Search Results for "labeling"
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Showing 9 open source projects for "labeling"
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Diffgram
Training data (data labeling, annotation, workflow) for all data types
From ingesting data to exploring it, annotating it, and managing workflows. Diffgram is a single application that will improve your data labeling and bring all aspects of training data under a single roof. Diffgram is world’s first truly open source training data platform that focuses on giving its users an unlimited experience. This is aimed to reduce your data labeling bills and increase your Training Data Quality. Training Data is the art of supervising machines through data. ... -
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Cleanlab
The standard data-centric AI package for data quality and ML
cleanlab helps you clean data and labels by automatically detecting issues in a ML dataset. To facilitate machine learning with messy, real-world data, this data-centric AI package uses your existing models to estimate dataset problems that can be fixed to train even better models. cleanlab cleans your data's labels via state-of-the-art confident learning algorithms, published in this paper and blog. See some of the datasets cleaned with cleanlab at labelerrors.com. This package helps you... -
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Metacrafter
Metadata and data identification tool and Python library
Python command line tool and Python engine to label table fields and fields in data files. It could help to find meaningful data in your tables and data files or to find Personal identifiable information (PII). Metacrafter is a rule-based tool that helps to label fields of the tables in databases. It scans table and finds person names, surnames, midnames, PII data, basic identifiers like UUID/GUID. These rules written as .yaml files and could be easily extended. -
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ggrepel
epel overlapping text labels away from each other in your ggplot2
ggrepel is an R package that provides “smart” repulsion for text and label geoms in ggplot2. When placing text labels on a plot (e.g. labeling points), the labels can often overlap; ggrepel ensures labels don’t overlap (or overlap less) by repelling labels / pushing them away, adding connecting lines or nudges, etc. It improves the readability of plots, especially when many labels are present. Support for point and segment geoms (so labels can be connected by lines when moved). ... -
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Encord Active
The toolkit to test, validate, and evaluate your models and surface
Encord Active is an open-source toolkit to test, validate, and evaluate your models and surface, curate, and prioritize the most valuable data for labeling to supercharge model performance. Encord Active has been designed as a all-in-one open source toolkit for improving your data quality and model performance. Use the intuitive UI to explore your data or access all the functionalities programmatically. Discover errors, outliers, and edge-cases within your data - all in one open source toolkit. ... -
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DataGym.ai
Open source annotation and labeling tool for image and video assets
...Your image data can be imported into DATAGYM from your local machine, from any public image URL or directly from an AWS cloud S3 bucket. Machine learning teams spend up to 80% of their time on data preparation. DATAGYM provides AI-powered annotation functions to help you accelerate your labeling task. The Pre-Labeling feature enables turbo-labeling – it processes thousands of images in the background within a very short time. -
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D_2D and D_3D are plotting programs with unique features, useful for data visualization and analysis. Input data should be provided as ASCII files formatted as x,y pairs or x,y,z triplets. Graphic output can be in DXF vector format, or raster image.
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BriPy
A BRIC-seq data analysis package written in Python.
...BRIC-seq, short for 5'-bromo-uridine (BrU) immunoprecipitation chase-deep sequencing analysis, is a novel method in Next Generation Sequencing (NGS) to determine the RNA stability of each transcript. It employs metabolic labeling by BrU of newly synthesized RNAs to chase chronological decreases of BrU-labeled RNA (Pulse-chase labeling), followed by immunoprecipitation with antibody for BrU, construction of cRNA library for High-throughput sequencing and computational data analysis. -What is BriPy? BriPy package is a BRIC-seq data analysis tool written in Python. ... -
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This projects hosts the worlds fastest algorithms for the labeling of point-features. It especially looks for algorithms thar are free of constraints, applicable to many scenarios (e.g., visualization, maps...) and do not need any preprocessing.
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