Forestman was found but the two blue ones were not. The peasant failed although similar prints were found, even though in very different colours, which might help track down what we have here. Note also one of the problems with BrickLink searches in the part names – inconsistent use of terms. The minifigure has a “pouch” whereas the torso has a “purse” even though it is the same design.
The Crusader was obviously rather unsuccessful, showing minidolls that do not look anything like it in either shape or colour. It frequently makes very bad suggestions like this which can be quite frustrating or funny depending on your mood. The threshold for showing possible matches seems to be way too low.
What about the old ghost shroud.
This highlights something else that happens quite frequently. It did not identify it when aligned, or when rotated. But when moved very slightly (between the second and third images), it does suggest incorrect matches, although it does find the newer shroud this time. This indicates that the suggestions if it doesn’t have the match tend to be somewhat random. Why suggest the shroud for image 3 and not for 1 or 2? This seems somewhat inconsistent.
Let’s go for possibly the most beautifully detailed minifigure ever produced: Theoden, from The Lord of the Rings. And what happens if he loses parts, as might happen in a played collection?
We get positive matches for the full figure, missing the helmet and/or armour, and get a match for the torso if the legs are missing. It failed when flipped over and also the head alone did not produce a match. It seems that if we have most parts of a specific figure, it produces good results if the figure is in the database with a decent number of images to work from, and we are sensible enough to put it the right way up. Again, excellent results.
Let’s now go for some custom figures to see what happens as they will certainly not be in the database. Sticking with The Lord of the Rings, here is my custom Eowyn.
It correctly matched both the torso to the Leia figure and the head. A very good result!
What about a more extreme custom, this time Gandalf. Note the hair and beard were originally genuine LEGO parts but have been cut and combined together into a single part.
This time no match at all, but the torso is recognised correctly when the head and the custom hair/beard combined part is removed.
But wait a minute, what else do we see there? It is a blue Forestman. He is in the database after all, but my two blue Forestmen were not correctly identified earlier! That is disappointing.
Here is a similar thing happening again. Green Lantern’s head
What does it think it is? Theoden’s head, even though it didn’t identify Theoden’s head earlier on. Again, disappointing.
One thing that I often read during the crowdfunding stage was that it would tell the difference between old and new greys, between the different browns and so on. Let’s test that out, starting with an old light grey 1x2 brick.
Well, that is not a good start. Let’s change position and orientation.
Here are 10 attempts at finding it (I actually tried it 20 times), moving the brick around. Note that it is actually in the database, as it appears in the 10th image. It appeared once in 20 tries, and when it did appear, it appeared after the coral one, suggesting coral is a better match. This is probably an indication that even though it has been added to the database, there are not enough images of it. Notice also some of the suggestions, these are frequently useless when there is no good match, but there is no confidence score shown for the matches.
Let’s go for an old light grey arch instead.
The results are just as bad. The first time it thought it was a 1950’s black car, the second time a white one! It did get the shape right second time but look at the colour. It thought it was light bluish grey and not old light grey, so a fail on colour recognition. Maybe the old light grey is not in the database and this was the best match when placed in that orientation (but not found at all on the first try).
It also failed to identify a number of other parts, both old and modern, in similar colours. Even if the part was correct, the colour is often wrong. The greys and browns and to some extent blues and greens produced particularly bad results.
Let’s give it another try with an old light grey panel / wall piece.
A black bear, a white bear, Mickey Mouse or a minifigure cape! This sort of result is not uncommon.
What about some more common parts?
It is meant to be able to tell plates from bricks by the length of the shadows, but it could not identify a 2x3 tan plate. It failed on a black 2x4 brick, returning a reddish brown one. It failed on a reddish brown 1x4 log brick, returning the right brick but in dark brown in one case or printed bricks (including a 1x3) on another try. It also failed on many other common parts. Maybe people don’t need to search for such common bricks, but the database seems to be severely lacking here, especially if the intent is to identify any brick.
We’ll end the tests on a fan favourite, Nick Bluetooth. He doesn’t fit in the box, but his head does.
Results: a forklift or a DUPLO teapot!
When it works, it works very well. A major problem though is that it doesn’t work very often. We’ll come back to this later on.
Less than optimal conditions
During the crowdfunding campaigns, a number of people asked why this was not done as a phone app and I recall that the reply was that their research did not give good results due to two reasons: the distance of the parts from the camera needs to be consistent to get the scale right, and the lighting needs to be consistent. So why not test this out. To test the distance, I built the three walled box as instructed, but varied the height away from 11 bricks. Here are the results, starting at 8 bricks high through to 14 bricks high. Obviously, the part appears to get smaller as the height of the box increases.
