davidhershey / LittlePlaNet

CS231n Project for Winter 2016

City-Recognition

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

Getting Started

Downloading the dataset

• 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

Feature extraction

• 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

Model training

• 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