PASCAL VOC: include more data details, rename layers -> voc_layers

data/pascal/README.md

+# PASCAL VOC and SBD
+
+PASCAL VOC is a standard recognition dataset and benchmark with detection and semantic segmentation challenges.
+The Semantic Boundary Dataset (SBD) is a further annotation of the PASCAL VOC data that provides more semantic segmentation and instance segmentation masks.
+
+PASCAL VOC has a private test set and [leaderboard for semantic segmentation](http://host.robots.ox.ac.uk:8080/leaderboard/displaylb.php?challengeid=11&compid=6).
+
+The train/val/test splits of PASCAL VOC segmentation challenge and SBD diverge.
+Most notably VOC 2011 segval intersects with SBD train.
+Care must be taken for proper evaluation by excluding images from the train or val splits.
+
+We train on the 8,498 images of SBD train.
+We validate on the non-intersecting set defined in the included `seg11valid.txt`.
+
+Refer to `classes.txt` for the listing of classes in model output order.
+Refer to `../voc_layers.py` for the Python data layer for this dataset.
+
+See the dataset sites for download:
+
+- PASCAL VOC 2012: http://host.robots.ox.ac.uk/pascal/VOC/voc2012/
+- SBD: http://www.cs.berkeley.edu/~bharath2/codes/SBD/download.html

data/pascal/classes.txt

+background
+aeroplane
+bicycle
+bird
+boat
+bottle
+bus
+car
+cat
+chair
+cow
+diningtable
+dog
+horse
+motorbike
+person
+pottedplant
+sheep
+sofa
+train
+tvmonitor
+
+and 255 is the ignore label that marks pixels excluded from learning and
+evaluation by the PASCAL VOC ground truth.

voc-fcn16s/net.py

@@ -21,7 +21,7 @@ def fcn(split):
     else:
         pydata_params['voc_dir'] = '../../data/pascal/VOC2011'
         pylayer = 'VOCSegDataLayer'
-    n.data, n.label = L.Python(module='layers', layer=pylayer,
+    n.data, n.label = L.Python(module='voc_layers', layer=pylayer,
             ntop=2, param_str=str(pydata_params))
 
     # the base net

voc-fcn32s/net.py

@@ -21,7 +21,7 @@ def fcn(split):
     else:
         pydata_params['voc_dir'] = '../../data/pascal/VOC2011'
         pylayer = 'VOCSegDataLayer'
-    n.data, n.label = L.Python(module='layers', layer=pylayer,
+    n.data, n.label = L.Python(module='voc_layers', layer=pylayer,
             ntop=2, param_str=str(pydata_params))
 
     # the base net

voc-fcn8s/net.py

@@ -21,7 +21,7 @@ def fcn(split):
     else:
         pydata_params['voc_dir'] = '../../data/pascal/VOC2011'
         pylayer = 'VOCSegDataLayer'
-    n.data, n.label = L.Python(module='layers', layer=pylayer,
+    n.data, n.label = L.Python(module='voc_layers', layer=pylayer,
             ntop=2, param_str=str(pydata_params))
 
     # the base net