how to add the overall "precision" and "recall" metrics to "tensorboard" log file, after training is finished?
I believe that you've already done that work: it's the same process as the validation (prediction and check) step you do after training.  You simply tally the results of the four categories (true/false pos/neg) and plug those counts into the equations (ratios) for precision and recall.
After the training is finished and I did the prediction on my network, I want to calculate "precision" and "recall" of my model, and then send it to log file of "tensorboard" to show the plot.
while training, I send "tensorboard" function as a callback to keras. but after training is finished, I dont know how to add some more data to tensorboard to be plotted.
I use keras for coding and tensorflow as its backend.