title: TensorFlow Object Detection API trains only one class from several
body: <p>Im running training process with TF Object Detection API on my own dataset with several classes, however after pretty big amount of steps (about 20k) I can see at PerformanceByCategory menu in TensorBoard that mAP is increasing only for one category, other are not even started.</p>
  
  <p><a href="https://i.stack.imgur.com/t1mMh.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/t1mMh.png" alt="enter image description here"></a></p>
  
  <p>My dataset is in PascalVOC format and I was following <a href="https://stackoverflow.com/questions/44973184/train-tensorflow-object-detection-on-own-dataset?noredirect=1&amp;lq=1">this answer</a> to create it. After data preparation I have generated Pascal records, edited label map and pipeline config, downloaded all the staff with ssd model checkpoints to Google Cloud Platform and started training and evaluation jobs accordingly to <a href="https://github.com/tensorflow/models/blob/master/object_detection/g3doc/running_pets.md" rel="nofollow noreferrer">Object Detection API Documentation</a>.</p>
  
  <p>But it seems from TensorBoard that something is wrong with data or something other because nothing happens with my another classes.</p>
  
  <p>Are there any hints or features when training Object Detection API with several classes?</p>
  
  <p>Thanks for any help in advance!</p>
  
  <p><strong>[EDITED]:</strong></p>
  
  <p>So having tried to train model with PascalVOC dataset they provide by default in tutorial I noticed that their Pascal records are much larger than mine. I opened them in text editor and there were references for every class from ImageSets, however my records contain references for only that class I pointed in create_pascal_tf_records.py.</p>
  
  <p>What am I missing guys? Please help!</p>