The system got the right identification for heights between 9 and 13, failing for 8 and 14. There is a reasonably large size difference for the 1x8 tile image at 9 high and 13 high. I got similar results for other parts that are known in the database, tending to fail if too close or too far, but with a reasonable tolerance of about +/- 20%, suggesting that as long as you know what scale to aim for, distance should not be a problem for identification purposes.
What about consistency of light? The first thing I did was remove the walls of the three sided box, which presumably are meant to stop outside light straying into the box. Instead, I built four 1x1 pillars, 11 bricks high. This was less secure and the top fell off if one of the pillars was knocked so I wouldn’t recommend it for stability reasons.
However, for known parts, I got exactly the same results as when there were three walls so any stray lighting was having a minimal effect. This might be because I was doing this in a fairly dim room away from any strong lights.
So what about more extreme lighting conditions? I got my very bright bicycle front light and placed it just out of shot to cause quite extreme shadows and very poor, inconsistent lighting and again tested parts that I know are in the database.
Perfect results again, despite a very bright light source causing extreme shadows especially when the arms are raised.
Of course, images taken for inclusion in the database should be based on both optimal distance and light conditions so they come from a consistent standard. However, for identification purposes, rather extreme conditions still produce matches if the parts are known. And if they are not known, it rarely produces a sensible suggestion anyway under optimal conditions.
No doubt there are other issues with having a phone app instead, such as compatibility on various operating systems, through to pricing/charging for the app. I imagine it would be quite expensive given that when you buy the package it is not just the camera and light top, but access to the software and database, and it is the latter that really makes the system usable.
Does it work?
The all important question is does the system work? I think that has to be answered in three stages, as there are essentially three components working together: the top, the technology/software and the database.
The INSTABRICK top is well-built, it feels really quite sturdy and able to be bashed about a bit, appears to be quality components inside that are all more than adequate for the job and even feels quite tactile with its nice smooth rounded corners. It is perfectly sized to fit with a 16x16 base and doesn’t move or wobble when put on top of the walls as instructed.
If you go with 1x1 pillars in each corner instead of walls, it can be a bit wobbly but of course that is not recommended. The lighting and distance it provides is of course optimal when built according to the instructions. It is possible that the camera is very slightly off-centre – you might just be able to see the base of my wall on the right-hand side of all my images – but this does not affect the performance. The top is a definite positive and a quality bit of kit.
The technology behind the recognition is clearly working, if the parts have enough photos for recognition in the database. However, there are some issues with the software. The first is that although there are help pages, they are not necessarily that helpful. For example, I could not find anything on detailing the difference between a quick scan or a deep scan, and in fact they just refer to a scan in the help.
There is no indication as to when to use one or the other, or why doesn’t it do a deep scan if the confidence scores after a quick scan are low. Another issue I have is the number of matches shown and the information shown for matches. There is no indication as to the score of a match. In earlier descriptions, it indicated that there would be some sort of score shown but this is not present. Especially given some of the very random matches it finds, it would be nice to know what the scores are.
The other issue here is the unnecessary data shown. When I want to find matches, I want to see the parts it thinks are matches so I can quickly scan then by eye. However, these are shown as quite small images and only two on the screen at once. Larger images would be much more useful, especially if you are trying to tell the differences between minifigures with very slight differences, for example.
A lot of the important information such as the DesignID / BrickLink part number could go to the side. There is a lot of wasted space on the screen and a significant amount of this is down to showing the details and a photo or logo of the person that originally submitted that part to the database. While I don’t mind that information being recorded somewhere, there is no need to keep seeing this when I am searching for matches. It is totally unnecessary, especially if it means I can see fewer matches on the page due to so much wasted space.
The final issue is the time taken. The tagline is to identify any brick in a blink of an eye. We’ll leave the “any brick” part until the next paragraph and concentrate on the “blink of an eye”. I was finding that when I got a match, it typically took 9-14 seconds. Where there was no match, it could be as long as 25-30 seconds on a quick scan and even longer on a deep scan. While 9-14 seconds is fast, this is not as fast as a blink of an eye would suggest and not all that much faster than someone that knows how to search at BrickLink although clearly if you have 100s of parts to identify this would represent a good overall speed up, especially for anyone with little to no experience of identifying parts or knowledge of parts. The technology is a positive, the software is acceptable but could be better.
