awesome-data-labeling VS datalabel

Compare awesome-data-labeling vs datalabel and see what are their differences.

datalabel

datalabel is a UI-based data editing tool that makes it easy to create labeled text data in a dataframe. With datalabel, you can quickly and effortlessly edit your data without having to write any code. Its intuitive interface makes it ideal for both experienced data professionals and those new to data editing. (by CoreLabsAI)
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awesome-data-labeling datalabel
7 1
3,480 2
1.6% -
0.0 10.0
7 months ago about 1 year ago
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The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

awesome-data-labeling

Posts with mentions or reviews of awesome-data-labeling. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-07-26.

datalabel

Posts with mentions or reviews of datalabel. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing awesome-data-labeling and datalabel you can also consider the following projects:

label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format

recogito-js - A JavaScript library for text annotation

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.

markup - A web-based document annotation tool, powered by GPT-4 :rocket:

SSL4MIS - Semi Supervised Learning for Medical Image Segmentation, a collection of literature reviews and code implementations.

Universal Data Tool - Collaborate & label any type of data, images, text, or documents, in an easy web interface or desktop app.

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]

stripnet - STriP Net: Semantic Similarity of Scientific Papers (S3P) Network

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/opencv/cvat]

doccano - Open source annotation tool for machine learning practitioners.

labelbee-client - Out-of-the-box Annotation Toolbox

refinery - The data scientist's open-source choice to scale, assess and maintain natural language data. Treat training data like a software artifact.