Step-0: Setup

See setup.sh for mamba/conda environment.

After setup run mkdir data to create a data directory where outputs will be stored.

Step-1: Downloading ortho imagery

Get raw ortho imagery

Use download_ortho.py to download the raw ortho iamgery from New York's GIS data website.

Processing ortho imagery

The ortho imagery are in format not suitable for deep learning applications. So we first convert it into computer vision format.

run the following three scripts:

python3 convert_orthojp22jpg.py

This converts jp2 images to jpeg images. Then to get geocoordinate bounds of these images run get_ortho_bounds.py

python3 get_ortho_bounds.py

After getting bounds for ortho images, use get_cropped_image_coordinates.py to get cropped image bounds for the corresponding ground images.

python3 get_cropped_image_coordinates.py

Finally, run

python3 get_cropped_images.py

to obtain the cropeed images corresponding to ground images. You can also change dimensions etc of these images to increase the span.

Step-2 Download streetview images.

For street locations, Openstreetmap extracts are also needed along with the shapefile. The NYC shapefile is already in the repo.

bbbike is the best source for this.

• Just select your area of interest either using bounding box aor polygon tool. (Select the 5 boroughs of NYC.)
• Remember to download in OSM XML gzip'd format.
• After clicking extract it redirects you to download page. Once the download is ready move it to the 'data/cities_osm' directory.
• Extract the osm.gz file.

gunzip -k ../data/cities_osm/nyc.osm.gz

Once the osm is downloaded first run save_streetview_heading.py to save the heading direction for each location. This saves the direction in which GSV car is heading and results in consitent views.

Obtain google cloud api key:

• Follow the instructions on the google api page to see instrutions on obtaining the api key.
• Put the api key in the streetview_downloader.py, google_key variable.