Now the third component and probably the most important given the other two work well - the database. This is really what makes the device survive or fail, and unfortunately it is (currently) a fail. Looking back at past claims, it was mentioned that the creators would have 90% of parts and minifigures in the database by the time of launch (originally Feb 2020, pushed back to December 2020). Well, it is now the start of April 2021, about 3-4 months after the delayed launch and these are the database statistics (note this data is only available after buying and registering):
The green bar (and smiley face) represents the percentage of parts where there are enough photos for the software to identify matches well, the orange bar (and neutral face) where the part has been added and occasionally matches are found but they require more photos to get reliable results and the grey bar where the parts have not been added.
This falls a long way short of the 90% they claimed for the time of release. It is fairly obvious why there are so many parts that do not get matches. They are either not in the database or even when they are in the database (remember it did not identify Theoden’s head or the blue Forestman or the light grey 1x2 brick even though they are in the database), then more likely than not there are not enough images for the AI to work and multiple attempts are necessary moving the part around in the hope of finding a match unless you give up. I don’t think the product is market ready since to work it requires all three components – the physical product, the software and the database – to be ready and one of them is not.
It seems that rather than getting the database 90% ready for the release date as claimed during the crowdfunding period, they are now relying on crowdsourcing the necessary data from paid-up users after release instead. There is a monthly competition and whoever enters the most data wins a LEGO set (42107 Ducati Panigale V4 R for March). To me, there is little incentive to work on supplying data with that model as it is all or nothing each month (although they do say there will be runners-up prizes for April) especially if you are up against someone with lots of time to spare.
Whereas if you could continually add data at your own pace and cash in points for supplying the data for different rewards whenever you feel like it, then there might be more incentive for more people to help populate the database. This is not BrickLink where there is no financial cost to enter parts into the database. You must have already bought into the system to be able to supply photos to the database, so the crowd is very small.
Another important issue that has apparently skewed the database is the “ownership” of the parts. You “own” the part if you are the person that supplies the first picture for that part to the database. If you “own” the part, then your name and photo or logo get shown on search screen when that part is a suggested match.
You also get substantially more prize points for the first photo and linking it to the part than for adding any subsequent photos that are necessary for the matching algorithms to work efficiently. This seems to have led to a race to “own” the parts in the database without submitting enough photos for the algorithms to work properly. This can be seen by the size of those green and orange bars.
For every three parts added, roughly only one has enough photos. There is even a prominent league table when you log on for who “owns” the most parts. Maybe they need to change the process so that you only “own” the part once there is enough data to create reliable matches, rather than just adding it to the database without sufficient data. Otherwise, it seems most parts will be added with insufficient data when relying on crowdsourcing.
There is another issue of sloppiness and inconsistency in the part names. Existing parts seem to have been taken from an old version of BrickLink's database but have lost the capitalization (for example, king theoden and not King Theoden) and also appear with outdated colour names in some cases (for example, one of the bears has medium flesh in the name rather than medium nougat, this change was made back in Feb 2020 at BrickLink). Newer (and presumably future) parts appear to have no link at all, for example, the Hidden Side partial figure I scanned is called “J.B. Watt (Large smile / annoyed)” on BrickLink, but here is just “j.b.”. Inconsistencies in naming will make comparisons difficult, especially when there are multiple variations of characters.
Is it worth it?
The final question is of course is it worth it (the price is 149 Euro). In the current status, the answer is almost certainly not as the database is too poorly populated to be of any use, with less than 15% of parts/minifigures reliably identified when scanned going up to about 35% of parts/minifigures known so might be matched if you are lucky or don’t mind repeatedly scanning moving it slightly each time.
Let’s assume that the database does get close to fully populated. Then who would use it? It is fun to use at least for a few hours, as the software magically identifies on screen what you put into the box (at least when it works). Therefore, people that like playing with this sort of technology would probably get both use and some fun out of it, even if they don’t really need it. I cannot really see it being a valuable tool for collectors/builders who tend to know what parts they have and use frequently.
Similarly, it is probably not much use for BrickLink sellers that sell new parts as they have a list of the parts when parting out new sets and so identification is not necessary. However, I can imagine it would speed up identification of parts for BrickLink sellers that sell mainly used parts and buy mixed up collections.
Whether the cost is justifiable is another matter. I would expect that most of the larger, used part BrickLink sellers with experience should be able to identify at least 90% of a typical mixed up box of LEGO parts within a few seconds per part or, for the majority of the remainder, to be able to find them quickly using a search at BrickLink.
