HackerReposA FIELD GUIDE TO OPEN SOURCE
ProSponsor the shelf♧ 0
← Back to top all-time
ageitgey
face_recognition
Python2017–2025
ageitgey / face_recognition

face_recognition

The world's simplest facial recognition api for Python and the command line

Command LineAI & Machine LearningLearning & Reference
Explore on GitHubRead Hacker News discussions
16Distinct people
18Mentions
0Explicit recommenders
56.9KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

The world's simplest facial recognition api for Python and the command line

GitHub

Where it is used

No documented product use was verified in the last source check.

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, 1:49:46 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 year18 dated mentions

Observed mentions: 2017-03-14 00:45:33 UTC to 2025-08-14 08:38:29 UTC.

0123452017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 4 mentions; 4 submissions, 0 comments20172018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 5 mentions; 0 submissions, 5 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20212022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2025

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
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC440
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC211
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC505
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC202
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC101
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC000
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC110
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC101
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC202

What Hacker News says

18 sources
zimpenfish·Aug 5, 2025
I'd check out the OpenCV documentation and examples. This is basically what I use for face recognition in videos[0]; for recognising cars or other objects, you'd probably want to either train your own model or use something like OpenCV's YOLOv3 (example: [1] but you'd need to steal the video reading code from the first link[0]) [0] https://github.com/ageitgey/face_recognition/blob/master/exa... [1] https://github.com/deveth0/python-opencv/tree/master/objectD...
In Monitor your security cameras with locally processed AI
bko·Dec 10, 2020
Not relating to this project, but there's no reason you can't do offline facial recognition. I've blogged about doing offline object detection on raspberry pi and facial recognition is much simpler [0]. I've done it using the face_recognition [1] python package although I never released anything and it works fine. Only catch is you can only process a few frames a second, but unless you're trying to capture faces in fast moving environment, this should be fine. I will note that aws facial recognition is far superior to the python package. If you need accuracy I would suggest an ensemble method where you use an inferior model (python package) to some level of confidence then offload it to the superior model that's off device for the final call and saving down the vectors. [0] https://medium.com/ml-everything/offline-object-detection-an... [
Read the rest
1] https://github.com/ageitgey/face_recognition
In Show HN: Open-source Face Recognition on Raspberry Pi 3/4
caryme·Nov 8, 2020
I've been using ffmpeg's xgrid filter (similar to hstack and vstack, but allows for arbitrary grids) to produce virtual choir videos for my church choir during covid. Here's an example: https://www.youtube.com/watch?v=Oeg9w8X6hrA. A lot of people are producing virtual choir videos right now, but I suspect few use a process similar to mine. I use Audacity to edit the audio separately, then crop the input videos using a face-aware cropping script (which uses https://github.com/ageitgey/face_recognition), then generate a video grid using ffmpeg + xgrid.
In Stack Videos Horizontally, Vertically, in a Grid With FFmpeg
CapricornNoble·Oct 4, 2019
>>>Unless you pin down what you mean by ethnicity, I can't even begin answer. Let's go with common genealogy or phenotype. >>>Ethnicity seems a social construction So in the absence of society you would not be able to physically distinguish between these two gentlemen [1][2] and would classify them as the same ethnicity? You cannot discern objectively-measurable distinctions between the appearances of these two faces? Facial recognition software demonstrates otherwise. [3] Every face has measurements, which cluster with other similar faces. I doubt it would be difficult to map each of those clusters with what we consider an "ethnicity". >>>But, maybe. After all an american indian guy decided to 'identify' as a tiger <https://en.wikipedia.org/wiki/Stalking_Cat>. While that's a very odd decision to me, I'm not going to step in and physicall
Read the rest
