summarize box area; update docs

.github/ISSUE_TEMPLATE/unexpected-problems---bugs.md

@@ -44,11 +44,12 @@ If you expect higher speed, please read
 http://tensorpack.readthedocs.io/tutorial/performance-tuning.html
 before posting.
 
-If you expect certain training results (e.g., accuracy), only in one of the two conditions can we help with it:
+If you expect the model to work better, only in one of the two conditions can we help with it:
 (1) You're unable to reproduce the results documented in tensorpack examples.
 (2) It appears to be a tensorpack bug.
 
-Otherwise, how to train a model is a machine learning question.
+Otherwise, how to train a good model on your task or your 
+modifications is a machine learning question.
 We do not answer machine learning questions and it is your responsibility to
 figure out how to make your models more accurate.
 

examples/FasterRCNN/modeling/generalized_rcnn.py

@@ -11,6 +11,7 @@ from tensorpack.tfutils.tower import get_current_tower_context
 
 from config import config as cfg
 from data import get_all_anchors, get_all_anchors_fpn
+from utils.box_ops import area as tf_area
 
 from . import model_frcnn
 from . import model_mrcnn
@@ -73,6 +74,8 @@ class GeneralizedRCNN(ModelDesc):
         proposals, rpn_losses = self.rpn(image, features, anchor_inputs)  # inputs?
 
         targets = [inputs[k] for k in ['gt_boxes', 'gt_labels', 'gt_masks'] if k in inputs]
+        gt_boxes_area = tf.reduce_mean(tf_area(inputs["gt_boxes"]), name='mean_gt_box_area')
+        add_moving_summary(gt_boxes_area)
         head_losses = self.roi_heads(image, features, proposals, targets)
 
         if self.training: