This is a simple class project that uses VLAD feature to build a large scale VPR (Visual Place Recognition) system. Given a query, you can retrieve images similar to the query from a database of images.
More details can be found in the markdown section of the notebook.
Besides some of the common default Python package,you will need numpy, scikit-learn and OpenCV >= 4.4 as the code uses SIFT feature detector that's only available after that specific version.
To run the code on any database of images and with customized query, replace the database_path and query_path to different folders and run the entire notebook. It may takes a while to index all the images in the database.
Currently the code will return the top 1 similar image of a given query. To increase this number, change num_of_imgs accordingly.