PratyushTripathy

ML-For-Beginners

12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

GFPGAN

GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.

learnopencv

Learn OpenCV : C++ and Python Examples

techniques

Techniques for deep learning with satellite & aerial imagery

google-maps-scraper

👋 HOLA 👋 HOLA 👋 HOLA ! ENJOY OUR GOOGLE MAPS SCRAPER 🚀 TO EFFORTLESSLY EXTRACT DATA SUCH AS NAMES, ADDRESSES, PHONE NUMBERS, REVIEWS, WEBSITES, AND RATINGS FROM GOOGLE MAPS WITH EASE! 🤖

Awesome-GEE

A curated list of Google Earth Engine resources

awesome-spectral-indices

A ready-to-use curated list of Spectral Indices for Remote Sensing applications.

awesome-gee-community-datasets

Community Datasets added by users and made available for use at large

GeoSeg

UNetFormer: A UNet-like transformer for efficient semantic segmentation of remote sensing urban scene imagery, ISPRS. Also, including other vision transformers and CNNs for satellite, aerial image and UAV image segmentation.

UTIF.js

Fast and advanced TIFF decoder

LOD2BuildingModel

SAT2LoD2: Automated LoD-2 Model Reconstruction from Satellite-derived DSM and Orthophoto

cropharvest

Open source remote sensing dataset with benchmarks

solar-pv-global-inventory

Repository for machine learning and remote sensing pipeline described in Kruitwagen, L., Story, K., Friedrich, J, et. al. (2019) , used to produce a global inventory of utility-scale solar photvoltaic generating stations.

EO-jobs

🛰️ List of earth observation companies and job sites

Municipal_Spatial_Data

Spatial Data of Municipalities

africa_poverty

india-religion-politics

Data on religion and politics in India

BuildingHeightModel

bap

Best Available Pixel calculation using Google Earth Engine

LandsatLinkr

An automated system for creating spectrally consistent and cloud-free Landsat image time series stacks from a combination of MSS, TM, ETM+, and OLI sensors

s1flood

GEE flood algorithm as described in DeVries et al., Remote Sensing of Environment (2020)

satimage

Code and models for the manuscript "Predicting Poverty and Developmental Statistics from Satellite Images using Multi-task Deep Learning"

random-data-viz

Random data visualizations

simple-ortho

Orthorectify drone and aerial imagery.

satellite_image_segmentation

Experimented with a U-Net variant to perform pixel wise multi-class classification to segment high resolution satellite imagery into land use types with potential applications in deforestation and flood monitoring. Developed with TensorFlow framework.

Human-settlement-extent-detection-from-Sentinel-2-images-via-fully-convolutional-neural-networks-

GHS-S2Net

popgrid_service_demo

DDA_PopulationMapping

Deep learning-based population mapping from Earth observation data in Sub-Saharan Africa

raster-utils