What you see is what you get: Delineating the urban jobs-housing spatial distribution at a parcel scale by using street view imagery

The compressed package (Study_code.zip) contains the code files implemented by an under review paper ("What you see is what you get: Delineating urban jobs-housing spatial distribution at a parcel scale by using street view imagery based on deep learning technique").
The compressed package (input_land_parcel_with_attributes.zip) is the sampled mixed "jobs-housing" attributes data of the study area with multiple probability attributes (Only working, Only living, working and living) at the land parcel scale.
The compressed package (input_street_view_images.zip) is the surrounding street view data near sampled land parcels (input_land_parcel_with_attributes.zip) with the pixel size of 240*160 obtained from Tencent map (https://map.qq.com/).

The compressed package (output_results.zip) contains the result vector files (Jobs-housing pattern distribution and error distribution) and file description (Readme.txt).
This project uses some Python open source libraries (Numpy, Pandas, Selenium, Gdal, Pytorch and sklearn). This project complies with the GPL license.
Numpy (https://numpy.org/) is an open source numerical calculation tool developed by Travis Oliphant. Used in this project for matrix operation. This library complies with the BSD license.
Pandas (https://pandas.pydata.org/) is an open source library, providing high-performance, easy-to-use data structures and data analysis tools. This library complies with the BSD license.
Selenium(https://www.selenium.dev/) is a suite of tools for automating web browsers.Used in this project for getting street view images.This library complies with the BSD license.
Gdal(https://gdal.org/) is a translator library for raster and vector geospatial data formats.Used in this project for processing geospatial data.This library complies with the BSD license.
Pytorch(https://pytorch.org/) is an open source machine learning framework that accelerates the path from research prototyping to production deployment.Used in this project for deep learning.This library complies with the BSD license.
sklearn(https://scikit-learn.org/) is an open source machine learning tool for python.Used in this project for comparing precision metrics.This library complies with the BSD license.