This project is a smale-scale spin on Google DeepMind's PlaNet geolocalization Neural Network. It was developed for CS231n at Stanford University.
Google's PlaNet: http://arxiv.org/abs/1602.05314
- the dataset we used cannot be included in the repo, but we have provided the script we used to download the data from google street view
- you need a google street view account and key to use this script
- create an account here
- after creating an account, get an api key, and store it in a file called "api_key.key" in the main repo directory
- this will allow you to run the script and download the images to use as the dataset
- the dataset downloads images from various cities that have been hard-coded in the
get_dataset.py
script, so change these coordinates if you'd like to focus on different cities
- this project used a pre-trained CNN to extract features for use with a linear classifier
- for access to the trained models, see the model repo
- for extracting features see
extract_features.py
- after extracting features, you can use them with a variety of classification models
- see
linear_classification.py
for an example script for training and evaluating some baseline models on the extracted features