y stop him. Would you? Did he receive any LEGAL benefits normally given to large predatory felines? If no, then intervention isn't required. If yes, then absolutely I would oppose it. "Sticking feathers up your butt does not make you a chicken" - Tyler Durden. >>plesse leave politics out of this, ta, it's complex enough. Regardless of her politics, Elizabeth Warren is a public, high-profile figure and a perfect example of an American using their "internal" identity for legal gain. Rachel Dolezal is an alternative example. Both demonstrate that these aren't really hypothetical issues, but present-day issues crossing the spectrum of not only social issues but also medical and cosmetic technology (elective, plastic surgery, skin treatments, etc...). >>>This is about people who feel they don't fit their body and you try to drag in this? I try to keep a long-term, macroscopic view on social issues. But honestly, if I were to elaborate on my position it would be a long, kinda-rambling mess, so I'll table that point of the discussion. >>>And why do you assume I'm from the US? Oddly enough I'm usually fighting the same bias inherent in a US (and especially SFV/SFBA-heavy) website. I'm American but don't live there. So....touché on that one. >>>Final question, have you ever met a trans person? Of course. I live in Asia. Anyone who has spent more than a few minutes in a bar in Thailand, Philippines, or the bigger cities in Japan has been hit on by a trans person. >>>Or understand what they can choose to undergo because they feel so wrong - they can go through a lot, it's not an easy thing. Every human is operating within the restrictions of their physical form. My rackmate at OCS was a short dude (like 5'4") and years later he told me he considered leg extension surgery....the same kind that killed the guy in [4]). Short guys experience all sorts of emotional abuse and nobody really gives two shits about them either. Should my friend declare that he is 6'1" because he FEELS taller? Should we update all of his government documents and forms of identification as such? Of course not. Feelings are ephemeral, fleeting, and subjective. Step off a cliff and say to yourself "I FEEL like I shouldn't fall...I identify as a bird." Does gravity comply? No. Life is hard. Get harder. [1]http://thewarriorfitness.com/wp-content/uploads/2015/09/Warr... [2]https://tinyurl.com/yyoamjl4 [3]https://github.com/ageitgey/face_recognition [4]https://news.ycombinator.com/item?id=21082702
In No evidence that testosterone reduces cognitive empathy
bko·Jul 7, 2019
A single picture is surprisingly effective in recognizing that person in another photo. I've been playing around with a python wrapper on dlib's facial recognition [0] and it's astonishing how it can identify people from just one photo. It's not like other machine learning methods that include training a classifier or even fine tuning a classifier. It works by encoding the persons face to a 128 dimension vector and then using that for comparison. The accuracy from most methods is between 99.2% - 99.8%, but the problem is that the training samples are too easy and controlled. It's sensitive to lighting. Google's most recent paper [1] on Facenet found 99.63% on the easy Labeled Faces in the Wild (LFW) dataset, and an impressive 95.12% on the Youtube faces dataset, presumably a much more difficult dataset. [0] https://github.com/ageitgey/fac
Read the rest
e_recognition [1] https://arxiv.org/abs/1503.03832
In FBI, ICE using state driver’s license photos for facial-recognition searches
bko·Apr 15, 2019
Modern facial recognition uses landmarks, much like humans do. First it identifies a face, which is essentially a flat 2-d plane. It's able to identify locations of the nose, ears, mouth, chin, etc. It then looks for relationships between these features (e.g. how wide is the mouth, how far apart are the eyes, etc). It's a much simpler problem than the general image detection. Imagine how many different types of dogs you can encounter at various angles, sizes, colors, perspectives. For that it's much more of a black box as your model would have to support detecting a dog from behind, side, front, above, sitting down, walking, jumping, standing, dogs with long tails, short tails, long hair, short hair, etc. Now think about a face. Most faces are very much alike. https://github.com/ageitgey/face_recognition
In MIT Researcher Exposing Bias in Facial Recognition Tech Triggers Amazon’s Wrath
jaclaz·Mar 29, 2019
>You have probably seen https://thispersondoesnotexist.com/ by Philip Wang. >But have you ever wondered if they made photos that look like you? Let's check! >We collected the huge dataset of 428526 fake generated photos and extracted their facial parameters with https://github.com/ageitgey/face_recognition. Now you can match your image against fake faces and compare with the closest matches. Enjoy! Maybe it is just me, but how would I go if I wanted to harvest large numbers of "real" photos of "real" persons? Having curious people uploading them to my website could be an easy way.
In Have you been faked?

Showing the 15 most recent of 18 sources. Enable JavaScript to search and browse every indexed mention.

MAKE YOURSELF AT HOME

A few shortcuts

/
Search the collection
?
Open this guide
Esc
Close dialogs and navigation

Your saved repositories and interests stay in this browser.