ELelliottcarlson·Apr 19, 2023
Have you looked at https://github.com/facebookresearch/segment-anything ?
In Ask HN: AI to study my DSL and then output it?facebookresearch
segment-anything
Jupyter Notebook2023–2024
facebookresearch / segment-anything
segment-anything
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
21Distinct people
24Mentions
1Explicit recommenders
55.1KGitHub stars
What to know before exploring
What it is
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
GitHub
Where it is used
No documented product use was verified in the last source check.
What people are saying
Yeah, they are great and some of the reason (up the causal chain) for some of the work I've done! Seems really fun! <3 :)))) Facebook's Segment Anything Model I think has a lot…
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Also in these discussions
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This week on Hacker News
Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 5:05:26 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 month24 dated mentions
Observed mentions: 2023-04-05 13:26:52 UTC to 2024-06-04 15:22:31 UTC.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| Apr 2023 | 2023-04-01 00:00:00 UTC | 2023-05-01 00:00:00 UTC | 17 | 2 | 15 |
| May 2023 | 2023-05-01 00:00:00 UTC | 2023-06-01 00:00:00 UTC | 2 | 0 | 2 |
| Jun 2023 | 2023-06-01 00:00:00 UTC | 2023-07-01 00:00:00 UTC | 0 | 0 | 0 |
| Jul 2023 | 2023-07-01 00:00:00 UTC | 2023-08-01 00:00:00 UTC | 0 | 0 | 0 |
| Aug 2023 | 2023-08-01 00:00:00 UTC | 2023-09-01 00:00:00 UTC | 1 | 0 | 1 |
| Sep 2023 | 2023-09-01 00:00:00 UTC | 2023-10-01 00:00:00 UTC | 1 | 0 | 1 |
| Oct 2023 | 2023-10-01 00:00:00 UTC | 2023-11-01 00:00:00 UTC | 0 | 0 | 0 |
| Nov 2023 | 2023-11-01 00:00:00 UTC | 2023-12-01 00:00:00 UTC | 0 | 0 | 0 |
| Dec 2023 | 2023-12-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 0 | 0 | 0 |
| Jan 2024 | 2024-01-01 00:00:00 UTC | 2024-02-01 00:00:00 UTC | 0 | 0 | 0 |
| Feb 2024 | 2024-02-01 00:00:00 UTC | 2024-03-01 00:00:00 UTC | 0 | 0 | 0 |
| Mar 2024 | 2024-03-01 00:00:00 UTC | 2024-04-01 00:00:00 UTC | 1 | 0 | 1 |
| Apr 2024 | 2024-04-01 00:00:00 UTC | 2024-05-01 00:00:00 UTC | 1 | 0 | 1 |
| May 2024 | 2024-05-01 00:00:00 UTC | 2024-06-01 00:00:00 UTC | 0 | 0 | 0 |
| Jun 2024 | 2024-06-01 00:00:00 UTC | 2024-07-01 00:00:00 UTC | 1 | 1 | 0 |
What Hacker News says
17 sourcesUsing:
https://github.com/facebookresearch/segment-anything/
https://github.com/MakieOrg/Tyler.jl
https://docs.makie.org/
In [dead]Nice work! Did you figure out the training/fine-tuning code for Segment Anything? There's an on-going discussion on the official repo[0] but no clear results yet.
[0]https://github.com/facebookresearch/segment-anything/issues/...
In EditAnything: Segment Anything + ControlNet + BLIP2 + Stable DiffusionThey are claiming that. They are also delivering on that claim: https://github.com/facebookresearch/segment-anything#model-c...
In Meta Releases New AI-Based Photo Segmentation Tool to Everybody> According to the article, the weights haven't been open sourced, so nobody can take this and build their own Photoshop plugin.
The article seems to be misleading, since I can just go to the github and download the weights right now: https://github.com/facebookresearch/segment-anything#model-c...
However, for sake of fairness, competition, and reproducible science, I hope that if Adobe makes this a part of their commercial offering, they train their own so we can have two variants of the same model available to us.
In Meta Releases New AI-Based Photo Segmentation Tool to EverybodyIn the README on said github
https://github.com/facebookresearch/segment-anything#model-c...
In Meta Releases New AI-Based Photo Segmentation Tool to EverybodyKind of off topic, but: I've never seen such crappy issues filed in a repo [1].
I don't read issues for major repositories, so perhaps this is standard? There are a ton of one line "issues", no clear example, test case, attempt to debug, not even a pull request for the one that points out a typo in the README.
Gross. It seems like none of these issues will never be read because they are going to drown in garbage.
[1] https://github.com/facebookresearch/segment-anything/issues
In Segment Anything Model (SAM) can "cut out" any object in an imageSAM itself _is_ open source: https://github.com/facebookresearch/segment-anything
ASL 2 license.
In Meta Releases New AI-Based Photo Segmentation Tool to EverybodyThe model is open source
https://github.com/facebookresearch/segment-anything/
In Meta Releases New AI-Based Photo Segmentation Tool to EverybodySegment Anything: Model released by Meta for image segmentation
1 points · Open discussionIt isn't purely client-side. The embeddings are generated on the server so your image is still sent to Meta for processing. https://github.com/facebookresearch/segment-anything/issues/...
In Segment Anything Model (SAM) can "cut out" any object in an imageMultiple block diagrams and the paper note that one of the inputs is supposed to be "text", but none of the example Jupyter notebooks or the live demo page show how to use those. I'm assuming just run the text into CLIP, take the resulting embedding, and throw it directly in as a prompt, which then gets re-encoded by the SAM prompt encoder?
> "Prompt encoder. We consider two sets of prompts: sparse (points, boxes, text) and dense (masks). We represent points and boxes by positional encodings [95] summed with learned embeddings for each prompt type and free-form text with an off-the-shelf text encoder from CLIP [82]. Dense prompts (i.e., masks) are embedded using convolutions and summed element-wise with the image embedding."
Edit: Found the answer myself: https://github.com/facebookresearch/segment-anything/issues/...
In Segment Anything Model (SAM) can "cut out" any object in an imageThis is going along with the new Segment Anything Model paper Meta AI just released:
Paper: https://scontent-sea1-1.xx.fbcdn.net/v/t39.2365-6/10000000_6...
Announcement: https://ai.facebook.com/blog/segment-anything-foundation-mod...
Code & Model Weights: https://github.com/facebookresearch/segment-anything
In Segment Anything Model (SAM) can "cut out" any object in an imageWow, glad they decided to provide all the model weights (not behind a request form this time!): https://github.com/facebookresearch/segment-anything#model-c...
very impressive work by Meta AI
In Meta New Segmentation ModelShowing the 15 most recent of 17 sources. Enable JavaScript to search and browse every indexed mention.