There are often unknown printed parts or minifigures where parts have been exchanged that are difficult to identify and this device may help speed up the identification and processing of such parts. Although any seller will need to be turning over a very large number of parts to justify the 149 Euro cost of the device for identifying maybe just a few percent of the parts they handle.
I imagine it would be useful if someone has a lot of printed parts, and they are not very experienced at searching BrickLink, or they use inexperienced staff to identify parts, and especially where there are many similar designs on a single colour part such as for minifigure heads. Similarly, it may well be useful for someone that buys a lot of mixed up minifigures and needs to sort them out as at least there with the relatively high value of the minifigures it could be worth investing in the cost of the INSTABRICK.
That said, uploading a photo of unknown parts to the BrickLink forum or the Brickset forum will get them identified, typically within an hour or so and for free.
Right now though, I would not recommend buying it. It remains to be seen how fast the database will be populated, and it becomes more reliable.
Thanks to Instabrick for supplying the unit for test. All opinions expressed are my own.
148 likes
41 comments on this article
It seems like a cool idea, but I think it’s gonna need some work before it becomes affordable.
Thank you for such a thorough review. I didn’t even know such a thing was in the works but it’s neat now that it’s here. I’m not sure how much I or anyone I know would really use it tho
Thanks CCC, great review. The product certainly is a work in progress, I just hope it doesn’t fail/get scrapped before it actually becomes a useful tool.
Pretty much what I said when I saw the prototype that its overall just a gimic that'll ultimately not work well and that could have been built into a phone app given the height and lighting didn't affect it too much.
Definitly not worth the price for someone without an extensive collection that needs mass sorting, IE , your average lego fan or AFOL. Nore worth it as a speed sorting device given the number of fails it had.
Concept is brilliant but it just hasn't been worked out properly. Cheers for the review mate
Brilliant review!
Brilliant Brutally honest review of the product!!!
Please avoid Instabrick at all costs, it's been a big waste as a backer of it. Huge flop of a product.
Keep your eyes on a product called Bricklyapp, currently for Apple devices. Scan bricks with your phone and have better results than this "Brick" of an identification tool. They are on Facebook as Brickly or add in to address bar after dot com/bricklyapp
Https://www.facebook.com/bricklyapp
That is not a Duplo teapot.
It was actually a bit of a jump scare.
Thanks for the honest review. I've considered buying this for the geek factor, but feared it would be just as you described.
At the very least, I'd like to be able to plug their camera into my phone or tablet. I don't need to use my own camera.
@Aib84e said:
"Keep your eyes on a product called Bricklyapp, currently for Apple devices. Scan bricks with your phone and have better results than this "Brick" of an identification tool. They are on Facebook as Brickly or add in to address bar after dot com/bricklyapp
https://www.facebook.com/bricklyapp "
Interesting. I'll borrow the wife's phone and have a go.
Although I have the utmost respect for the Instabrick team, whom I met a few years ago, I do think the product is flawed.
- There should be no need for dedicated hardware. They claim pictures taken with a phone are too variable in terms of distance from brick, lighting, colour balance and so on but that just needs more advanced AI to overcome
- The image database was always going to be the Achilles' heel and the entire system is only as good as it. I personally think it's unreasonable to expect paying customers to populate it: that's not what they signed up for.
The ultimate system will use nothing more than phone and LEGO or BrickLink parts images for identification and I suspect that is not too far away.
I have no need for this, especially at that price. It would ruin the enjoyment and satisfaction I get out of identifying random parts on Bricklink and finding out what sets they belong too. I still discover parts and sets that I didn't know existed.
I bought one of these via Kickstarter when they launched and was looking forward to using it, but was let down by the low success rate of the scans.
There was a fault with the camera lens, where small pieces of plastic where loose in side the camera housing and would show up on the pictures, unfortunately this was never rectified by the Instabrick team.
Have you tried a trip of goats in the contraption yet?
An interesting concept but at the end of the day you can't beat the human eye/brain in recognising pieces. Just as Police forces use humans in identifying criminals from photographs as humans are better than software at facial recognition.
Will it ever be able to identify the versions of pieces from different time periods? That ghost shroud was one of the more obvious differences, which means they will probably never be able to identify more complex differences. e.g. solid studs and hollow studs.
Plus there are far cheaper ways of finding out what minifigs/sets the pieces are from on the internet.
Brickset/Bricklink or even just ask someone.
