title: LSTM object detection tensorflow
body: <p><em>Long story short:</em></p>
  
  <p><strong>How to prepare data for lstm object detection retraining of the tensorflow master github implementation.</strong></p>
  
  <p><em>Long story:</em></p>
  
  <p>Hi all,
  I recently found implementation a lstm object detection algorithm based on this <strong>paper</strong>:
  <a href="http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_Mobile_Video_Object_CVPR_2018_paper.pdf" rel="noreferrer">http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_Mobile_Video_Object_CVPR_2018_paper.pdf</a></p>
  
  <p>at the tensorflow model master <strong>github repository</strong> (<a href="https://github.com/tensorflow/models/tree/master/research/lstm_object_detection" rel="noreferrer">https://github.com/tensorflow/models/tree/master/research/lstm_object_detection</a>)</p>
  
  <p>I would like to <strong>retrain</strong> this implementation on my <strong>own dataset</strong> to evaluate the lstm improvement to other algorithms like SSD. But I keep struggling on how to prepare the data for the training. I've tried the config file of the authors and tried to prepare the data similar to the object-detection-api and also tried to use the same procedure as the <em>inputs/seq_dataset_builder_test.py</em> or <em>inputs/tf_sequence_example_decoder_test.py</em> does. Sadly the github Readme does not provide any information. Someone else created an issue with a similar question on the github repo (<a href="https://github.com/tensorflow/models/issues/5869" rel="noreferrer">https://github.com/tensorflow/models/issues/5869</a>) but the authors did not provide a helpful answer yet. I tried to contact the authors via email a month ago, but didn't got a response. I've also searched the internet but found no solution. Therefore I desperately write to you!</p>
  
  <p><strong><em>Is anybody out there who can explain how to prepare the data for the retraining and how to actually run the retraining.</em></strong> </p>
  
  <p>Thank you for reading, any help is really appreciated!</p>