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

Related tags

Deep Learninglarger-google-sat2maps-dataset
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.

Houston

Charlotte

Indianapolis

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
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

null 184 Dec 11, 2022
Code release for
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

UBC Computer Vision Group 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

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

Mingrui Yu 3 Jan 7, 2022
Official code for our CVPR '22 paper
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

George Cazenavette 256 Jan 5, 2023
Train a deep learning net with OpenStreetMap features and satellite imagery.
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

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

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

Kunal Wadhwa 2 Jan 5, 2022
A vision library for performing sliced inference on large images/small objects
A vision library for performing sliced inference on large images/small objects

SAHI: Slicing Aided Hyper Inference A vision library for performing sliced inference on large images/small objects Overview Object detection and insta

Open Business Software Solutions 2.3k Jan 4, 2023
Amazon Forest Computer Vision: Satellite Image tagging code using PyTorch / Keras with lots of PyTorch tricks
Amazon Forest Computer Vision: Satellite Image tagging code using PyTorch / Keras with lots of PyTorch tricks

Amazon Forest Computer Vision Satellite Image tagging code using PyTorch / Keras Here is a sample of images we had to work with Source: https://www.ka

Mamy Ratsimbazafy 360 Dec 10, 2022
1st place solution to the Satellite Image Change Detection Challenge hosted by SenseTime
1st place solution to the Satellite Image Change Detection Challenge hosted by SenseTime

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

Lihe Yang 209 Jan 1, 2023
Releases(v1.0)
Owner
Ph.D. student @ UC Berkeley https://taesung.me
GitHub Repository
This reporistory contains the test-dev data of the paper "xGQA: Cross-lingual Visual Question Answering".

This reporistory contains the test-dev data of the paper "xGQA: Cross-lingual Visual Question Answering".

AdapterHub 18 Dec 09, 2022
[IJCAI'21] Deep Automatic Natural Image Matting

Deep Automatic Natural Image Matting [IJCAI-21] This is the official repository of the paper Deep Automatic Natural Image Matting. Introduction | Netw

Jizhizi_Li 316 Jan 06, 2023
Unified Instance and Knowledge Alignment Pretraining for Aspect-based Sentiment Analysis

Unified Instance and Knowledge Alignment Pretraining for Aspect-based Sentiment Analysis Requirements python 3.7 pytorch-gpu 1.7 numpy 1.19.4 pytorch_

12 Oct 29, 2022
Tools for investing in Python

InvestOps Original repository on GitHub Original author is Magnus Erik Hvass Pedersen Introduction This is a Python package with simple and effective

24 Nov 26, 2022
Official implementation for "QS-Attn: Query-Selected Attention for Contrastive Learning in I2I Translation" (CVPR 2022)

QS-Attn: Query-Selected Attention for Contrastive Learning in I2I Translation (CVPR2022) https://arxiv.org/abs/2203.08483 Unpaired image-to-image (I2I

Xueqi Hu 50 Dec 16, 2022
Codes to pre-train T5 (Text-to-Text Transfer Transformer) models pre-trained on Japanese web texts

t5-japanese Codes to pre-train T5 (Text-to-Text Transfer Transformer) models pre-trained on Japanese web texts. The following is a list of models that

Kimio Kuramitsu 1 Dec 13, 2021
Adaptive Denoising Training (ADT) for Recommendation.

DenoisingRec Adaptive Denoising Training for Recommendation. This is the pytorch implementation of our paper at WSDM 2021: Denoising Implicit Feedback

Wenjie Wang 51 Dec 30, 2022
Pytorch code for "DPFM: Deep Partial Functional Maps" - 3DV 2021 (Oral)

DPFM Code for "DPFM: Deep Partial Functional Maps" - 3DV 2021 (Oral) Installation This implementation runs on python = 3.7, use pip to install depend

Souhaib Attaiki 29 Oct 03, 2022
An extremely simple, intuitive, hardware-friendly, and well-performing network structure for LiDAR semantic segmentation on 2D range image. IROS21

FIDNet_SemanticKITTI Motivation Implementing complicated network modules with only one or two points improvement on hardware is tedious. So here we pr

YimingZhao 54 Dec 12, 2022
Unsupervised Foreground Extraction via Deep Region Competition

Unsupervised Foreground Extraction via Deep Region Competition [Paper] [Code] The official code repository for NeurIPS 2021 paper "Unsupervised Foregr

28 Nov 06, 2022
A Keras implementation of CapsNet in the paper: Sara Sabour, Nicholas Frosst, Geoffrey E Hinton. Dynamic Routing Between Capsules

NOTE This implementation is fork of https://github.com/XifengGuo/CapsNet-Keras , applied to IMDB texts reviews dataset. CapsNet-Keras A Keras implemen

Lauro Moraes 5 Oct 23, 2022
Scripts used to make and evaluate OpenAlex's concept tagging model

openalex-concept-tagging This repository contains all of the code for getting the concept tagger up and running. To learn more about where this model

OurResearch 18 Dec 09, 2022
Source code for paper: Knowledge Inheritance for Pre-trained Language Models

Knowledge-Inheritance Source code paper: Knowledge Inheritance for Pre-trained Language Models (preprint). The trained model parameters (in Fairseq fo

THUNLP 31 Nov 19, 2022
PyTorch implementation of "Continual Learning with Deep Generative Replay", NIPS 2017

pytorch-deep-generative-replay PyTorch implementation of Continual Learning with Deep Generative Replay, NIPS 2017 Results Continual Learning on Permu

Junsoo Ha 127 Dec 14, 2022
Generic ecosystem for feature extraction from aerial and satellite imagery

Note: Robosat is neither maintained not actively developed any longer by Mapbox. See this issue. The main developers (@daniel-j-h, @bkowshik) are no l

Mapbox 1.9k Jan 06, 2023
Understanding the Properties of Minimum Bayes Risk Decoding in Neural Machine Translation.

Understanding Minimum Bayes Risk Decoding This repo provides code and documentation for the following paper: Müller and Sennrich (2021): Understanding

ZurichNLP 13 May 01, 2022
This repo contains the code for the paper "Efficient hierarchical Bayesian inference for spatio-temporal regression models in neuroimaging" that has been accepted to NeurIPS 2021.

Dugh-NeurIPS-2021 This repo contains the code for the paper "Efficient hierarchical Bayesian inference for spatio-temporal regression models in neuroi

Ali Hashemi 5 Jul 12, 2022
When BERT Plays the Lottery, All Tickets Are Winning

When BERT Plays the Lottery, All Tickets Are Winning Large Transformer-based models were shown to be reducible to a smaller number of self-attention h

Sai 16 Nov 10, 2022
[ICML 2020] "When Does Self-Supervision Help Graph Convolutional Networks?" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen

When Does Self-Supervision Help Graph Convolutional Networks? PyTorch implementation for When Does Self-Supervision Help Graph Convolutional Networks?

Shen Lab at Texas A&M University 106 Nov 11, 2022
Enhancing Knowledge Tracing via Adversarial Training

Enhancing Knowledge Tracing via Adversarial Training This repository contains source code for the paper "Enhancing Knowledge Tracing via Adversarial T

Xiaopeng Guo 14 Oct 24, 2022