Python Scale Resources

A Large-Scale Dataset for Spinal Vertebrae Segmentation in Computed Tomography

An algorithm that handles large-scale aerial photo co-registration, based on SURF, RANSAC and PyTorch autograd.

XL-Sum This repository contains the code, data, and models of the paper titled "XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Lang

DensePhrases DensePhrases is an extractive phrase search tool based on your natural language inputs. From 5 million Wikipedia articles, it can search

XL-Sum This repository contains the code, data, and models of the paper titled "XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Lang

RootBA: Square Root Bundle Adjustment Project Page | Paper | Poster | Video | Code Table of Contents Citation Dependencies Installing dependencies on

RGBT Crowd Counting Lingbo Liu, Jiaqi Chen, Hefeng Wu, Guanbin Li, Chenglong Li, Liang Lin. "Cross-Modal Collaborative Representation Learning and a L

Paraphrastic Representations at Scale Code to train models from "Paraphrastic Representations at Scale". The code is written in Python 3.7 and require

Patch-NetVLAD: Multi-Scale Fusion of Locally-Global Descriptors for Place Recognition This repository contains code for the CVPR2021 paper "Patch-NetV

GraspNet Baseline Baseline model for "GraspNet-1Billion: A Large-Scale Benchmark for General Object Grasping" (CVPR 2020). [paper] [dataset] [API] [do

SCALE: Modeling Clothed Humans with a Surface Codec of Articulated Local Elements (CVPR 2021) This repository contains the official PyTorch implementa

Secure Distributed Training at Scale This repository contains the implementation of experiments from the paper "Secure Distributed Training at Scale"

DistML is a Ray extension library to support large-scale distributed ML training on heterogeneous multi-node multi-GPU clusters

ASPset-510 (Australian Sports Pose Dataset) is a large-scale video dataset for the training and evaluation of 3D human pose estimation models. It contains 17 different amateur subjects performing 30 sports-related actions each, for a total of 510 action clips.

ASPset-510 ASPset-510 (Australian Sports Pose Dataset) is a large-scale video dataset for the training and evaluation of 3D human pose estimation mode

EPSANet：An Efficient Pyramid Split Attention Block on Convolutional Neural Network This repo contains the official Pytorch implementaion code and conf

DeepLM DeepLM: Large-scale Nonlinear Least Squares on Deep Learning Frameworks using Stochastic Domain Decomposition (CVPR 2021) Run Please install th

Fast Face Classification (F²C) This is the code of our paper An Efficient Training Approach for Very Large Scale Face Recognition or F²C for simplicit

CrossViT : Cross-Attention Multi-Scale Vision Transformer for Image Classification This is an unofficial PyTorch implementation of CrossViT: Cross-Att

City-Scale Multi-Camera Vehicle Tracking Guided by Crossroad Zones Requirements Python 3.8 or later with all requirements.txt dependencies installed,

MSAD Multi-Scale Aligned Distillation for Low-Resolution Detection Lu Qi*, Jason Kuen*, Jiuxiang Gu, Zhe Lin, Yi Wang, Yukang Chen, Yanwei Li, Jiaya J

SA-AutoAug Scale-aware Automatic Augmentation for Object Detection Yukang Chen, Yanwei Li, Tao Kong, Lu Qi, Ruihang Chu, Lei Li, Jiaya Jia [Paper] [Bi

Portrait Photo Retouching with PPR10K Paper | Supplementary Material PPR10K: A Large-Scale Portrait Photo Retouching Dataset with Human-Region Mask an

XtremeDistilTransformers for Distilling Massive Multilingual Neural Networks ACL 2020 Microsoft Research [Paper] [Video] Releasing [XtremeDistilTransf

DroneCrowd Paper Detection, Tracking, and Counting Meets Drones in Crowds: A Benchmark. Introduction This paper proposes a space-time multi-scale atte

GenSen Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning Sandeep Subramanian, Adam Trischler, Yoshua B

** DEPRECATED ** This repo has been deprecated. Please visit Megatron-LM for our up to date Large-scale unsupervised pretraining and finetuning code.

fastMRI is a collaborative research project from Facebook AI Research (FAIR) and NYU Langone Health to investigate the use of AI to make MRI scans faster. NYU Langone Health has released fully anonymized knee and brain MRI datasets that can be downloaded from the fastMRI dataset page. Publications associated with the fastMRI project can be found at the end of this README.

Towards Good Practices for Efficiently Annotating Large-Scale Image Classification Datasets This is the official implementation of "Towards Good Pract

Vision Longformer This project provides the source code for the vision longformer paper. Multi-Scale Vision Longformer: A New Vision Transformer for H

Multi-Scale Discriminative Feature Loss This repository provides code for Multi-Scale Discriminative Feature (MDF) loss for image reconstruction algor

Skeleton Aware Multi-modal Sign Language Recognition By Songyao Jiang, Bin Sun, Lichen Wang, Yue Bai, Kunpeng Li and Yun Fu. Smile Lab @ Northeastern

SA-AutoAug Scale-aware Automatic Augmentation for Object Detection Yukang Chen, Yanwei Li, Tao Kong, Lu Qi, Ruihang Chu, Lei Li, Jiaya Jia [Paper] [Bi

CoaT: Co-Scale Conv-Attentional Image Transformers Introduction This repository contains the official code and pretrained models for CoaT: Co-Scale Co

This tutorial's purpose is to introduce Pythonistas to methods for scaling their data science and machine learning work to larger datasets and larger models, using the tools and APIs they know and love from the PyData stack (such as numpy, pandas, and scikit-learn).

