This is the repository of shape matching algorithm Iterative Rotations and Assignments (IRA)

Overview

Description

This is the repository of shape matching algorithm Iterative Rotations and Assignments (IRA), described in the publication [1].

Directory contents

/IRA: Contains the IRA software, see also the README in /IRA.

/benchmark_test: Contains data and other software used for benchmark tests from [1]. See also the README in /benchmark_test folder.

Compile and run

To run IRA, you need to compile it. See README in /IRA subdirectory.

References

[1] Gunde M., Salles N., Hemeryck A., Martin Samos L. IRA: A shape matching approach for recognition and comparison of generic atomic patterns, Journal of Chemical Information and Modeling (2021), DOI: https://doi.org/10.1021/acs.jcim.1c00567, HAL: hal-03406717, arXiv: 2111.00939

You might also like...
Implementation of Perceiver, General Perception with Iterative Attention, in Pytorch
Implementation of Perceiver, General Perception with Iterative Attention, in Pytorch

Perceiver - Pytorch Implementation of Perceiver, General Perception with Iterative Attention, in Pytorch Install $ pip install perceiver-pytorch Usage

Official Implementation for
Official Implementation for "ReStyle: A Residual-Based StyleGAN Encoder via Iterative Refinement" https://arxiv.org/abs/2104.02699

ReStyle: A Residual-Based StyleGAN Encoder via Iterative Refinement Recently, the power of unconditional image synthesis has significantly advanced th

Implementation of Perceiver, General Perception with Iterative Attention in TensorFlow
Implementation of Perceiver, General Perception with Iterative Attention in TensorFlow

Perceiver This Python package implements Perceiver: General Perception with Iterative Attention by Andrew Jaegle in TensorFlow. This model builds on t

PyTorch Implementation of Google Brain's WaveGrad 2: Iterative Refinement for Text-to-Speech Synthesis
PyTorch Implementation of Google Brain's WaveGrad 2: Iterative Refinement for Text-to-Speech Synthesis

WaveGrad2 - PyTorch Implementation PyTorch Implementation of Google Brain's WaveGrad 2: Iterative Refinement for Text-to-Speech Synthesis. Status (202

Pytorch implementation of “Recursive Non-Autoregressive Graph-to-Graph Transformer for Dependency Parsing with Iterative Refinement”

Graph-to-Graph Transformers Self-attention models, such as Transformer, have been hugely successful in a wide range of natural language processing (NL

StackRec: Efficient Training of Very Deep Sequential Recommender Models by Iterative Stacking

StackRec: Efficient Training of Very Deep Sequential Recommender Models by Iterative Stacking Datasets You can download datasets that have been pre-pr

Code for PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning

PackNet: https://arxiv.org/abs/1711.05769 Pretrained models are available here: https://uofi.box.com/s/zap2p03tnst9dfisad4u0sfupc0y1fxt Datasets in Py

[CVPR 2021] Official PyTorch Implementation for
[CVPR 2021] Official PyTorch Implementation for "Iterative Filter Adaptive Network for Single Image Defocus Deblurring"

IFAN: Iterative Filter Adaptive Network for Single Image Defocus Deblurring Checkout for the demo (GUI/Google Colab)! The GUI version might occasional

Unoffical implementation about Image Super-Resolution via Iterative Refinement by Pytorch
Unoffical implementation about Image Super-Resolution via Iterative Refinement by Pytorch

Image Super-Resolution via Iterative Refinement Paper | Project Brief This is a unoffical implementation about Image Super-Resolution via Iterative Re

Comments
  • ira_eq.x doesn't work.

    ira_eq.x doesn't work.

    Hi , @mgoonde .

    I am a student working on a project of Off-lattice Kinetic Monte Carlo. I found your paper and source code with excitement. As you mentioned in the paper(IRA: A shape matching approach for recognition and comparison of generic atomic patterns), in self-Learning KMC, atomic assignment is unknown amd number of atoms unset. Traditional optimal method like SVD and assignment method like Hungarian algorithm cannot work on my system. So I downloaded your code and tried.

    However, there was something wrong after I combined two .xyz system and executed ira_eq.x.

    First, variable hd_fin not defined. To be honest, I don't know what it means. So i changed hd_out = hd_fin to hd_out = hd image

    Second, the way you permute the coordinates is not recognized by my machine, it goes image , whenerver there is a permutation operation. So I changed it from coords1(:,:) = coords1(:,nint(d_o(2,:))) to do i = 1, nat1 coords1(:,i) = coords1_tmp(:,nint(d_o(2,i))) end do So does the array typ1/typ2/coords2

    After doing these rescue measures, I ran your example ./ira_eq.x < temp_ira. temp_ira is combined from benchmark_test/data/lj_clusters/xyz/47.xyz, same structure file in run_single.sh, and the randomized one. The two xyz structures didn't found scattered using ovito. The result goes infinity.

    I don't know what is wrong and I am not that farmiliar with fortran. So I appreciate your help about it. Best wishes.

    opened by FanMover 1
Releases(IRA_v1.5.0)
  • IRA_v1.5.0(May 12, 2022)

    The second release of IRA code. Improvements are made on performance (speed), and in the unification of routines dealing with equal and nonequal number of atoms. An interface to python is also added. For complete list of changes see the version_history file.

