hhy5277 / google-landmark

Dataset with 5 million images depicting human-made and natural landmarks spanning 200 thousand classes.

Google Landmarks Dataset v2

This is the second version of the Google Landmarks dataset, which contains images annotated with labels representing human-made and natural landmarks. The dataset can be used for landmark recognition and retrieval experiments. This version of the dataset contains approximately 5 million images, split into 3 sets of images: train, index and test.

This dataset is associated to two Kaggle challenges, on landmark recognition and landmark retrieval. Results will be discussed as part of a CVPR'19 workshop. Please visit the Kaggle challenge webpages for more detail on the data.

Currently, only the train dataset is available. The index and test sets will be released with the second stage of the Kaggle challenges.

For reference, the previous version of the Google Landmarks dataset is available here.

Download train set

Download the labels and metadata

• train.csv: CSV with id,url,landmark_id fields. id is a 16-character string, url is a string, landmark_id is an integer. Available at: https://s3.amazonaws.com/google-landmark/metadata/train.csv.

• train_attribution.csv: CSV with id,url,author,license,title fields. id is a 16-character string, and the other fields are strings of variable length. Available at: https://s3.amazonaws.com/google-landmark/metadata/train_attribution.csv.

Downloading the data

The train set is split into 500 TAR files (each of size ~1GB) containing JPG-encoded images. The files are located in the train/ directory, and are named images_000.tar, images_001.tar, ..., images_499.tar. To download them, access the following link:

https://s3.amazonaws.com/google-landmark/train/images_000.tar

And similarly for the other files.

Checking the download

We also make available md5sum files for checking the integrity of the downloaded files. Each md5sum file corresponds to one of the TAR files mentioned above; they are located in the md5sum/train/ directory, with file names md5.images_000.txt, md5.images_001.txt, md5.images_499.txt. For example, the md5sum file corresponding to the images_000.tar file can be found via the following link:

https://s3.amazonaws.com/google-landmark/md5sum/train/md5.images_000.txt

And similarly for the other files.

Extracting the data

We recommend that all 500 TAR files be extracted into the same directory. The directory structure of the image data is as follows: Each image is stored in a directory ${a}/${b}/${c}/${id}.jpg, where ${a}, ${b} and ${c} are the first three letters of the image id, and ${id} is the image id found in train.csv. For example, an image with the id 0123456789abcdef would be stored in 0/1/2/0123456789abcdef.jpg.

train image licenses

All images in the train set have CC-BY licenses without the NonDerivs (ND) restriction. To verify the license for a particular image, please refer to train_attribution.csv.

Dataset licenses

The annotations are licensed by Google under CC BY 4.0 license. The images listed in this dataset are publicly available on the web, and may have different licenses. Google does not own their copyright. Note: while we tried to identify images that are licensed under a Creative Commons Attribution license, we make no representations or warranties regarding the license status of each image and you should verify the license for each image yourself.