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8 best C++ Dataset libraries in 2022

by Open Weaver kits ✔ Updated: May 13, 2022

C++ is the language of choice for many programmers who need to create software that works well with a variety of platforms. It is also a very popular language among hackers, who often use C++ to develop exploits, root kits and other forms of malware. Dataset is an important part of the Artificial Intelligence project. It needs to be classified and processed to train the model. It has imperative, object-oriented and generic programming features. C++ also supports generic programming and meta-programming through templates which makes it easy to write large data structures with very small memory footprint. Many developers depend on the following C++ Dataset open source libraries: h5cpp - C17 templates between and HDF5 datasets; Digit-Recognition-MNIST-SVHN-PyTorch-CPP - Implementing CNN for Digit Recognition using PyTorch C API; PixelatedDPC - C program for fast parallelised GPU based analysis of disk movement in pixelated STEM datase

cosmoscout-vrby cosmoscout

C++ star image 317 Version:v1.7.0

License: Others (Non-SPDX)

:milky_way: A virtual universe which lets you explore, analyze and present huge planetary datasets and large simulation data in real-time.

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cosmoscout-vrby cosmoscout

C++ star image 317 Version:v1.7.0 License: Others (Non-SPDX)

:milky_way: A virtual universe which lets you explore, analyze and present huge planetary datasets and large simulation data in real-time.
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h5cppby steven-varga

C++ star image 118 Version:Current

License: Others (Non-SPDX)

C++17 templates between [stl::vector | armadillo | eigen3 | ublas | blitz++] and HDF5 datasets

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h5cppby steven-varga

C++ star image 118 Version:Current License: Others (Non-SPDX)

C++17 templates between [stl::vector | armadillo | eigen3 | ublas | blitz++] and HDF5 datasets
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z5by constantinpape

C++ star image 80 Version:2.0.13

License: Permissive (MIT)

Lighweight C++ and Python interface for datasets in zarr and N5 format

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z5by constantinpape

C++ star image 80 Version:2.0.13 License: Permissive (MIT)

Lighweight C++ and Python interface for datasets in zarr and N5 format
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mnistby wichtounet

C++ star image 66 Version:Current

License: Permissive (MIT)

Simple C++ reader for MNIST dataset

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mnistby wichtounet

C++ star image 66 Version:Current License: Permissive (MIT)

Simple C++ reader for MNIST dataset
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Digit-Recognition-MNIST-SVHN-PyTorch-CPPby krshrimali

C++ star image 18 Version:Current

License: Permissive (MIT)

Implementing CNN for Digit Recognition (MNIST and SVHN dataset) using PyTorch C++ API

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Digit-Recognition-MNIST-SVHN-PyTorch-CPPby krshrimali

C++ star image 18 Version:Current License: Permissive (MIT)

Implementing CNN for Digit Recognition (MNIST and SVHN dataset) using PyTorch C++ API
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cifar-10by wichtounet

C++ star image 12 Version:Current

License: Permissive (MIT)

Simple C++ reader for CIFAR-10 dataset

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cifar-10by wichtounet

C++ star image 12 Version:Current License: Permissive (MIT)

Simple C++ reader for CIFAR-10 dataset
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PixelatedDPCby matkraj

C++ star image 6 Version:Current

License: Strong Copyleft (GPL-3.0)

C++ program for fast parallelised GPU based analysis of disk movement in pixelated STEM dataset

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PixelatedDPCby matkraj

C++ star image 6 Version:Current License: Strong Copyleft (GPL-3.0)

C++ program for fast parallelised GPU based analysis of disk movement in pixelated STEM dataset
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Nearest-Neighbour-LSHby cchatzis

C++ star image 3 Version:Current

License: Permissive (MIT)

C++ program that, given a vectorised dataset and query set, performs locality sensitive hashing, finding either Nearest Neighbour (NN) or Neighbours in specified range of points in query set, using either Euclidian distance or Cosine Similarity.

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Nearest-Neighbour-LSHby cchatzis

C++ star image 3 Version:Current License: Permissive (MIT)

C++ program that, given a vectorised dataset and query set, performs locality sensitive hashing, finding either Nearest Neighbour (NN) or Neighbours in specified range of points in query set, using either Euclidian distance or Cosine Similarity.
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