[HN Gopher] DeepFace: A lightweight deep face recognition librar...
___________________________________________________________________
DeepFace: A lightweight deep face recognition library for Python
Author : serengil
Score : 231 points
Date : 2025-01-03 12:03 UTC (3 days ago)
(HTM) web link (github.com)
(TXT) w3m dump (github.com)
| bn-l wrote:
| Hey good post. I enjoy your blog also.
| aussieguy1234 wrote:
| how accurate is the age detection? i.e. lets say you have someone
| who looks much younger than their age, would this model be able
| to detect the persons actual age?
| ted_dunning wrote:
| Check out the README. They comment on the accuracy.
| Refusing23 wrote:
| i would assume it CAN Be accurate if people 'look their age'
| but of course you can easily have someone who looks younger or
| older than their age that skews the overall etimate
| barrkel wrote:
| It depends on the quality of the image. It's most accurate for
| a square head-on photo, like a passport photo, and can be
| wildly off for occluded or angled photos. It's more accurate
| for people under 30, for older people it often underestimates
| age.
| michaelt wrote:
| For most machine learning systems, "performance equivalent to
| an expert human" is the best you can expect - simply because
| it's learned from training data labelled by expert humans.
|
| So if a person looks much younger than their age in the
| judgement of an expert human, I wouldn't expect the model to do
| any better than that.
|
| You should also know a lot of work in this area relies on
| photos of celebrities scraped from the internet - which is much
| easier than getting loads of labelled images of normal people
| in normal situations, which would be a total hassle practically
| and legally.
|
| Of course that has some benefits - if you know the celebrity's
| date of birth and the date of the photo, you don't need to rely
| on human labelling to know the age of the person in the photo!
| But it has the major disadvantage that if your application
| doesn't involve professionally made up people with movie star
| looks in evening wear on red carpets - you might find real
| world performance falls short of the benchmark claims.
| bangaladore wrote:
| > For most machine learning systems, "performance equivalent
| to an expert human" is the best you can expect - simply
| because it's learned from training data labelled by expert
| humans.
|
| However, this is one of the few cases where presumably the
| data _could_ be perfect, far exceeding the ability of a
| expert human.
|
| Some things have no ground truth. For example, masking
| objects for training vision object detection models. Does the
| object end at this pixel or that one?
| bishes wrote:
| Love this package. has a bunch of functions for most face
| recognition, detection and feature extraction purposes. love the
| readme.md docs for familiarizing with the basic features. PLUS it
| offers different models(backends) for the tasks which lets you
| try out a bunch of approach for the same task without writing a
| custom function
| rahimnathwani wrote:
| I'm curious whether others here are working with supervised
| dimensionality reduction for face embeddings, particularly using
| single-task or multi-task learning approaches.
|
| While clustering tends to perform better after dimensionality
| reduction, selecting the optimal dimensions depends heavily on
| your specific use case. This makes it more complex than simply
| applying PCA or t-SNE.
| woodson wrote:
| If you have labelled data, you can try linear discriminant
| analysis (LDA; also known as canonical discriminant analysis),
| which maximizes the between-class variance while minimizing the
| within-class variance to best separate different classes by
| projecting data onto a new space that maximizes class
| separability (for whichever classes help your specific use
| case).
| highcountess wrote:
| Quite curious how no one ever talks about "responsible use of
| facial recognition" or policies to control the use of facial
| recognition, as it totally pervades and destroys the ability of a
| person to remain anonymous, at all.
|
| It's always curious to me how the peasants always seem eager to
| facilitate the interests of the monarchs to oppress them rather
| than their own interests to remain free from control by the
| narcissistic psychopathy of the ruling class prone to tyranny.
| What do you do as a peasant once you've closed the trap you
| created and led yourself into? I guess maybe more accurately
| would be to say that it is the aspirational minor nobility that
| facilitates the creation of the structure that serves the
| creation of oppressive, top down structures. It's an odd human
| characteristic.
| planb wrote:
| Your criticism seems somewhat misplaced. An open-source facial
| recognition library enables the peasants to wield the same
| tools that the monarchs already have at their disposal. The cat
| is out of the bag, and there's no putting it back.
| isodev wrote:
| We can ban the stuff until such time when we truly need it.
|
| Doesn't help with the climate crisis? No. Does it help with
| any of the ongoing health threats? No. Does it help hungry
| people finding food and healthcare or somehow advancing
| science or any cultural benefits? No.
|
| Does it consume vast amounts of water and electricity to
| facilitate "bad example of humanity" use cases? Oh yes.
|
| Just feel our priorities are not where they should be.
| planb wrote:
| So we as humanity should stop all actions that are not
| directly solving the worlds largest problems (at least if
| there might be slightly negative side effects)? And what's
| up with the energy and water consumption argument. I accept
| this for LLMs maybe, but not for a local python script that
| runs on consumer hardware. Should we stop playing video
| games, too?
| DrillShopper wrote:
| > Quite curious how no one ever talks about "responsible use of
| facial recognition" or policies to control the use of facial
| recognition
|
| That's because that debate has already been lost starting in
| about 2000 to 2001. 9/11 was really the last nail in that
| coffin.
| Clubber wrote:
| Post 9/11 made everything shitty. I feel bad for people who
| didn't know life before it; now it's the normal.
|
| I would imagine other milestones for new and improved
| shittiness is the drug war, 1993 crime bill, prohibition,
| Woodrow Wilson and WWI, etc.
| qchris wrote:
| Respectfully, I think it's more likely that you're just not
| personally plugged into and/or have your awareness tuned to
| them but those conversations are definitely happening. There's
| not a single consensus (at least in the U.S.), but discussion
| definitely occurs and in many cases has led to concrete action.
|
| [1] https://www.npr.org/2021/05/07/982709480/massachusetts-
| pione...
|
| [2] https://www.nytimes.com/2019/05/14/us/facial-recognition-
| ban...
|
| [3] https://www.wired.com/story/face-recognition-banned-but-
| ever...
| isodev wrote:
| There is the EU AI Act which heavily regulates the use of
| facial recognition, but I feel that we as "the people in tech
| who makes these things" should be a lot more conservative in
| creating frameworks, abstractions and generally
| advancing/facilitating facial rec use.
|
| It's even more shocking as this library also incorporates a
| great deal of cultural bias. e.g. gender, emotion are
| attributes which vary a lot more than what the models allow
| for.
| theanonymousone wrote:
| I somehow miss the time when face recognition was the only
| "controversial" area of ML/AI.
| liamYC wrote:
| How do you measure positive and negative societal impact of this
| technology?
|
| I find mobile phone face unlock so useful, giving every citizen
| the power to use face recognition could be better than a few
| people, robots that identify someone and give them lifesaving
| medication are great (but the opposite, robot assassin can also
| be created). I guess it comes down to good people building good
| tools. Humans are generally kind and empathetic
| TheRealQueequeg wrote:
| Yet also short sighted hairless apes with all the genetic
| programming that comes with, for better AND for worse.
| babayega2 wrote:
| Very nice package. I used it recently for a project where I
| needed to detect faces in images as tasks with celery [0]. I
| wonder if there is an equivalent for OCR.
|
| [0]: https://github.com/srugano/facematch
| barrkel wrote:
| The performance is focused on correctness and the APIs work with
| individual images. The underlying models can be run with batches,
| but you need to extract the architecture code to run directly. As
| a result, while I started with DeepFace, I mostly just used the
| models.
___________________________________________________________________
(page generated 2025-01-06 23:02 UTC)