Pratyush Das's repositories
xcube-sh
An xcube plugin to allow generating data cubes from the Sentinel Hub Cloud API
nixos-wsl-starter
A sane, batteries-included starter template for running NixOS on WSL
NixOS-WSL
NixOS on WSL(2) [maintainer=@nzbr]
nixpkgs
Nix Packages collection & NixOS
pint
Operate and manipulate physical quantities in Python
timeseriesAI
Practical Deep Learning for Time Series / Sequential Data using fastai/ Pytorch
otbtf
Deep learning with otb (mirror of https://gitlab.irstea.fr/remi.cresson/otbtf)
xcube
xcube is a Python package for generating and exploiting data cubes powered by xarray, dask, and zarr.
geonode-project
A django template project for creating custom GeoNode projects.
geonode
GeoNode is an open source platform that facilitates the creation, sharing, and collaborative use of geospatial data.
sr4rs
Super resolution for remote sensing
crop-type-mapping
Source code to Rußwurm & Körner 2019. Self-Attention for Raw Optical Satellite Time Series Classification
DeepCropMapping
Official implementation of "DeepCropMapping: A multi-temporal deep learning approach with improved spatial generalizability for dynamic corn and soybean mapping".
resources-earth-observation
A collection of Earth Observation Notebooks.
deeplearning-models
A collection of various deep learning architectures, models, and tips
ee-tensorflow-ts
python notebooks for tensorflow time-series analysis with google earth engine
torchsat
🔥TorchSat 🌏 is an open-source deep learning framework for satellite imagery analysis based on PyTorch.
MTLCC-pytorch
A pytorch implementation of the (Tensorflow) MTLCC network implementation
Deep-Gapfill
Mirror of https://gitlab.irstea.fr/remi.cresson/deep-gapfill
igarss2019-dl4sits
Machine learning for satellite image time series
WebODM
📷 ✈ A free, user-friendly, extendable application and API for drone image processing.
keras-tensorflow-windows-installation
10 easy steps to install Tensorflow-GPU and Keras in Windows
MTLCC
Multi-temporal land cover classification. Source code and evaluation of IJGI 2018 journal publication
Deep-Learning-with-PyTorch
Deep Learning with PyTorch, published by Packt