label-studio
engineering
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label-studio | engineering | |
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49 | 3 | |
16,385 | 36 | |
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9.8 | 0.0 | |
1 day ago | over 1 year ago | |
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Apache License 2.0 | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
label-studio
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First 15 Open Source Advent projects
14. LabelStudio by Human Signal | Github | tutorial
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Exploring Open-Source Alternatives to Landing AI for Robust MLOps
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.
- FLaNK Stack Weekly for 14 Aug 2023
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You Can't Have a Free Software AI Stack
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
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.
- Label Studio: Open-Source Data Labeling Platform
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Best (quickest) way to annotate images for whole-image classification?
LabelStudio is free for single use. https://labelstud.io/
- Label Studio – Free multi-type data ML labeling and annotation tool
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Way to label yolov7 images fast
LabelStudio is pretty nice, and free & open source, but I have yet to try out their ML integration with a YOLO object detection model.
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image labeling online Tools
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.
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Preprocessing data for CNN tips?
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.
engineering
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Ask HN: Who is hiring? (January 2022)
Slim.AI | Fullstack and Backend Engineers | REMOTE, international or Seattle/Bellevue/WA | Full-time | Golang, Node.js, Vue.js/Nuxt.js
I'm the founder and CTO at Slim.AI. We are a well funded seed stage startup (9M+) in the developer tooling space. Our mission is to simplify and accelerate the containerized app delivery (it's too hard, too complicated and with too much manual work). We are about to transition to the next phase and we are expanding our engineering team.
Our engineering team is the innovation engine for our product because we are building a solution to solve our own problems creating and running containerized cloud-native applications.
We use Golang, Node.js Serverless/Lambda and containers. We have frontend, backend and fullstack roles ( https://github.com/slim-ai/engineering ).
Our engineering principles:
* We use what we build.
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Ask HN: Who is hiring? (December 2021)
Slim.AI | Backend and Fullstack Engineers | REMOTE, international or Seattle/Bellevue/WA | Full-time | https://github.com/slim-ai/engineering
We are a well funded seed stage startup (9M+) in the developer tooling space on a mission to redefine how DevOps is done for containerized apps (it's too hard, too complicated and with too much manual work). We are about to transition to the next phase and we are expanding our engineering team.
Our engineering team is the innovation engine for our product because we are building a solution to solve our own problems creating and running containerized cloud-native applications.
We use Golang, Node.js Serverless/Lambda and containers. Take a look at the backend ( https://github.com/slim-ai/engineering/blob/master/roles/bac... ) and fullstack ( https://github.com/slim-ai/engineering/blob/master/roles/ful... ) roles and our engineering principles to see if the role and how we do engineering looks interesting to you ( https://github.com/slim-ai/engineering#engineering-principle... ).
Email me at [email protected] if you'd like to learn more.
P.S.
And take a look at DockerSlim ( https://github.com/docker-slim/docker-slim ) if you are interested in working on the open source project that powers our SaaS.
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Ask HN: Who is hiring? (January 2021)
Slim.AI | REMOTE or Seattle | Full-time | Developer Experience Lead | https://github.com/slim-ai/engineering
Do you enjoy working with lots of different applications stacks? Do you like helping others? Do you want to build lots of different applications? Are you interested in contributing to open source?
We are a funded seed stage startup in the developer tooling and DevOps space empowering developers to build and run their cloud-native applications. The current product is focusing on containers and the friction around them.
We are building a brand new engineering team. We are developer friendly, low on process with no mind-numbing bureaucracy or micromanagement. We are looking for people who'll be excited to be a part of the engineering team in an early stage startup during its inception phase building modern cloud-native applications the right way.
You can find out more about the mission, how we work and the roles here: https://github.com/slim-ai/engineering
Email me at [email protected] if you'd like to learn more.
What are some alternatives?
cvat - Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale. [Moved to: https://github.com/cvat-ai/cvat]
pulsechain-testnet
doccano - Open source annotation tool for machine learning practitioners.
orchest - Build data pipelines, the easy way 🛠️
awesome-data-labeling - A curated list of awesome data labeling tools
Lean and Mean Docker containers - Slim(toolkit): Don't change anything in your container image and minify it by up to 30x (and for compiled languages even more) making it secure too! (free and open source)
diffgram - The AI Datastore for Schemas, BLOBs, and Predictions. Use with your apps or integrate built-in Human Supervision, Data Workflow, and UI Catalog to get the most value out of your AI Data.
MLServer - An inference server for your machine learning models, including support for multiple frameworks, multi-model serving and more
haystack - :mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.
zenml - ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.
labelbox-custom-labeling-apps - Explore example custom labeling apps built with Labelbox SDK
engineering-principles - Skyscanner's Engineering Principles