Data reduction pipeline for KOALA on the AAT.

Overview

KOALA

Build Status Documentation Status Coverage Status License Supported versions PyPI


KOALA, the Kilofibre Optical AAT Lenslet Array, is a wide-field, high efficiency, integral field unit used by the AAOmega spectrograph on the 3.9m AAT (Anglo-Australian Telescope) at Siding Spring Observatory. PyKOALA is the forthcoming data reduction pipeline for creating science-ready 3D data cubes using Raw Stacked Spectra (RSS) images created with 2dfdr.

Helping to develop PyKOALA

  1. Fork koala into your github account
  2. Clone your fork onto your laptop:
    git clone https://github.com/<your_account>/koala
  1. Add this repository as another remote (to get the latest stuff):
    git remote add upstream https://github.com/pykoala/koala
  1. Create a branch to work on the changes:
    git checkout -b <new_branch>
  1. Add and commit changes
  2. Push up your changes
  3. Create a PR, and wait for someone to review it

Reviewing commits

  1. Look through the changes, and provide comments
  2. Once the PR is ready, type bors r+, then bors will handle the merge (DON'T HIT THE MERGE BUTTON).
  3. If the tests fail, help the proposer fix the failures
  4. Use bors r+ again

You can also use bors try to try running the tests, without merging

Towards Interpretable Deep Metric Learning with Structural Matching

DIML Created by Wenliang Zhao*, Yongming Rao*, Ziyi Wang, Jiwen Lu, Jie Zhou This repository contains PyTorch implementation for paper Towards Interpr

Wenliang Zhao 75 Nov 11, 2022
Code for the paper "Location-aware Single Image Reflection Removal"

Location-aware Single Image Reflection Removal The shown images are provided by the datasets from IBCLN, ERRNet, SIR2 and the Internet images. The cod

72 Dec 08, 2022
SimpleDepthEstimation - An unified codebase for NN-based monocular depth estimation methods

SimpleDepthEstimation Introduction This is an unified codebase for NN-based monocular depth estimation methods, the framework is based on detectron2 (

8 Dec 13, 2022
Sky Computing: Accelerating Geo-distributed Computing in Federated Learning

Sky Computing Introduction Sky Computing is a load-balanced framework for federated learning model parallelism. It adaptively allocate model layers to

HPC-AI Tech 72 Dec 27, 2022
This is the repo of the manuscript "Dual-branch Attention-In-Attention Transformer for speech enhancement"

DB-AIAT: A Dual-branch attention-in-attention transformer for single-channel SE

Guochen Yu 68 Dec 16, 2022
Jupyter notebooks for using & learning Keras

deep-learning-with-keras-notebooks 這個github的repository主要是個人在學習Keras的一些記錄及練習。希望在學習過程中發現到一些好的資訊與範例也可以對想要學習使用 Keras來解決問題的同好,或是對深度學習有興趣的在學學生可以有一些方便理解與上手範例

ErhWen Kuo 2.1k Dec 27, 2022
A certifiable defense against adversarial examples by training neural networks to be provably robust

DiffAI v3 DiffAI is a system for training neural networks to be provably robust and for proving that they are robust. The system was developed for the

SRI Lab, ETH Zurich 202 Dec 13, 2022
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)

Karate Club is an unsupervised machine learning extension library for NetworkX. Please look at the Documentation, relevant Paper, Promo Video, and Ext

Benedek Rozemberczki 1.8k Jan 07, 2023
This is a collection of simple PyTorch implementations of neural networks and related algorithms. These implementations are documented with explanations,

labml.ai Deep Learning Paper Implementations This is a collection of simple PyTorch implementations of neural networks and related algorithms. These i

labml.ai 16.4k Jan 09, 2023
Learning Calibrated-Guidance for Object Detection in Aerial Images

Learning Calibrated-Guidance for Object Detection in Aerial Images arxiv We propose a simple yet effective Calibrated-Guidance (CG) scheme to enhance

51 Sep 22, 2022
Fast, general, and tested differentiable structured prediction in PyTorch

Fast, general, and tested differentiable structured prediction in PyTorch

HNLP 1.1k Dec 16, 2022
In-place Parallel Super Scalar Samplesort (IPS⁴o)

In-place Parallel Super Scalar Samplesort (IPS⁴o) This is the implementation of the algorithm IPS⁴o presented in the paper Engineering In-place (Share

82 Dec 22, 2022
Computer Vision Paper Reviews with Key Summary of paper, End to End Code Practice and Jupyter Notebook converted papers

Computer-Vision-Paper-Reviews Computer Vision Paper Reviews with Key Summary along Papers & Codes. Jonathan Choi 2021 The repository provides 100+ Pap

Jonathan Choi 2 Mar 17, 2022
Neural Lexicon Reader: Reduce Pronunciation Errors in End-to-end TTS by Leveraging External Textual Knowledge

Neural Lexicon Reader: Reduce Pronunciation Errors in End-to-end TTS by Leveraging External Textual Knowledge This is an implementation of the paper,

Mutian He 19 Oct 14, 2022
Multi-view 3D reconstruction using neural rendering. Unofficial implementation of UNISURF, VolSDF, NeuS and more.

Volume rendering + 3D implicit surface Showcase What? previous: surface rendering; now: volume rendering previous: NeRF's volume density; now: implici

Jianfei Guo 682 Jan 04, 2023
Meta-learning for NLP

Self-Supervised Meta-Learning for Few-Shot Natural Language Classification Tasks Code for training the meta-learning models and fine-tuning on downstr

IESL 43 Nov 08, 2022
An 16kHz implementation of HiFi-GAN for soft-vc.

HiFi-GAN An 16kHz implementation of HiFi-GAN for soft-vc. Relevant links: Official HiFi-GAN repo HiFi-GAN paper Soft-VC repo Soft-VC paper Example Usa

Benjamin van Niekerk 42 Dec 27, 2022
GeoMol: Torsional Geometric Generation of Molecular 3D Conformer Ensembles

GeoMol: Torsional Geometric Generation of Molecular 3D Conformer Ensembles This repository contains a method to generate 3D conformer ensembles direct

127 Dec 20, 2022
Official code for "Eigenlanes: Data-Driven Lane Descriptors for Structurally Diverse Lanes", CVPR2022

[CVPR 2022] Eigenlanes: Data-Driven Lane Descriptors for Structurally Diverse Lanes Dongkwon Jin, Wonhui Park, Seong-Gyun Jeong, Heeyeon Kwon, and Cha

Dongkwon Jin 106 Dec 29, 2022
Deep Learning Head Pose Estimation using PyTorch.

Hopenet is an accurate and easy to use head pose estimation network. Models have been trained on the 300W-LP dataset and have been tested on real data with good qualitative performance.

Nataniel Ruiz 1.3k Dec 26, 2022