I'm glad it could see the forestman for the trees, if only barely!
I may be lucky in this regard but between my decent enough knowledge of the brick, experience with the Bricklink catalog, and the combined knowledge of my friends in our LUG, this device is solving a problem that I don't have (and suspect that other hardcore fans don't have either). Add to this the fact that we likely make up the target audience, I can't see this being a successful venture. Pile on the honest review from above and this definitely doesn't seem like something that will do well at its current price and success rate of identifying parts.
Reminds me of that "Identifying Wood" meme.
Identifying bricks: yep, it's a brick.
I don't get why the camera is not angled in one corner to get real height information instead of relying on shadows. I also don't understand why they didn't print the most important shapes as positioning help on the bottom to also identify the group of brick more easily, for example torso would always be top left, standard bricks center, etc ....
It feels like this might have worked as a free app for phones that wasn't attempting to monetise anything, so that the crowdsourcing of parts images was open to anyone who wanted to contribute.
The target market for the device seems confused - you'd have to have a lot of parts to make it worthwhile while also not having the ability to do the search yourself more quickly and I would have thought the crossover wasn't that large between those two factors.
Also, the people who'd want to spend money on this will be the most hardcore AFOLS who probably already know all of the colours and part numbers anyway for the most common parts, meanwhile the rarest parts and printed parts are maybe less likely to be in the database meaning the very pieces that you might want it to be able to identify will be the ones it is least able to correctly show.
Nice Gandalf custom! What parts did you use, and how did you modify them for that?
"ITLLTAKEAWHILEBRICK part identification system"
Everyone has a smartphone these days,why not make an app and release it for Android & iPhone and get a whole more bunch of customers.
Sure, Google Lens might work but you do get a whole lot else than Lego when you try to identify a Lego piece using Lens.
Great idea, a lot of DIY construction of a box that might really not be needed
I don't understand why they make an entire scanbox while you could just develop a good working app that can be used on any android or IOS device with a decent camera. I would welcome such an app and would gladly pay for it. I do use Google Lens but that's a bit of a hit and miss when it comes to identifying lego parts and figures.
or I can use google lens and have almost same results for free... still not 100% but it found the torso and the head
with no much looking I found both bat lord and caste dude that I have on my desk, recognized the minisets or figures or torsos... 2 older ones
I will stay with google images and then forums when it fails when I have unknown figure
As somebody who has done a little work on machine learning, I'm not surprised at all that the poor database produces poor results. What is surprising is the lack of a confidence value. These are typically easy to calculate or estimate from machine learning algorithms. Perhaps the values are so low they make the product seem worse?
Thanks for the honest review.
The most comprehensive review I've ever seen on Brickset, and that's saying something! I think you may have just killed this product, but as you correctly point out - they've failed to deliver the database which is where this product lives or dies.
All of the tools needed to make a working phone app with a 3D parts library exist, and as far as I can tell there are several small scale projects ongoing with this approach. The hangup with using the 3D parts database lies with the need to identify decorated parts, which play little if any role in the 3D information of a part. With all respect to the designers of this product, I feel that INSTABRICK was obsolete before it even came to market, and the effort to populate it's database is just another independent project to support a system that will be forgotten within 5 years.
At this point in the niche of LEGO part ID systems, there is perhaps a need for printed part databases that stand apart from the general scope of an all-encompassing LEGO database.
My favorite part of the article: "Let’s go for possibly the most beautifully detailed minifigure ever produced: Theoden, from The Lord of the Rings."
I backed it on Kickstarter. When I put my enclosure together, I installed it and went to work identifying. I have a HUGE unsorted collection and was looking forward to this. But out of thirty-odd parts I attempted, the only parts successfully ID'd were the minifigs (and only the complicated ones of those, not the bog-simple early space ones, for example), so I tried another large handful of very simple pieces, e.g., 2x4, 2x8 and 2x6 bricks and plates, as well as 1x of the same. Again, NO successful IDs. Some of the "suggestions" reminded me of Peppermint Patty's attempts at math: "Lebenty-seven? Twelvety-two?" I regret the money I put into this. I could've bought some Lego instead, and should've.
putting aside the question of does it work or how well does it work, the bigger question to me is why or when would a real LEGO enthusiast even need this? maybe to ID a random minifig or printed tile or something.
not something I'd ever see investing in
Weird, I was just thinking about this yesterday... Huw, did you set a mind reading algorithm?
Am I the only one thinking it would be fune to see what this thing made of some clone bricks?
