The general workflow sounds good.
However, I’m not sure about this part:



 shafei:

(0 means the object exists with a low probability and one means it exists with a high probability)


Would this mean that you won’t pass any images without the class?
Your model would thus only learn to predict the object class for each sample.



 shafei:

Only problem I am thinking about can I use the 0 and the 1 (high and low probability) to set up a better preforming network.


You could try to apply a loss weighting based on the low and high probability, i.e. you could reduce the loss for a low probability class to decrease the penalty for your model.