Software and tools

Data download and description:

Access to the data is password protected. Register and accept the terms and conditions from Codalab competition server to get the authentication information.

Terms of use: The data of this track (cultural event classification) are available only for open research and educational purposes, within the scope of the challenge. ChaLearn and the organizers make no warranties regarding the database, including but not limited to warranties of non-infringement or fitness for a particular purpose. The copyright of the images remain the property of their respective owners. By downloading and making use of the data, you accept full responsibility for using the data. You shall defend and indemnify ChaLearn and the organizers, including their employees, Trustees, officers and agents, against any and all claims arising from your use of the data. You agree not to redistribute the data without this notice.


The dataset is composed by 50 cultural events, containing more than 11000 images manually labelled in total. The data has been split into 50% for training, 20% validation and 30% for testing. The distributions of images by category are approximately equal. In this first stage, we provide two ZIP files containing the images for the training and validation sets. Additionaly, we provide a file for each category with the labels for the training and validation images. The participants will evaluate their methods in the validation set. Then, in the second stage we will provide the test set to measure their final results.


For this track, class-specific image sets with per-image ground truth are provided. The file 


contains image identifiers and ground truth for a particular category and image set, for example the file San_Fermin_train.txt applies to the `San Fermin' cultural event and train image set. Each line of the file contains a single image identifier and ground truth label, separated by a space, for example:

    001045.jpg -1
    006547.jpg -1
    012548.jpg  1

There are two ground truth labels:

-1: Negative: The image does not belong to the category of interest. A classifier should give a `negative' output.

1:  Positive: The image belongs to the class of interest. A classifier should give a `positive' output.


There are no news registered in Cultural Event V1 (CVPR '15)