I got mine from the Kickstarter program, and have used it quite a bit for identifying minifigure parts. They definitely over-promised and under-delivered on the database, but it is slowly improving. I think they would do a lot better getting the database populated if they switched the rewards from a once-a-month prize for the most submitted to saving points that could be cashed in on demand, as was suggested above. I'd certainly spend the time to submit more parts if there was an attainable reward for it, and with the current plan it is just not possible.
Great review!
I got this system as well, and found very similar results. Disappointing results. The thing that really surprises me is how poorly a job it does and matching basic bricks.
Also, lets say they get the database up to par, who is paying for the band width and hosting of the web services needed to keep it running. Currently, once you make the hardware investment the system is free to use. I am not sure how many you would need to sell every month to keep it afloat. I am also sure that I would not pay a subscription to use the system either. Ads?
@alstba:
There are sites out there that generate fake pictures of people that look very convincing. Fake pictures of dogs or cats are also a lot better than you'd expect. It's really just a matter of time and effort. Humans have an easier time than computers, sure, but every human needs to learn the entire parts database separately, where something like this could be continually improved by one person and outperform most of the people who would be likely to use it.
Currently, the most reliable method of identifying parts (especially minifig parts) is to just post a picture to the Bricklink forums and wait for the people who frequent their forum to scramble to be the first to post a correct ID. When it works, it works great. The problem is that not every minifig part is guaranteed to be recognized just due to the sheer volume of prints involved (unprinted parts are usually pretty easy to get answers for), turnaround can take some time, and heads especially can be identified wrong if they're too similar.
Isn't this basically Brickink's database in a box, but a much worse and less accurate version of it?
@CCC said:
" @dougts said:
"putting aside the question of does it work or how well does it work, the bigger question to me is why or when would a real LEGO enthusiast even need this? maybe to ID a random minifig or printed tile or something.
not something I'd ever see investing in"
As noted above, I think really only for identifying very mixed up lots of printed or minifig parts quickly. I find heads especially hard (time consuming) to find so if you have 100s to sort it could speed up the process even if you can identify them manually but slowly."
I think the interest in this kind of products would be the fast entry into a system, like scanning parts to fill an inventory. It's like a barcode: you can usually read the number on some barcodes, like books, and type it into your computer, but when you have to maintain a library, it's much faster to just scan it. Same for LEGO parts, if the database follows...
After fulfilling the main purpose: to identify almost any part, I think it would be useful if it could distinguish between different mould types. If ever I wanted an Instabrick, that would be the most important reason.
I feel compelled to counteract the negative comments above.
I was an early backer and I'm using this product for 4 months now.
After the release of the product, Instabrick made a lot of adjustments to the website and the software, all through feedback from users.
They also have set up a Facebook group for Instabrick users. There were complaints as well as suggestions. Instabrick has proved to listen to all comments carefully and made numerous alterations to the software since then. (This is something I rarely see at other suppliers - the first coming to mind is LEGO itself).
The practical usability of AI (Artificial Intelligence) for image recognition is hugely overestimated by many people. Not only here --where it is about LEGO parts recognition-- but also when it's about to using CCTV footage for identifying persons by the police.
About scanning and using AI to interpret the results:
a. it is not simple as one might think -- there's a lot of technology involved
b. the database of LEGO parts is really gigantic and is changing daily; you need pictures to add all those parts, in every angle
c. it is suggested that there are all kinds of apps that (could?) do better with a mobile phone. Well: which one are you talking about? Name and URL please. Until now I haven't seen any of these apps, so please don't judge Instabrick by apps that are not yet on the market (and haven't proved their existence).
My conclusion is that I don't think the review is fair.
Instabrick is not set up to recognize combined parts such as the mini figures that CCC put under the scanner with different arms and hands.
It makes sense that the scanner will not recognize this because it was not created for that purpose in the first place. Remember the fact that 6 2x4 LEGO bricks Lego bricks can be combined in 915103765 ??different ways.
CCC said about himself "consider myself very good to expert" but this product is not meant to be a a tool to satisfy or challenge the expectations from an 'expert'.
Until something smarter or better is developed and proven to be better, I'ld like to give the nice people who developed Instabrick support rather than the many negative comments that were posted above.
I can find all my bricks in seconds on Rebrickable, as fast as putting it in here.
The REAL THING I want is to have this, working really fast, with a SORTING MACHINE. So I can throw a disassembled model in a bucket, and have it sorted out in an hour or so.