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...
The Scientific Visualization Artist Tools (SVAT) include converters from the Visualization Toolkit (VTK) to RenderMan Interface Bytestream (RIB) (ASCII and binary files supported), Blender to RenderMan, compilable RenderMan shaders and other utilities.
File-Spector is a small, fast and easy to use binary file analyzer and Inspector.
It allows the users to format a complete binary file structure and then use it to read any binary file that matches the specified format.
FEVal, the Finite Element Evaluator written in Python, provides easy conversion for many Finite Element data formats (both binary and ascii). Mesh modification is very easy. Values of model results can be accessed given coordinates in physical space.