This work aims at data preparation for OCR systems based on recurrent neural networks. Precisely annotated data are necessary for training a network as well as for evaluation of OCR methods. It is possible to synthesize the data, however such data are not that realistic as the real ones. Manual annotation is thus still needed in many cases, especially in the case of historical documents we are focusing on. Although there are several complex systems for historical document processing, to the best of our knowledge, a simple annotation tool for OCR data is completely missing. Therefore, we propose and implement a set of tools utilizing artificial intelligence that simplify the annotation process. These tools create ground truths for line images that are used for training of nowadays OCR systems. Another contribution of this paper is making these tools freely available for research purposes.