Python Satellite-prediction Resources

pyroSAR A Python Framework for Large-Scale SAR Satellite Data Processing The pyroSAR package aims at providing a complete solution for the scalable or

untiler Utility to take a directory of {z}/{x}/{y}.(jpg|png) tiles, and stitch into a scenetiff (tif w/ exact merc tile bounds). Future versions will

rio-cogeo Cloud Optimized GeoTIFF (COG) creation and validation plugin for Rasterio. Documentation: https://cogeotiff.github.io/rio-cogeo/ Source Code

rio-tiler User friendly Rasterio plugin to read raster datasets. Documentation: https://cogeotiff.github.io/rio-tiler/ Source Code: https://github.com

rio-color A rasterio plugin for applying basic color-oriented image operations to geospatial rasters. Goals No heavy dependencies: rio-color is purpos

rio-hist Histogram matching plugin for rasterio. Provides a CLI and python module for adjusting colors based on histogram matching in a variety of col

Landsat-util Landsat-util is a command line utility that makes it easy to search, download, and process Landsat imagery. Docs For full documentation v

PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning The predictive learning of spatiotemporal sequences aims to generate future

Completer: Incomplete Multi-view Clustering via Contrastive Prediction This repo contains the code and data of the following paper accepted by CVPR 20

Joint Entity and Relation Extraction with Set Prediction Networks Source code for Joint Entity and Relation Extraction with Set Prediction Networks. W

Official PyTorch code for Transformers Solve Limited Receptive Field for Monocular Depth Prediction. Guanglei Yang, Hao Tang, Mingli Ding, Nicu Sebe,

scikit-multilearn scikit-multilearn is a Python module capable of performing multi-label learning tasks. It is built on-top of various scientific Pyth

DESlib DESlib is an easy-to-use ensemble learning library focused on the implementation of the state-of-the-art techniques for dynamic classifier and

Torch-Struct: Structured Prediction Library A library of tested, GPU implementations of core structured prediction algorithms for deep learning applic

GluonTS - Probabilistic Time Series Modeling in Python GluonTS is a Python toolkit for probabilistic time series modeling, built around Apache MXNet (

sentinelsat Sentinelsat makes searching, downloading and retrieving the metadata of Sentinel satellite images from the Copernicus Open Access Hub easy

Satpy The Satpy package is a python library for reading and manipulating meteorological remote sensing data and writing it to various image and data f

Rasterio Rasterio reads and writes geospatial raster data. Geographic information systems use GeoTIFF and other formats to organize and store gridded,

WIMP - What If Motion Predictor Reference PyTorch Implementation for What If Motion Prediction [PDF] [Dynamic Visualizations] Setup Requirements The W

Feel free to visit my homepage Robust Long-Term Object Tracking via Improved Discriminative Model Prediction (RLT-DIMP) [ECCVW2020 paper] Presentation

PG-MORL This repository contains the implementation for the paper Prediction-Guided Multi-Objective Reinforcement Learning for Continuous Robot Contro

Vision Transformers for Dense Prediction This repository contains code and models for our paper: Vision Transformers for Dense Prediction René Ranftl,

LPC_for_TTS Linear Prediction Coefficients estimation from mel-spectrogram implemented in Python based on Levinson-Durbin algorithm. 基于Levinson-Durbin

merged_depth runs (1) AdaBins, (2) DiverseDepth, (3) MiDaS, (4) SGDepth, and (5) Monodepth2, and calculates a weighted-average per-pixel absolute dept

whatthelang Lightning Fast Language Prediction 🚀 Dependencies The dependencies can be installed using the requirements.txt file: $ pip install -r req

NeurIPS 2020 SEVIR Code for paper: SEVIR : A Storm Event Imagery Dataset for Deep Learning Applications in Radar and Satellite Meteorology Requirement

FiGNN for CTR prediction The code and data for our paper in CIKM2019: Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Predicti

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TrajNet++ : The Trajectory Forecasting Framework PyTorch implementation of Human Trajectory Forecasting in Crowds: A Deep Learning Perspective TrajNet

FLAVR is a fast, flow-free frame interpolation method capable of single shot multi-frame prediction. It uses a customized encoder decoder architecture with spatio-temporal convolutions and channel gating to capture and interpolate complex motion trajectories between frames to generate realistic high frame rate videos. This repository contains original source code for the paper accepted to CVPR 2021.

A supervised domain-agnostic framework that allows for probabilistic modelling, namely the prediction of probability distributions for individual data

======== FairML: Auditing Black-Box Predictive Models FairML is a python toolbox auditing the machine learning models for bias. Description Predictive

Stacking (stacked generalization) Overview ikki407/stacking - Simple and useful stacking library, written in Python. User can use models of scikit-lea

MLBox is a powerful Automated Machine Learning python library. It provides the following features: Fast reading and distributed data preprocessing/cle

scikit-multilearn scikit-multilearn is a Python module capable of performing multi-label learning tasks. It is built on-top of various scientific Pyth

The 3rd place solution for competition "Lyft Motion Prediction for Autonomous Vehicles" at Kaggle Team behind this solution: Artsiom Sanakoyeu [Homepa

cnn_age_gender Age and Gender prediction using Keras Dataset example : Description : UTKFace dataset is a large-scale face dataset with long age span

Lyft Motion Prediction for Autonomous Vehicles Code for the 4th place solution of Lyft Motion Prediction for Autonomous Vehicles on Kaggle. Discussion

Rugby score prediction An end-to-end machine learning web app to predict rugby scores Overview An demo project to provide a high-level overview of the

windml Build status : The importance of wind in smart grids with a large number of renewable energy resources is increasing. With the growing infrastr

The easiest way to build Machine Learning APIs BentoML makes moving trained ML models to production easy: Package models trained with any ML framework

StellarGraph Machine Learning Library StellarGraph is a Python library for machine learning on graphs and networks. Table of Contents Introduction Get