![]() Considering the more popular Google Maps app has Street View support and Google offers a “Street View Studio” web app for contributors, it should be no surprise to learn that the company is now preparing to shut down the Street View app. This standalone app served two distinct groups of people – those who wanted to deeply browse Street View and those who wanted to contribute their own 360° imagery. While the Google Maps app has long offered an easy way to hop into Street View, there has also been a dedicated Street View app on Android and iOS. Google’s Street View is an easy way to get a 360° look at almost any given street on the planet, perfect for getting a sense of your next travel destination or simply exploring the world from the comfort of home. We’ll try to enable those that are closer to being finished, however, to show you how they’ll look in case that they do ship. Keep in mind that Google may or may not ever ship these features, and our interpretation of what they are may be imperfect. When we decompile these files (called APKs, in the case of Android apps), we’re able to see various lines of code within that hint at possible future features. If you don’t have Anaconda installed on your computer, reference the Anaconda Installation section of a guide I previously created.Google is preparing to shut down the dedicated Street View app on Android, keeping the feature in Google Maps.Ībout APK Insight: In this “APK Insight” post, we’ve decompiled the latest version of an application that Google uploaded to the Play Store. At the bottom of the file, input your latitude, longitude, zoom level, and output path. You can obtain the Python script used for this project from. Python Pillow is used to stitch all of the tiles into a complete spherical image. The algorithm I used horizontally concatenates all tiles (width wise) for each row, creating width-wise image strips. The width-wise image strips are then vertically concatenated (height wise) to reconstruct the spherical image. Finally, the reconstructed output image is saved. The total number of tiles downloaded for a given panoramic image is simply the number of rows multiplied by the number of columns. At higher zoom levels, there can hundreds of tiles. Where PANORAMAID = panoramic id found in the metadata, XPOS = column position, and YPOS = row position. The columns and rows need to be calculated as an integer datatype. Next an iterative procedure is used to establish a list of the Google Maps REST API urls needed to obtain all the tiles. The second step involves determining the number or tile rows and columns that will be requested for a given zoom level. First, we need to determine the output resolution for an input zoom level. The first step involves finding the metadata associated with the nearest panoramic image to a provided latitude and longitude. A call is made to Google Maps REST API to obtain metadata in JSON format. Simply replace “LAT” with your latitude and “LNG” with your longitude.Ī request is made using python requests to obtain the JSON metadata and the metadata is converted into a Python dictionary to obtain the values to the fields of interest, such as the panorama identifier label assigned by Google for the unique panoramic image, and overall panoramic image height and width. Reconstructing the tiles into a complete image.īefore getting to the script, I will describe the overall process used by the script to obtain the spherical imagery. Inputting a zoom level to adjust output resolution of the image (1 is lowest resolution, 5 is highest resolution).Ĥ. Obtaining metadata associated with the specific image, specifically the unique panoramic identification label and full image pixel resolution height and width.Ģ. I was recently exploring how to utilize Google Street View depth maps in combination with spherical imagery to reconstruct basic point clouds of city environments. I came across an article describing the process. I created a Python script to compose a panorama using Google Maps REST API using the methodology presented in the article. My script demonstrates:ġ. You can open the raw images in any spherical (360° panoramic) image viewer or use in a VR environment. The purpose of this article is to demonstrate how to obtain complete spherical images captured in Google Street View using Python.
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