label-studio VS identity-idp

14. LabelStudio by Human Signal | Github | tutorial

For instance, the COCO Annotator is a web-based image annotation tool tailored for the COCO dataset format, allowing collaborative labeling with features like attribute tagging and automatic segmentation. Similarly, Label Studio offers an easy-to-use interface for bounding box object labeling in images.

Huh?

I wrote my own system for classifying a stream of texts in Python, I might Open Source it one of these days but I have to get it to the point where it is modular enough that I can customize it to do the particular things I want without subjecting people to my whims... I use it every day and I'm not afraid to demo it because it is rock solid.

My understanding is that my system would not be hard to adapt to work on images for certain kinds of tasks.

Pytorch is open source, Huggingface is open source. CUDA isn't. This is

https://labelstud.io/

and for annotating text spans there are so many open source tools

https://github.com/doccano/doccano

I worked for a company a few years back that built annotation tools for projects we sold to customers but never quite got to a polished general purpose annotator. Today there are an overwhelming number of companies in this space and products I never heard of, many of which are cloud based or paid. Looks like a gold rush to me.

LabelStudio is free for single use. https://labelstud.io/

LabelStudio is pretty nice, and free & open source, but I have yet to try out their ML integration with a YOLO object detection model.

Label Studio is an open source data labeling tool that includes annotation functionality. It provides a simple user interface (UI) that lets you label various data types, including text, audio, time series data, videos, and images, and export the information to various model formats.

I’m fairly new to deep learning and learning as I got so sorry if this is very basic, but I’m working on a model for detecting invasive coconut rhinoceros beetles destroying palm trees using drone photography. The 1080p photos I’m given were taken 250ft AGL and were cropped into equal size smaller images with some having one or more palm trees and some having none. Im using I’m using labelStudio to generate the XML files that point to their jpg counterparts path.

Sign in to your login.gov account at https://secure.login.gov/ Stay on the login.gov Your account page. Look for Backup Codes and click Generate. Download, print, or write down your backup codes and save them in a secure place. Click Continue.

For more advanced 2FA techniques, including security keys, take a look at the source code for login.gov: https://github.com/18F/identity-idp

I'm skeptical of the number that Rettig quotes. I'd like to know where he got those numbers. Also, the code that runs Login.gov is (mostly) in the public domain: https://github.com/18F/identity-idp – anybody with a $2/mo VPS could run the code and do their own load testing.

Login.gov is pretty good. Source code viewable here.

Currently trying to finish my global entry application. I have previously been able to log in to my Trust Traveler profile. Today, when I hit "Use face or touch unlock" it says "Do you want to sign in to "secure.login.gov" using a security key? Insert and activate your security key, or bring it to the top of your phone.

How to apply > pdf > https://secure.login.gov/

Another vote for Ahoy. I did the initial implementation for login.gov over 6 years ago and it worked out great. It's still in use: https://github.com/18F/identity-idp/blob/main/app/services/analytics.rb

Absolutely. I've been pretty impressed with their Login.gov prerequisite and (CA) DMV RealID process. Quite modern as online service portals go. And it details every penny I've paid-in for every job I've had since 1993. A Citizen Portal really isn't a stretch from that.