How can i get the predicted classes from my retinanet model detection over the images.

[Monk5088]

How to get the list of predicted classes for each image in my databunch, i want to map and show predictions of my retinanet model, I have tried using show_results_side_by_side. Still, it only shows the GT and prediction for some images in a batch only, is there any method in the evaluator.py of this repository where I can get the number of predictions for each class, e.g. if my dataset has 10 cycles so can I get the number of predictions where the cycle was detected and where it was detected as some other class, not the tp and fp from compute_class_ap as it gives the rough idea only, I want to display the number of overall correct and wrong predictions for each class.
If you could help me with how I can create such stats it would be really helpful.