i am a little confused …



 ptrblck:

and use matplotlib.pyplot.plot to visualize the loss and accuracy curves.


its okay with the loss, but where is “accuracy”  during training in pytorch Mask R-CNN model ??
  # For Training
  images,targets = next(iter(data_loader))
  images = list(image for image in images)
  targets = [{k: v for k, v in t.items()} for t in targets]
  output = model(images,targets)

 #Output 
 {'loss_box_reg': tensor(0.0100, grad_fn=<DivBackward0>),
 'loss_classifier': tensor(0.2265, grad_fn=<NllLossBackward>),
 'loss_objectness': tensor(0.0190, grad_fn=<BinaryCrossEntropyWithLogitsBackward>),
'loss_rpn_box_reg': tensor(0.0068, grad_fn=<DivBackward0>)}

its just a dictionary of losses … they can be plotted but i am more concerned in accuracy plotting during training … any thoughts ?