Legate NumPy is a Legate library that aims to provide a distributed and accelerated drop-in replacement for the NumPy API on top of the Legion runtime. Using Legate NumPy you do things like run the final example of the Python CFD course completely unmodified on 2048 A100 GPUs in a DGX SuperPOD and achieve good weak scaling.

The SLIDE package contains the source code for reproducing the main experiments in this paper. Dataset The Datasets can be downloaded in Amazon-

MSAD Multi-Scale Aligned Distillation for Low-Resolution Detection Lu Qi*, Jason Kuen*, Jiuxiang Gu, Zhe Lin, Yi Wang, Yukang Chen, Yanwei Li, Jiaya J

pyroSAR A Python Framework for Large-Scale SAR Satellite Data Processing The pyroSAR package aims at providing a complete solution for the scalable or

STAR-FC This code is the implementation for the CVPR 2021 paper "Structure-Aware Face Clustering on a Large-Scale Graph with 10^7 Nodes" 🌟 🌟 . 🎓 Re

AOT-GAN for High-Resolution Image Inpainting Arxiv Paper | AOT-GAN: Aggregated Contextual Transformations for High-Resolution Image Inpainting Yanhong

Res2Net The official pytorch implemention of the paper "Res2Net: A New Multi-scale Backbone Architecture" Our paper is accepted by IEEE Transactions o

DensePhrases DensePhrases provides answers to your natural language questions from the entire Wikipedia in real-time. While it efficiently searches th

ACMM [News] The code for ACMH is released!!! [News] The code for ACMP is released!!! About ACMM is a multi-scale geometric consistency guided multi-vi

lightning lightning is a library for large-scale linear classification, regression and ranking in Python. Highlights: follows the scikit-learn API con

Description FairScale is a PyTorch extension library for high performance and large scale training on one or multiple machines/nodes. This library ext

News Python3 implementations of PSENet [1], PAN [2] and PAN++ [3] are released at https://github.com/whai362/pan_pp.pytorch. [1] W. Wang, E. Xie, X. L

PSENet: Shape Robust Text Detection with Progressive Scale Expansion Network Introduction This is a tensorflow re-implementation of PSENet: Shape Robu

Large Scale Image Completion via Co-Modulated Generative Adversarial Networks, ICLR 2021 (Spotlight) Demo | Paper [NEW!] Time to play with our interac

TrueNAS CORE/Enterprise/SCALE main source repo Want to contribute or collaborate? Join our Slack instance. IMPORTANT NOTE: This is the master branch o

Model search (MS) is a framework that implements AutoML algorithms for model architecture search at scale. It aims to help researchers speed up their exploration process for finding the right model architecture for their classification problems (i.e., DNNs with different types of layers).

This is a Pytorch implementation of the paper: Self-Supervised Graph Transformer on Large-Scale Molecular Data.

Haystack is an end-to-end framework for Question Answering & Neural search that enables you to ... ... ask questions in natural language and find gran

The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate. Website • Key Features • How To Use • Docs •

Apache Spark Spark is a unified analytics engine for large-scale data processing. It provides high-level APIs in Scala, Java, Python, and R, and an op

The Falcon Web Framework Falcon is a reliable, high-performance Python web framework for building large-scale app backends and microservices. It encou

DALL-E in Mesh-Tensorflow [WIP] Open-AI's DALL-E in Mesh-Tensorflow. If this is similarly efficient to GPT-Neo, this repo should be able to train mode

- 基于标题的大规模商品实体检索top1 一、任务介绍 CCKS 2020：基于标题的大规模商品实体检索，任务为对于给定的一个商品标题，参赛系统需要匹配到该标题在给定商品库中的对应商品实体。 输入：输入文件包括若干行商品标题。 输出：输出文本每一行包括此标题对应的商品实体，即给定知识库中商品 ID，

Contextual Non-Local Alignment over Full-Scale Representation for Text-Based Person Search This is an implementation for our paper Contextual Non-Loca

The Falcon Web Framework Falcon is a reliable, high-performance Python web framework for building large-scale app backends and microservices. It encou

The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate. Website • Key Features • How To Use • Docs •

Run inference at scale Cortex is an open source platform for large-scale machine learning inference workloads. Workloads Realtime APIs - respond to pr

Latest Salt Documentation Open an issue (bug report, feature request, etc.) Salt is the world’s fastest, most intelligent and scalable automation engi

pyinfra automates/provisions/manages/deploys infrastructure super fast at massive scale. It can be used for ad-hoc command execution, service deployme