pre-trained-model

Thanks to Google, that it provided few pre-trained models with tensorflow API . I would like to know how to retrain a pre-trained model available from the above repository, by adding new classes to the model. For example, COCO dataset trained model has 90 classes, I would like to add 1 or 2 classes to the existing one and get one 92 class object detection model as a result. Running Locally is provided by the repository but it is totally replacing those pre-trained classes with newly trained classes, there only train and eval are mentioned. So, is there any other way to retrain the model and

I created a trainable variable in a scope. Later, I entered the same scope, set the scope to reuse_variables , and used get_variable to retrieve the same variable. However, I cannot set the variable's trainable property to False . My get_variable line is like: weight_var = tf.get_variable('weights', trainable = False) But the variable 'weights' is still in the output of tf.trainable_variables . Can I set a shared variable's trainable flag to False by using get_variable ? The reason I want to do this is that I'm trying to reuse the low-level filters pre-trained from VGG net in my model, and I