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realsenseai
librealsense
C++2016–2022
realsenseai / librealsense

librealsense

RealSense SDK

8Distinct people
10Mentions
0Explicit recommenders
9.1KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

RealSense SDK

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 5:04:57 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year10 dated mentions

Observed mentions: 2016-01-21 17:32:59 UTC to 2022-01-30 00:44:44 UTC.

01232016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 2 mentions; 2 submissions, 0 comments20162017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20192020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 3 mentions; 0 submissions, 3 comments2022

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC220
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC000
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC101
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC101
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC101
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC211
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC303

What Hacker News says

10 sources
I have an Intel Realsense camera, which sometimes reports the error "Failed to recconect" (there being a typo in the drivers) [1] - that's a pretty unique error, so in combination with the product name that should be a very easy keyword search, right? Especially if I throw in some quotation marks, to make it clear I want a literal match? Yet when I search for realsense "failed to recconect" Google, in its infinite wisdom, returns pages that contain neither realsense nor recconect [2]. They offer me a supreme court opinion, a review of a car dealership, and a facebook church service. Correcting the spelling of a query is one thing - but also completely ignoring other keywords? Even when there are pages available that match the query? [1] [1] https://github.com/IntelRealSense/librealsense/blob/5ff27fca... [2] https://imgur.com/a/okYV5V2
In Tell HN: Google doesn't work anymore for exact matches
My main workstation is too a Raptor Power9 running Void since November 2019, and I’m very happy with it although as the article mentions, “My experience with firmware is that open source does not mean necessarily better, rather the opposite”. OpenBMC (the firmware for the little ARM-based embedded computer that boots the big one) has a number of rough edges. From time to time I submit patches to software to make it work (or work better) on this machine, last week it was these two trivial ones: https://github.com/ciao-lang/ciao/pull/45 https://github.com/janet-lang/janet/pull/915 Typically that’s all that’s needed, in some cases it’s just more of it: https://github.com/oneapi-src/oneDNN/pull/767 But for most things, since it’s Linux, it’s just those small changes: (one of my customers runs the software I write on AIX and that’s a little mo
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re work) https://github.com/IntelRealSense/librealsense/pull/5586 https://sourceforge.net/p/speed-dreams/tickets/1022/ For Rust programs, many packages used i8 for C strings (to interface with OpenGL for instance) which broke when running on ppc64 and had to be changed to c_char, but that’s not a problem these days, I guess because many people now test on ARM. https://github.com/femtovg/femtovg/pull/5 Before Power10 was done, IBM actually asked us Raptor users about proposals for useful machine code instructions to add to it. I replied that I’d like to have hardware UTF-8 de-/encoding but they wanted a more detailed proposal and I never got around to write it. I’m not even sure that this would be worthwhile, but I see UTF-8 de-/encoding everywhere in the code I write and would like it to approach memory read/write speeds. I was very disappointed to learn that they had gone more proprietary with Power10 so I would not have been able to use those instructions anyway. What a pity! This machine still covers my needs so I’m not planning to replace it any time soon.
In Keeping POWER relevant in the open source world
I have an Intel Realsense camera, which sometimes reports the error "Failed to recconect" (there being a typo in the drivers) [1] - that's a pretty unique error, so in combination with the product name that should be a very easy keyword search, right? But no, when I search for realsense "failed to recconect" Google returns pages that contain neither realsense nor recconect [2]. They offer me a supreme court opinion, a review of a car dealership, and a facebook church service. Correcting the spelling of a query is one thing - but also completely ignoring other keywords? I can see why there are so many people posting about the poor quality of Google's search results. [1] https://github.com/IntelRealSense/librealsense/blob/5ff27fca... [2] https://imgur.com/a/okYV5V2
In Is Google Search Deteriorating? Measuring Google's Search Quality in 2022
If I understand https://github.com/IntelRealSense/librealsense/issues/6296 and https://github.com/IntelRealSense/librealsense/issues/5777#i... correctly, what happened is the RealSense developers don't provide a pre-compiled version for 3.8 on PyPI. Python is "broken" in that the C API does not maintain backwards compatibility. (See https://www.python.org/dev/peps/pep-0620/#the-c-api-blocks-c... for a proposed solution.) RealSense is "broken" in that they don't provide builds for all the versions of Python their users use. But that's because "Officially, Librealsense is only currently supported up to Ubuntu 18.04 LTS" Perhaps also your process is "broken" for depending only on pre-compiled builds; the published solution is to build from source. https://github.com/IntelRealSense/librealsense/issues/6296#i... says it's possible. Or "broken"
