Variable Message Signal annotated images for object detection

Laburpena

<strong>If you use this dataset, please cite this paper: <em>Puertas, E.; De-Las-Heras, G.; Sánchez-Soriano, J.; Fernández-Andrés, J. Dataset: Variable Message Signal Annotated Images for Object Detection. Data 2022, 7, 41. https://doi.org/10.3390/data7040041</em></strong> This dataset consists of Spanish road images taken from inside a vehicle, as well as annotations in XML files in PASCAL VOC format that indicate the location of Variable Message Signals within them. Also, a CSV file is attached with information regarding the geographic position, the folder where the image is located, and the text in Spanish. This can be used to train supervised learning computer vision algorithms, such as convolutional neural networks. Throughout this work, the process followed to obtain the dataset, image acquisition, and labeling, and its specifications are detailed. The dataset is constituted of <strong>1216</strong> instances, <strong>888</strong> positives, and <strong>328</strong> negatives, in <strong>1152</strong> jpg images with a resolution of 1280x720 pixels. These are divided into <strong>576</strong> real images and <strong>576</strong> images created from the data-augmentation technique. The purpose of this dataset is to help in road computer vision research since there is not one specifically for VMSs. The folder structure of the dataset is as follows: vms_dataset/ data.csv real_images/ imgs/ annotations/ data-augmentation/ imgs/ annotations/ In which: <strong>data.csv:</strong> Each row contains the following information separated by commas (,): image_name, x_min, y_min, x_max, y_max, class_name, lat, long, folder, text. <strong>real_images:</strong> Images extracted directly from the videos. <strong>data-augmentation:</strong> Images created using data-augmentation <strong>imgs:</strong> Image files in .jpg format. <strong>annotations:</strong> Annotation files in .xml format.