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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
+**********************************************