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for using an unsupported environment and expecting it will work. Software in general is broken. It's amazing that it works as well as it does.
In Python setuptools v50 breaks pip installation on Debian/Ubuntu
That is doable right now. I am only sort of being glib here. I just want to outline what's involved in what people think is a simple task in a spatial system. TLDR: As of right now, your wildest dreams are pretty possible. In the next 2 years, how we compute is going to get strange. Nothing is nearly as simple in an XR environment as a traditional computing one and currently most people don't really want what they'd ask for. Building a simple (useful) XR app makes launching a web product look like assembling a lego set vs. landing on the moon. --------- Imagenet[0] works just fine for the object identification. You would probably want to use RGBd sensors like the kinect[1] or Intel Realsense[2] instead of regular cameras, but tracking like what the Vive[3] uses could also work. The thing you just proposed would involve a network of server
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processes handling the spatial data and feeding extracted relevant contextual information to a wireless headset at a pretty crazy rate. Just to give you an idea a SLAM[4] point cloud from a stereo set of cameras or a cloud from a Kinect2 or Realsese produces a stream of data that is about 200mb a second. Google Draco[5] can compress that and help you stream that data at 1/8 the size without any tuning. Extracting skeletal information from that is really something that only Microsoft has reliably managed to deliver and it's at the core of the Kinect/Hololens products. NuiTrack[6] is the next best thing, but registering a human involves a T-Pose and gets tricky. Definitely you could roll something specific to the application, maybe just put a fiduciary marker[7] or two on a person and extrapolate skeleton from knowing where it is on their shirt. You will also want to be streaming back the RGBd, IMU, hand and skeletal tracking from the headset back to the server. This could help inform and reduce the tracking requirements from the surrounding sensors. Out of the box, you'd probably need a base i7, 64Gb+ of ram, and a couple GTX 1080s to power 4 sensors in one room. The task of syncing the cameras and orienting[8] them would be something you'd have to solve independently. After having all of that, you would have an amazing lab to reduce the problem further and maybe require less bandwidth, but very probably to get where you're going you'd need to scale that up by 2x for dev headroom and maybe run some sort of cluster operations[9] for management of your GPU processes and pipeline. Keeping everything applicable in memory for transport+processing would be desirable so you'd want to look at something like Apache Arrow[10]. At this point you are on the edge of what is possible at even the best labs at Google, Microsoft, or Apple. The arrow people will gladly welcome you as a contributor! Hope you like data science and vector math, because that's where you live now. After getting all of this orchestrated, you now have to stream an appropriate networked "game" environment[11] to your application client on the hololens, but congrats! You made a baby step! Battery life is still an issue, but Disney Research has demonstrated full room wireless power[12]. Now all you have to do is figure out all the UI/UX, gesture control, text entry/speech recognition, art assets, textures, models, particle effects, post processing pipelines, spatial audio systems[13], internal APIs, cloud service APIs, and application build pipeline. The Unity asset store has a ton of that stuff, so you don't have to get in the weeds making it yourself but you will probably have to do a big lift on getting your XR/Holodeck cluster processing pipeline to produce the things you want as instantiated game objects. Once that's done, you literally have a reality warping metaverse overlay platform to help people find their car keys. What's crazy is that you can probably have all of it for under $15,000 in gear. Getting it to work right is where the prizes are currently living and they are huge prizes. [0] https://en.wikipedia.org/wiki/ImageNet [1] https://azure.microsoft.com/en-us/services/kinect-dk/ [2] https://github.com/IntelRealSense/librealsense [3] https://www.vive.com/us/vive-tracker/ [4] http://webdiis.unizar.es/~jcivera/papers/pire_etal_iros15.pd... [5] https://github.com/google/draco [6] https://nuitrack.com/ [7] https://www.youtube.com/watch?v=JzlsvFN_5HI (markers are on the boxes not the robot) [8] https://realsense.intel.com/wp-content/uploads/sites/63/Mult... [9] https://kubernetes.io/docs/tasks/manage-gpus/scheduling-gpus... [10] https://arrow.apache.org/ [11] https://docs.unity3d.com/Manual/UNetClientServer.html [12] https://www.youtube.com/watch?v=gn7T599QaN8 [13] https://en.wikipedia.org/wiki/Ambisonics
In How does the Hololens 2 matter?

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