A large dataset of 100k Google Satellite and matching Map images, resembling pix2pix's Google Maps dataset.

Last update: Dec 28, 2022

Overview

Larger Google Sat2Map dataset

This dataset extends the aerial ⟷ Maps dataset used in pix2pix (Isola et al., CVPR17). The provide script download_sat2maps.py scrapes pairs of matching Maps and Satellite images using the Google Maps API from the 22 most populous cities in the United States.

Following pix2pix, the pair of satellite and map images are concatenated side-by-side into one image like below.

Occasionally, the satellite or the map image are not provided by the API, or simply not interesting like entirely water or forest. prune_out_uninteresting_regions.py prunes away these uninteresting regions using simple thresholding on the standard deviation on the color distribution of the Map images.

Using this script, an example dataset of roughly 100k images were gathered and pruned, and it can be downloaded from this link. The samples were random split into train / val set of size 92376 / 275. Since the coordinates of each image are randomly and independently sampled, it is possible that there exists overlap between the splits.

You might also like...

Official Implementation and Dataset of "PPR10K: A Large-Scale Portrait Photo Retouching Dataset with Human-Region Mask and Group-Level Consistency", CVPR 2021

Portrait Photo Retouching with PPR10K Paper | Supplementary Material PPR10K: A Large-Scale Portrait Photo Retouching Dataset with Human-Region Mask an

184 Dec 11, 2022

Code release for "COTR: Correspondence Transformer for Matching Across Images"

COTR: Correspondence Transformer for Matching Across Images This repository contains the inference code for COTR. We plan to release the training code

360 Jan 6, 2023

Space robot - (Course Project) Using the space robot to capture the target satellite that is disabled and spinning, then stabilize and fix it up

3 Jan 7, 2022

Official code for our CVPR '22 paper "Dataset Distillation by Matching Training Trajectories"

Dataset Distillation by Matching Training Trajectories Project Page | Paper This repo contains code for training expert trajectories and distilling sy

256 Jan 5, 2023

Train a deep learning net with OpenStreetMap features and satellite imagery.

DeepOSM Classify roads and features in satellite imagery, by training neural networks with OpenStreetMap (OSM) data. DeepOSM can: Download a chunk of

1.3k Nov 24, 2022

To propose and implement a multi-class classification approach to disaster assessment from the given data set of post-earthquake satellite imagery.

2 Jan 5, 2022

A vision library for performing sliced inference on large images/small objects

A large dataset of 100k Google Satellite and matching Map images, resembling pix2pix's Google Maps dataset.

Related tags

Overview

Larger Google Sat2Map dataset

You might also like...

Official Implementation and Dataset of "PPR10K: A Large-Scale Portrait Photo Retouching Dataset with Human-Region Mask and Group-Level Consistency", CVPR 2021

Code release for "COTR: Correspondence Transformer for Matching Across Images"

Space robot - (Course Project) Using the space robot to capture the target satellite that is disabled and spinning, then stabilize and fix it up

Official code for our CVPR '22 paper "Dataset Distillation by Matching Training Trajectories"

Train a deep learning net with OpenStreetMap features and satellite imagery.

To propose and implement a multi-class classification approach to disaster assessment from the given data set of post-earthquake satellite imagery.

A vision library for performing sliced inference on large images/small objects

Amazon Forest Computer Vision: Satellite Image tagging code using PyTorch / Keras with lots of PyTorch tricks

1st place solution to the Satellite Image Change Detection Challenge hosted by SenseTime

Releases(v1.0)

v1.0(Jun 20, 2021)

Owner

A variational Bayesian method for similarity learning in non-rigid image registration (CVPR 2022)

Repository for the paper "PoseAug: A Differentiable Pose Augmentation Framework for 3D Human Pose Estimation", CVPR 2021.

Industrial knn-based anomaly detection for images. Visit streamlit link to check out the demo.

Multi-label classification of retinal disorders

NLP From Scratch Without Large-Scale Pretraining: A Simple and Efficient Framework

Implementation of several Bayesian multi-target tracking algorithms, including Poisson multi-Bernoulli mixture filters for sets of targets and sets of trajectories. The repository also includes the GOSPA metric and a metric for sets of trajectories to evaluate performance.

Implementation of the HMAX model of vision in PyTorch

Weight initialization schemes for PyTorch nn.Modules

The pyrelational package offers a flexible workflow to enable active learning with as little change to the models and datasets as possible

Classify the disease status of a plant given an image of a passion fruit

[ICCV'21] Neural Radiance Flow for 4D View Synthesis and Video Processing

Official code for 'Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentationon Complex Urban Driving Scenes'

PyTorch implementation code for the paper MixCo: Mix-up Contrastive Learning for Visual Representation

Official repository for "On Improving Adversarial Transferability of Vision Transformers" (2021)

Doing fast searching of nearest neighbors in high dimensional spaces is an increasingly important problem

Replication Package for "An Empirical Study of the Effectiveness of an Ensemble of Stand-alone Sentiment Detection Tools for Software Engineering Datasets"

Validated, scalable, community developed variant calling, RNA-seq and small RNA analysis

[ACMMM 2021 Oral] Enhanced Invertible Encoding for Learned Image Compression

GeneDisco is a benchmark suite for evaluating active learning algorithms for experimental design in drug discovery.

Code and results accompanying our paper titled Mixture Proportion Estimation and PU Learning: A Modern Approach at Neurips 2021 (Spotlight)