sarthakpati Goto Github PK

releasing-research-code

Tips for releasing research code in Machine Learning (with official NeurIPS 2020 recommendations)

rusty1s

sarthakpati

Machine Learning Engineer with a flair for C++.

sarthakpati.github.io

scikit-network

Graph Algorithms

setsimilaritysearch

All-pair set similarity search on millions of sets in Python and on a laptop

sge_submission_test

Example of iterative job submission using the cubic cluster at CBICA, UPenn

staged-recipes

A place to submit conda recipes before they become fully fledged conda-forge feedstocks

stress-test

For Stress Testing Machines

synthseg

Contrast-agnostic segmentation of MRI scans

tempdownloads

tiatoolbox

Computational Pathology Toolbox developed by TIA Centre, University of Warwick.

tiatoolbox-feedstock

A conda-smithy repository for tiatoolbox.

tifffile

Read and write TIFF files. Forked from https://pypi.org/project/tifffile

tiffslide

tifffile based openslide-python replacement

torch-scatter-feedstock

A conda-smithy repository for torch-scatter.

torchinfo

View model summaries in PyTorch!

torchio

Medical image preprocessing and augmentation tools for deep learning.

torchio-feedstock

A conda-smithy repository for torchio.

torchio_lambda_test

torchio_minimal

torchtuples

Training neural networks in PyTorch

training

Reference implementations of training benchmarks

tum-dissertation-latex

Latex template for a TUM dissertation/PhD thesis

tutorials

Here, we will be showcasing our seminar series “CPP for Image Processing and Machine Learning” including presentations and code examples. There are image processing and machine learning libraries out there which use C++ as a base and have become industry standards (ITK for medical imaging, OpenCV for computer vision and machine learning, Eigen for linear algebra, Shogun for machine learning). The documentation provided with these packages, though extensive, assume a certain level of experience with C++. Our tutorials are intended for those people who have basic understanding of medical image processing and machine learning but who are just starting to get their toes wet with C++ (and possibly have prior experience with Python or MATLAB). Here we will be focusing on how someone with a good theoretical background in image processing and machine learning can quickly prototype algorithms using CPP and extend them to create meaningful software packages.

vcpkg

VC++ Packaging Tool

vision

Datasets, Transforms and Models specific to Computer Vision

vscodesnippets

Code snippets for Visual Studio

wsidicom

Python package for reading DICOM WSI file sets.

zipfile-deflate64

Extract Deflate64 ZIP archives with Python's `zipfile` API.