Training
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********************************************** The German Traffic Sign Recognition Benchmark ********************************************** This archive contains the training set of the "German Traffic Sign Recognition Benchmark". This training set is supposed be used for the online competition as part of the IJCNN 2011 competition. It is a subset of the final training set that will be published after the online competition is closed. ********************************************** Archive content ********************************************** This archive contains the following structure: There is one directory for each of the 43 classes (0000 - 00043). Each directory contains the corresponding training images and one text file with annotations, eg. GT-00000.csv. ********************************************** Image format and naming ********************************************** The images are PPM images (RGB color). Files are numbered in two parts: XXXXX_YYYYY.ppm The first part, XXXXX, represents the track number. All images of one class with identical track numbers originate from one single physical traffic sign. The second part, YYYYY, is a running number within the track. The temporal order of the images is preserved. ********************************************** Annotation format ********************************************** The annotations are stored in CSV format (field separator is ";" (semicolon) ). The annotations contain meta information about the image and the class id. In detail, the annotations provide the following fields: Filename - Image file the following information applies to Width, Height - Dimensions of the image Roi.x1,Roi.y1, Roi.x2,Roi.y2 - Location of the sign within the image (Images contain a border around the actual sign of 10 percent of the sign size, at least 5 pixel) ClassId - The class of the traffic sign ********************************************** Further information ********************************************** For more information on the competition procedures and to obtain the test set, please visit the competition website at http://benchmark.ini.rub.de If you have any questions, do not hesitate to contact us tsr-benchmark@ini.rub.de ********************************************** Institut für Neuroinformatik Real-time computer vision research group Ruhr-Universität Bochum Germany **********************************************