title: What exactly are the losses in Matterport Mask-R-CNN?
body: <p>I use Mask-R-CNN to train my data with it. When i use TensorBoard to see the result, i have the <strong>loss,</strong> <strong>mrcnn_bbox_loss</strong>, <strong>mrcnn_class_loss</strong>, <strong>mrcnn_mask_loss</strong>, <strong>rpn_bbox_loss</strong>, <strong>rpn_class_loss</strong> and all the same 6 loss for the validation: <strong>val_loss,</strong> <strong>val_mrcnn_bbox_loss</strong> etc. </p>
  
  <p>I want to know what is each loss exactly. </p>
  
  <p>Also i want to know if the first 6 losses are the train loss or what are they? If they aren't the train loss, how can i see the train loss?</p>
  
  <p>My guess is:</p>
  
  <p><strong>loss</strong>: it's all the 5 losses in summary (but i don't know how TensorBoard summarizes it).</p>
  
  <p><strong>mrcnn_bbox_loss</strong>: is the size of the bounding box correct or not? </p>
  
  <p><strong>mrcnn_class_loss</strong>: is the class correct? is the pixel correctly assign to the class?</p>
  
  <p><strong>mrcnn_mask_loss</strong>: is the shape of the instance correct or not? is the pixel correctly assign to the instance?</p>
  
  <p><strong>rpn_bbox_loss</strong>:  is the size of the bbox correct?</p>
  
  <p><strong>rpn_class_loss</strong>: is the class of the bbox correct?</p>
  
  <p>But i am pretty sure this is not right...</p>
  
  <p>And are some lossed irrelevant if i have only 1 class? For example only the background and 1 other class?</p>
  
  <p>My data have only the background and 1 other class and this is my result on TensorBoard:</p>
  
  <p><a href="https://i.stack.imgur.com/z4plk.png" rel="noreferrer"><img src="https://i.stack.imgur.com/z4plk.png" alt="Result 1:"></a><a href="https://i.stack.imgur.com/yVMeK.png" rel="noreferrer"><img src="https://i.stack.imgur.com/yVMeK.png" alt="Result 2:"></a><a href="https://i.stack.imgur.com/P5J1Z.png" rel="noreferrer"><img src="https://i.stack.imgur.com/P5J1Z.png" alt="Result 3:"></a><a href="https://i.stack.imgur.com/aIb5Z.png" rel="noreferrer"><img src="https://i.stack.imgur.com/aIb5Z.png" alt="Result :4"></a></p>
  
  <p>My prediction is ok, but i don't know why some losses from my validation is going up and down at the end... I thought it has to be first only down and after overfitting only up.
  The prediction i used is the green line on TensorBoard with the most epochs. I am not sure if my Network is overfitted, therfore i am wondering why some losses in the validation look how they look...</p>
  
  <p>Here is my prediction:
  <a href="https://i.stack.imgur.com/ovIts.png" rel="noreferrer"><img src="https://i.stack.imgur.com/ovIts.png" alt="Example of my Trainset:"></a>
  <a href="https://i.stack.imgur.com/yPVH0.png" rel="noreferrer"><img src="https://i.stack.imgur.com/yPVH0.png" alt="This is the Ground Truth of my Testset example:"></a>
  <a href="https://i.stack.imgur.com/hnHaM.png" rel="noreferrer"><img src="https://i.stack.imgur.com/hnHaM.png" alt="This is the prediction from the Testset example:"></a></p>