S2s2net - Sentinel-2 Super-Resolution Segmentation Network

Related tags

Deep Learnings2s2net
Overview

S2S2Net

Sentinel-2 Super-Resolution Segmentation Network

Getting started

Installation

Basic

To help out with development, start by cloning this repo-url

git clone <repo-url>

Then I recommend using mamba to install both non-python binaries and python libraries. A virtual environment will also be created with Python and JupyterLab installed.

cd s2s2net
mamba env create --file environment.yml

Activate the virtual environment first.

mamba activate s2s2net

Finally, double-check that the libraries have been installed.

mamba list

Advanced

This is for those who want full reproducibility of the virtual environment.

Making an explicit conda-lock file (only needed if creating a new virtual environment/refreshing an existing one).

mamba env create --file environment.yml
mamba list --explicit > environment-linux-64.lock

Creating/Installing a virtual environment from a conda lock file. See also https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/managenvironments.html#building-identical-conda-environments.

mamba create --name s2s2net --file environment-linux-64.lock
mamba install --name s2s2net --file environment-linux-64.lock

Running jupyter lab

mamba activate s2s2net
python -m ipykernel install --user --name s2s2net  # to install virtual env properly
jupyter kernelspec list --json                     # see if kernel is installed
jupyter lab &
Owner
Wei Ji
Geospatial Data Scientist, Postdoc doing Remote Sensing AI research.
Wei Ji
source code of “Visual Saliency Transformer” (ICCV2021)

Visual Saliency Transformer (VST) source code for our ICCV 2021 paper “Visual Saliency Transformer” by Nian Liu, Ni Zhang, Kaiyuan Wan, Junwei Han, an

89 Dec 21, 2022
Zen-NAS: A Zero-Shot NAS for High-Performance Deep Image Recognition

Zen-NAS: A Zero-Shot NAS for High-Performance Deep Image Recognition How Fast Compare to Other Zero-Shot NAS Proxies on CIFAR-10/100 Pre-trained Model

190 Dec 29, 2022
Code for NAACL 2021 full paper "Efficient Attentions for Long Document Summarization"

LongDocSum Code for NAACL 2021 paper "Efficient Attentions for Long Document Summarization" This repository contains data and models needed to reprodu

56 Jan 02, 2023
A PyTorch Lightning solution to training OpenAI's CLIP from scratch.

train-CLIP 📎 A PyTorch Lightning solution to training CLIP from scratch. Goal ⚽ Our aim is to create an easy to use Lightning implementation of OpenA

Cade Gordon 396 Dec 30, 2022
TART - A PyTorch implementation for Transition Matrix Representation of Trees with Transposed Convolutions

TART This project is a PyTorch implementation for Transition Matrix Representati

Lee Sael 2 Jan 19, 2022
MIRACLE (Missing data Imputation Refinement And Causal LEarning)

MIRACLE (Missing data Imputation Refinement And Causal LEarning) Code Author: Trent Kyono This repository contains the code used for the "MIRACLE: Cau

van_der_Schaar \LAB 15 Dec 29, 2022
Anomaly detection analysis and labeling tool, specifically for multiple time series (one time series per category)

taganomaly Anomaly detection labeling tool, specifically for multiple time series (one time series per category). Taganomaly is a tool for creating la

Microsoft 272 Dec 17, 2022
[CVPR'20] TTSR: Learning Texture Transformer Network for Image Super-Resolution

TTSR Official PyTorch implementation of the paper Learning Texture Transformer Network for Image Super-Resolution accepted in CVPR 2020. Contents Intr

Multimedia Research 689 Dec 28, 2022
Recall Loss for Semantic Segmentation (This repo implements the paper: Recall Loss for Semantic Segmentation)

Recall Loss for Semantic Segmentation (This repo implements the paper: Recall Loss for Semantic Segmentation) Download Synthia dataset The model uses

32 Sep 21, 2022
CDGAN: Cyclic Discriminative Generative Adversarial Networks for Image-to-Image Transformation

CDGAN CDGAN: Cyclic Discriminative Generative Adversarial Networks for Image-to-Image Transformation CDGAN Implementation in PyTorch This is the imple

Kancharagunta Kishan Babu 6 Apr 19, 2022
Fog Simulation on Real LiDAR Point Clouds for 3D Object Detection in Adverse Weather

LiDAR fog simulation Created by Martin Hahner at the Computer Vision Lab of ETH Zurich. This is the official code release of the paper Fog Simulation

Martin Hahner 110 Dec 30, 2022
WormMovementSimulation - 3D Simulation of Worm Body Movement with Neurons attached to its body

Generate 3D Locomotion Data This module is intended to create 2D video trajector

1 Aug 09, 2022
Official Pytorch Implementation of: "Semantic Diversity Learning for Zero-Shot Multi-label Classification"(2021) paper

Semantic Diversity Learning for Zero-Shot Multi-label Classification Paper Official PyTorch Implementation Avi Ben-Cohen, Nadav Zamir, Emanuel Ben Bar

28 Aug 29, 2022
Official Pytorch implementation of the paper "MotionCLIP: Exposing Human Motion Generation to CLIP Space"

MotionCLIP Official Pytorch implementation of the paper "MotionCLIP: Exposing Human Motion Generation to CLIP Space". Please visit our webpage for mor

Guy Tevet 173 Dec 26, 2022
Recognize numbers from an (28 x 28) image using neural networks

Number recognition Recognize numbers from a 28 x 28 image using neural networks Usage This is an example of a simple usage of number-recognition NOTE:

Mauro Baladés 2 Dec 29, 2021
Multistream CNN for Robust Acoustic Modeling

Multistream Convolutional Neural Network (CNN) A multistream CNN is a novel neural network architecture for robust acoustic modeling in speech recogni

ASAPP Research 37 Sep 21, 2022
Multiview Dataset Toolkit

Multiview Dataset Toolkit Using multi-view cameras is a natural way to obtain a complete point cloud. However, there is to date only one multi-view 3D

11 Dec 22, 2022
DTCN SMP Challenge - Sequential prediction learning framework and algorithm

DTCN This is the implementation of our paper "Sequential Prediction of Social Me

Bobby 2 Jan 24, 2022
(SIGIR2020) “Asymmetric Tri-training for Debiasing Missing-Not-At-Random Explicit Feedback’’

Asymmetric Tri-training for Debiasing Missing-Not-At-Random Explicit Feedback About This repository accompanies the real-world experiments conducted i

yuta-saito 19 Dec 01, 2022
patchmatch和patchmatchstereo算法的python实现

patchmatch patchmatch以及patchmatchstereo算法的python版实现 patchmatch参考 github patchmatchstereo参考李迎松博士的c++版代码 由于patchmatchstereo没有做任何优化,并且是python的代码,主要是方便解析算

Sanders Bao 11 Dec 02, 2022