    Source code(tar.gz)
    Source code(zip)
  • v1.0.0(Nov 18, 2021)

Owner
MAMMASMIAS Consortium
Multiscale And Multi Model ApproacheS for Materials In Applied Science Consortium
MAMMASMIAS Consortium
Heterogeneous Deep Graph Infomax

Heterogeneous-Deep-Graph-Infomax Parameter Setting: HDGI-A: Node-level dimension: 16 Attention head: 4 Semantic-level attention vector: 8 learning rat

52 Oct 31, 2022
BLEURT is a metric for Natural Language Generation based on transfer learning.

BLEURT: a Transfer Learning-Based Metric for Natural Language Generation BLEURT is an evaluation metric for Natural Language Generation. It takes a pa

Google Research 492 Jan 05, 2023
Ensemble Visual-Inertial Odometry (EnVIO)

Ensemble Visual-Inertial Odometry (EnVIO) Authors : Jae Hyung Jung, Yeongkwon Choe, and Chan Gook Park 1. Overview This is a ROS package of Ensemble V

Jae Hyung Jung 95 Jan 03, 2023
Marine debris detection with commercial satellite imagery and deep learning.

Marine debris detection with commercial satellite imagery and deep learning. Floating marine debris is a global pollution problem which threatens mari

Inter Agency Implementation and Advanced Concepts 56 Dec 16, 2022
Keras implementation of Deeplab v3+ with pretrained weights

Keras implementation of Deeplabv3+ This repo is not longer maintained. I won't respond to issues but will merge PR DeepLab is a state-of-art deep lear

1.3k Dec 07, 2022
An OpenAI Gym environment for multi-agent car racing based on Gym's original car racing environment.

Multi-Car Racing Gym Environment This repository contains MultiCarRacing-v0 a multiplayer variant of Gym's original CarRacing-v0 environment. This env

Igor Gilitschenski 56 Nov 01, 2022
Show-attend-and-tell - TensorFlow Implementation of "Show, Attend and Tell"

Show, Attend and Tell Update (December 2, 2016) TensorFlow implementation of Show, Attend and Tell: Neural Image Caption Generation with Visual Attent

Yunjey Choi 902 Nov 29, 2022
Training PSPNet in Tensorflow. Reproduce the performance from the paper.

Training Reproduce of PSPNet. (Updated 2021/04/09. Authors of PSPNet have provided a Pytorch implementation for PSPNet and their new work with support

Li Xuhong 126 Jul 13, 2022
Codes and Data Processing Files for our paper.

Code Scripts and Processing Files for EEG Sleep Staging Paper 1. Folder Tree ./src_preprocess (data preprocessing files for SHHS and Sleep EDF) sleepE

Chaoqi Yang 18 Dec 12, 2022
Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework

Official repository of OFA. Paper: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework

OFA Sys 1.4k Jan 08, 2023
Pytorch implementation of U-Net, R2U-Net, Attention U-Net, and Attention R2U-Net.

pytorch Implementation of U-Net, R2U-Net, Attention U-Net, Attention R2U-Net U-Net: Convolutional Networks for Biomedical Image Segmentation https://a

leejunhyun 2k Jan 02, 2023
Imagededup - 😎 Finding duplicate images made easy

imagededup is a python package that simplifies the task of finding exact and near duplicates in an image collection.

idealo 4.3k Jan 07, 2023
MINERVA: An out-of-the-box GUI tool for offline deep reinforcement learning

MINERVA is an out-of-the-box GUI tool for offline deep reinforcement learning, designed for everyone including non-programmers to do reinforcement learning as a tool.

Takuma Seno 80 Nov 06, 2022
List of awesome things around semantic segmentation 🎉

Awesome Semantic Segmentation List of awesome things around semantic segmentation 🎉 Semantic segmentation is a computer vision task in which we label

Dam Minh Tien 18 Nov 26, 2022
DeepStochlog Package For Python

DeepStochLog Installation Installing SWI Prolog DeepStochLog requires SWI Prolog to run. Run the following commands to install: sudo apt-add-repositor

KU Leuven Machine Learning Research Group 17 Dec 23, 2022
[ICCV 2021] Relaxed Transformer Decoders for Direct Action Proposal Generation

RTD-Net (ICCV 2021) This repo holds the codes of paper: "Relaxed Transformer Decoders for Direct Action Proposal Generation", accepted in ICCV 2021. N

Multimedia Computing Group, Nanjing University 80 Nov 30, 2022
Hyperparameter tuning for humans

KerasTuner KerasTuner is an easy-to-use, scalable hyperparameter optimization framework that solves the pain points of hyperparameter search. Easily c

Keras 2.6k Dec 27, 2022
MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from a Single Moving Camera

MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from a Single Moving Camera

Felix Wimbauer 494 Jan 06, 2023
NExT-QA: Next Phase of Question-Answering to Explaining Temporal Actions (CVPR2021)

NExT-QA We reproduce some SOTA VideoQA methods to provide benchmark results for our NExT-QA dataset accepted to CVPR2021 (with 1 'Strong Accept' and 2

Junbin Xiao 50 Nov 24, 2022
Keras implementations of Generative Adversarial Networks.

This repository has gone stale as I unfortunately do not have the time to maintain it anymore. If you would like to continue the development of it as

Erik Linder-Norén 8.9k Jan 04, 2023