title: How do I use the Object Detection API to evaulate an own custom model? What do I write into the config files?
body: <p>I have a custom object detection model that I can call with <code>model = MyModel()</code> and <code>model.loadweights(checkpoint)</code> and I want to evaluate it using the Object Detection API.</p>
  <p>From what I understood there are two possibilities, either I use the legacy eval.py, there I don't know, what to put into the pipeline_config file</p>
  <p>Or I use the newer version that is implemented in model_main_tf2.py, but there I would have to save my model as model.config and I don't know what to put the pipeline file either.</p>
  <p>Since my model is a YOLO model, it is not included in the sample once yet.</p>
  <p><a href="https://github.com/tensorflow/models/tree/master/research/object_detection/configs/tf2" rel="nofollow noreferrer">https://github.com/tensorflow/models/tree/master/research/object_detection/configs/tf2</a></p>
  <p>Would really appreciate the help!</p>