Software and tools
Data download and description:
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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.