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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
REPOSITORY AT A GLANCE

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…

tysam_and used a recommendation phrase. One indexed comment matches. This is a phrase match, not a verdict.

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 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.

0510152023-04-01 00:00:00 UTC to 2023-05-01 00:00:00 UTC (exclusive): 17 mentions; 2 submissions, 15 commentsApr 20232023-05-01 00:00:00 UTC to 2023-06-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2023-06-01 00:00:00 UTC to 2023-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-07-01 00:00:00 UTC to 2023-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-08-01 00:00:00 UTC to 2023-09-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2023-09-01 00:00:00 UTC to 2023-10-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2023-10-01 00:00:00 UTC to 2023-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-11-01 00:00:00 UTC to 2023-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsNov 20232023-12-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-01-01 00:00:00 UTC to 2024-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-02-01 00:00:00 UTC to 2024-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-03-01 00:00:00 UTC to 2024-04-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2024-04-01 00:00:00 UTC to 2024-05-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2024-05-01 00:00:00 UTC to 2024-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-06-01 00:00:00 UTC to 2024-07-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 commentsJun 2024

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
Apr 20232023-04-01 00:00:00 UTC2023-05-01 00:00:00 UTC17215
May 20232023-05-01 00:00:00 UTC2023-06-01 00:00:00 UTC202
Jun 20232023-06-01 00:00:00 UTC2023-07-01 00:00:00 UTC000
Jul 20232023-07-01 00:00:00 UTC2023-08-01 00:00:00 UTC000
Aug 20232023-08-01 00:00:00 UTC2023-09-01 00:00:00 UTC101
Sep 20232023-09-01 00:00:00 UTC2023-10-01 00:00:00 UTC101
Oct 20232023-10-01 00:00:00 UTC2023-11-01 00:00:00 UTC000
Nov 20232023-11-01 00:00:00 UTC2023-12-01 00:00:00 UTC000
Dec 20232023-12-01 00:00:00 UTC2024-01-01 00:00:00 UTC000
Jan 20242024-01-01 00:00:00 UTC2024-02-01 00:00:00 UTC000
Feb 20242024-02-01 00:00:00 UTC2024-03-01 00:00:00 UTC000
Mar 20242024-03-01 00:00:00 UTC2024-04-01 00:00:00 UTC101
Apr 20242024-04-01 00:00:00 UTC2024-05-01 00:00:00 UTC101
May 20242024-05-01 00:00:00 UTC2024-06-01 00:00:00 UTC000
Jun 20242024-06-01 00:00:00 UTC2024-07-01 00:00:00 UTC110

What Hacker News says

1 sources
Fengjiao·Jun 4, 2024Submission

Show HN: Shortbread App – AI-powered, romantic comics for women

Hi HN! Fengjiao and Evan here. We are building Shortbread App, Netflix for webcomics. We publish guilty-pleasure romance series (think 50 Shades of Gray) as comics. Like the mature version of Webtoon. You can see two comics episodes at https://create.shortbread.ai/viewer/3d25370c-a4eb-4df4-af8e-... https://create.shortbread.ai/viewer/866c2873-9962-4ebe-8f0c-..., and read more in the app via https://www.shortbreadapp.com/. All comics in the app are made by artists using the Shortbread AI Comics Studio (https://shortbread.ai). It is a powerful Photoshop-like editor that speeds up comic creation 10x with AI. The editor provides consistency and granular artistic control. More below. We first posted on HN 6 months ago when we built a prompt-to-comics AI (https://news.ycombinator.com/item?id=37792444). We sunsetted this soon after - it was a fu
Read the rest
n experiment but it didn’t meet the real need of comic artists. Shortbread Studio now changes this by enhancing how creators naturally work instead of replacing them. The tech: One-shot Character LoRA: Artists upload a single photo of their character. Our backend uses prompt engineering and ControlNet pipelines to generate a synthetic dataset from this photo. This dataset shows the character in all kinds of angles, poses and facial expressions that the artist can pick the best from. It’s then sent to our LoRA training service to create a LoRA model. This takes about 7 minutes. Control -> Redraw -> Refine Workflow: In real life drawing, you draw, erase, and draw again. The human creative process is iterative. In Shortbread Studio, artists can start from a text prompt, a sketch, a web image or a pose reference as a basis, create an initial panel and quickly modify and regenerate until they get what they want. If you spend 5 seconds, you get a decent panel. If you spend 10 minutes, you can push the limits and get pro results. Built-in Post-Processing: The editor’s features include liquify, upscale, remove background, and outpainting to extend an image. This allows artists to remove, add, or modify parts of an image on a pixel level without drawing by hand. We combine this with segmentation models like Segment Anything (https://github.com/facebookresearch/segment-anything) to support intelligently selecting and editing a part of an image. Google-docs like collaboration: The Studio runs in the browser and supports comments and collaboration. LLM Powered Copy Editor: Comics need text. An AI agent proofreads speech bubbles, fixes lettering and identifies grammar mistakes. Read our comics: https://shortbreadapp.com/ (free to download + read, iOS + Android) All of the above are built by a team of 3 engineers including myself. I will be around to answer any questions in this thread!
62 points · Open discussion

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