A method to perform unsupervised cross-region adaptation of crop classifiers trained with satellite image time series.

Overview

TimeMatch

Official source code of TimeMatch: Unsupervised Cross-region Adaptation by Temporal Shift Estimation by Joachim Nyborg, Charlotte Pelletier, Sébastien Lefèvre, and Ira Assent.

Requirements

Python requirements

  • Python 3.9.4, PyTorch 1.8.1, and more in environment.yml.

TimeMatch dataset download

The dataset can be freely downloaded from Zenodo. The extracted size is about 78 GB.

Pre-trained models and full results

Pre-trained models and results can also be downloaded from Zenodo

Usage

Setup conda environment and activate

conda env create -f environment.yml
conda activate timematch

Download dataset and extract to /media/data/timematch_data (or set --data_root to its path for train.py).

Pre-trained models should be extracted to timematch/outputs.

Example: train model on the source domain

python train.py -e pseltae_32VNH --source denmark/32VNH/2017 --target denmark/32VNH/2017

Train TimeMatch with pre-trained model

python train.py -e timematch_32VNH_to_30TXT --source denmark/32VNH/2017 --target france/30TXT/2017 timematch --weights outputs/pseltae_32VNH

All training scripts can be found in the scripts directory.

Reference

TODO

Credits

Owner
Joachim Nyborg
PhD student at the Department of Computer Science, Aarhus University
Joachim Nyborg
Official implementation of the ICLR 2021 paper

You Only Need Adversarial Supervision for Semantic Image Synthesis Official PyTorch implementation of the ICLR 2021 paper "You Only Need Adversarial S

Bosch Research 272 Dec 28, 2022
generate-2D-quadrilateral-mesh-with-neural-networks-and-tree-search

generate-2D-quadrilateral-mesh-with-neural-networks-and-tree-search This repository contains single-threaded TreeMesh code. I'm Hua Tong, a senior stu

Hua Tong 18 Sep 21, 2022
DimReductionClustering - Dimensionality Reduction + Clustering + Unsupervised Score Metrics

Dimensionality Reduction + Clustering + Unsupervised Score Metrics Introduction

11 Nov 15, 2022
nfelo: a power ranking, prediction, and betting model for the NFL

nfelo nfelo is a power ranking, prediction, and betting model for the NFL. Nfelo take's 538's Elo framework and further adapts it for the NFL, hence t

6 Nov 22, 2022
Code for "Learning Graph Cellular Automata"

Learning Graph Cellular Automata This code implements the experiments from the NeurIPS 2021 paper: "Learning Graph Cellular Automata" Daniele Grattaro

Daniele Grattarola 37 Oct 26, 2022
Data and code from COVID-19 machine learning paper

Machine learning approaches for localized lockdown, subnotification analysis and cases forecasting in São Paulo state counties during COVID-19 pandemi

Sara Malvar 4 Dec 22, 2022
Unofficial implementation of Point-Unet: A Context-Aware Point-Based Neural Network for Volumetric Segmentation

Point-Unet This is an unofficial implementation of the MICCAI 2021 paper Point-Unet: A Context-Aware Point-Based Neural Network for Volumetric Segment

Namt0d 9 Dec 07, 2022
learning and feeling SLAM together with hands-on-experiments

modern-slam-tutorial-python Learning and feeling SLAM together with hands-on-experiments 😀 😃 😆 Dependencies Most of the examples are based on GTSAM

Giseop Kim 59 Dec 22, 2022
Mapping Conditional Distributions for Domain Adaptation Under Generalized Target Shift

This repository contains the official code of OSTAR in "Mapping Conditional Distributions for Domain Adaptation Under Generalized Target Shift" (ICLR 2022).

Matthieu Kirchmeyer 5 Dec 06, 2022
Skipgram Negative Sampling in PyTorch

PyTorch SGNS Word2Vec's SkipGramNegativeSampling in Python. Yet another but quite general negative sampling loss implemented in PyTorch. It can be use

Jamie J. Seol 287 Dec 14, 2022
Easily Process a Batch of Cox Models

ezcox: Easily Process a Batch of Cox Models The goal of ezcox is to operate a batch of univariate or multivariate Cox models and return tidy result. ⏬

Shixiang Wang 15 May 23, 2022
Manifold Alignment for Semantically Aligned Style Transfer

Manifold Alignment for Semantically Aligned Style Transfer [Paper] Getting Started MAST has been tested on CentOS 7.6 with python = 3.6. It supports

35 Nov 14, 2022
Official implementation for the paper: Multi-label Classification with Partial Annotations using Class-aware Selective Loss

Multi-label Classification with Partial Annotations using Class-aware Selective Loss Paper | Pretrained models Official PyTorch Implementation Emanuel

99 Dec 27, 2022
PyTorch Implementation of Daft-Exprt: Robust Prosody Transfer Across Speakers for Expressive Speech Synthesis

PyTorch Implementation of Daft-Exprt: Robust Prosody Transfer Across Speakers for Expressive Speech Synthesis

Ubisoft 76 Dec 30, 2022
Real-Time SLAM for Monocular, Stereo and RGB-D Cameras, with Loop Detection and Relocalization Capabilities

ORB-SLAM2 Authors: Raul Mur-Artal, Juan D. Tardos, J. M. M. Montiel and Dorian Galvez-Lopez (DBoW2) 13 Jan 2017: OpenCV 3 and Eigen 3.3 are now suppor

Raul Mur-Artal 7.8k Dec 30, 2022
A machine learning library for spiking neural networks. Supports training with both torch and jax pipelines, and deployment to neuromorphic hardware.

Rockpool Rockpool is a Python package for developing signal processing applications with spiking neural networks. Rockpool allows you to build network

SynSense 21 Dec 14, 2022
Annotated notes and summaries of the TensorFlow white paper, along with SVG figures and links to documentation

TensorFlow White Paper Notes Features Notes broken down section by section, as well as subsection by subsection Relevant links to documentation, resou

Sam Abrahams 437 Oct 09, 2022
LiDAR R-CNN: An Efficient and Universal 3D Object Detector

LiDAR R-CNN: An Efficient and Universal 3D Object Detector Introduction This is the official code of LiDAR R-CNN: An Efficient and Universal 3D Object

TuSimple 295 Jan 05, 2023
Cluttered MNIST Dataset

Cluttered MNIST Dataset A setup script will download MNIST and produce mnist/*.t7 files: luajit download_mnist.lua Example usage: local mnist_clutter

DeepMind 50 Jul 12, 2022
[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

Junyong Lee 173 Dec 30, 2022