As mentioned in my other thread (Tensorflow Object Detection - Avoid overlapping boxes) I'm new to machine learning and I have to implement an algorithm for detecting traffic lights.
Regarding Tensorflow and it's possibilities, I've got a whole bunch of questions I don't know where to ask except Stack Overflow.
For a quick start I've downloaded a pre trained model and started training it using the Bosch Traffic Lights Dataset. Using a pre trained model is fine but every now and then I wonder if it's possible to modify this model (add or remove a layer) or if it would be best to use keras on top of tf for better customization possibilities.
Additionally I wonder how I should know what are the possible configurations in the pipeline.config file inside every pre trained model. Is there any documentation or do I have to dig into the python files to get into it? In other words, does it even make any sense to change the configuration?
For documentation purpose we're using tensorboard. Unfortunately there's no accuracy (but loss) documented out of the box - how do we get the accuracy displayed as an additional graph?