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deepinsight
insightface
Python2018–2024
deepinsight / insightface

insightface

State-of-the-art 2D and 3D Face Analysis Project

8Distinct people
8Mentions
0Explicit recommenders
30.2KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

State-of-the-art 2D and 3D Face Analysis Project

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, 3:03:16 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 year8 dated mentions

Observed mentions: 2018-03-16 05:47:57 UTC to 2024-07-07 18:33:18 UTC.

0122018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments20182019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2020-01-01 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): 1 mentions; 0 submissions, 1 comments20212022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2024

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
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC110
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 UTC101
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC101
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC202
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC101

What Hacker News says

8 sources
It was literally the bust of a woman, no real nudity. Imagine an inch above cleavage upwards, I suspect the original guy who seemingly tries to please everyone if you check their replies on feedback [1] just wanted an excuse over time to discontinue for a while for numerous reasons (career, ethics & he was the face of it, 20k stars) [2]. (I also wouldn't necessarily want to be associated with something like this similar to the insightface guy due to the potential for abuse and it has probably grown a lot more than he expected [3]) and 90% of the new features were added by henry. The first version of roop was barely a derivation from the example code in insightface [4], it just added a gui. [1] - https://news.ycombinator.com/item?id=36117013, https://twitter.com/s0md3v/status/1663604795524149248 [2] - https://twitter.com/emilyx64/status/16
Read the rest
In FaceFusion: Next generation face swapper and enhancer
Hi, Mattlondon, it's really nice to have your reply. You are asking a good question, the 'Mali GPU' supporting is not for RPi, it's on the board which has 'Mali GPU' as RK3288/3399 or others (MTK/....). For now, the reference code is running on RPi cpu, a light MXNET model do the extracting of face feature, the detection code is also running on RPi, the classifier is on RPi too. The API server is the APP logic server, AWS/MINIO is storage layer. The light model is https://github.com/deepinsight/insightface/wiki/Model-Zoo#34... which running MobileNet as backbone. IF running on Mali GPU, ResNet50 can be used. Inference duration depends on the GPU power. if running on Mali 720 MP2, should be something close to 0.3s.
In Show HN: Open-source Face Recognition on Raspberry Pi 3/4

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