align proto defs with net spec: VOC paths, dropout, and module name

voc-fcn-alexnet/net.py

@@ -18,12 +18,12 @@ def fcn(split):
     pydata_params = dict(split=split, mean=(104.00699, 116.66877, 122.67892),
             seed=1337)
     if split == 'train':
-        pydata_params['sbdd_dir'] = '../../data/sbdd/dataset'
+        pydata_params['sbdd_dir'] = '../data/sbdd/dataset'
         pylayer = 'SBDDSegDataLayer'
     else:
-        pydata_params['voc_dir'] = '../../data/pascal/VOC2011'
+        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-fcn-alexnet/train.prototxt

@@ -6,7 +6,7 @@ layer {
   python_param {
     module: "voc_layers"
     layer: "SBDDSegDataLayer"
-    param_str: "{\'sbdd_dir\': \'../../data/sbdd/dataset\', \'seed\': 1337, \'split\': \'train\', \'mean\': (104.00699, 116.66877, 122.67892)}"
+    param_str: "{\'sbdd_dir\': \'../data/sbdd/dataset\', \'seed\': 1337, \'split\': \'train\', \'mean\': (104.00699, 116.66877, 122.67892)}"
   }
 }
 layer {

voc-fcn-alexnet/val.prototxt

@@ -6,7 +6,7 @@ layer {
   python_param {
     module: "voc_layers"
     layer: "VOCSegDataLayer"
-    param_str: "{\'voc_dir\': \'../../data/pascal/VOC2011\', \'seed\': 1337, \'split\': \'seg11valid\', \'mean\': (104.00699, 116.66877, 122.67892)}"
+    param_str: "{\'voc_dir\': \'../data/pascal/VOC2011\', \'seed\': 1337, \'split\': \'seg11valid\', \'mean\': (104.00699, 116.66877, 122.67892)}"
   }
 }
 layer {

voc-fcn16s/train.prototxt

@@ -428,6 +428,15 @@ layer {
   bottom: "fc6"
   top: "fc6"
 }
+layer {
+  name: "drop6"
+  type: "Dropout"
+  bottom: "fc6"
+  top: "fc6"
+  dropout_param {
+    dropout_ratio: 0.5
+  }
+}
 layer {
   name: "fc7"
   type: "Convolution"
@@ -454,6 +463,15 @@ layer {
   bottom: "fc7"
   top: "fc7"
 }
+layer {
+  name: "drop7"
+  type: "Dropout"
+  bottom: "fc7"
+  top: "fc7"
+  dropout_param {
+    dropout_ratio: 0.5
+  }
+}
 layer {
   name: "score_fr"
   type: "Convolution"

voc-fcn16s/val.prototxt

@@ -428,6 +428,15 @@ layer {
   bottom: "fc6"
   top: "fc6"
 }
+layer {
+  name: "drop6"
+  type: "Dropout"
+  bottom: "fc6"
+  top: "fc6"
+  dropout_param {
+    dropout_ratio: 0.5
+  }
+}
 layer {
   name: "fc7"
   type: "Convolution"
@@ -454,6 +463,15 @@ layer {
   bottom: "fc7"
   top: "fc7"
 }
+layer {
+  name: "drop7"
+  type: "Dropout"
+  bottom: "fc7"
+  top: "fc7"
+  dropout_param {
+    dropout_ratio: 0.5
+  }
+}
 layer {
   name: "score_fr"
   type: "Convolution"

voc-fcn32s/net.py

@@ -16,10 +16,10 @@ def fcn(split):
     pydata_params = dict(split=split, mean=(104.00699, 116.66877, 122.67892),
             seed=1337)
     if split == 'train':
-        pydata_params['sbdd_dir'] = '../../data/sbdd/dataset'
+        pydata_params['sbdd_dir'] = '../data/sbdd/dataset'
         pylayer = 'SBDDSegDataLayer'
     else:
-        pydata_params['voc_dir'] = '../../data/pascal/VOC2011'
+        pydata_params['voc_dir'] = '../data/pascal/VOC2011'
         pylayer = 'VOCSegDataLayer'
     n.data, n.label = L.Python(module='voc_layers', layer=pylayer,
             ntop=2, param_str=str(pydata_params))

voc-fcn32s/train.prototxt

@@ -6,7 +6,7 @@ layer {
   python_param {
     module: "voc_layers"
     layer: "SBDDSegDataLayer"
-    param_str: "{\'sbdd_dir\': \'../../data/sbdd/dataset\', \'seed\': 1337, \'split\': \'train\', \'mean\': (104.00699, 116.66877, 122.67892)}"
+    param_str: "{\'sbdd_dir\': \'../data/sbdd/dataset\', \'seed\': 1337, \'split\': \'train\', \'mean\': (104.00699, 116.66877, 122.67892)}"
   }
 }
 layer {
@@ -428,6 +428,15 @@ layer {
   bottom: "fc6"
   top: "fc6"
 }
+layer {
+  name: "drop6"
+  type: "Dropout"
+  bottom: "fc6"
+  top: "fc6"
+  dropout_param {
+    dropout_ratio: 0.5
+  }
+}
 layer {
   name: "fc7"
   type: "Convolution"
@@ -454,6 +463,15 @@ layer {
   bottom: "fc7"
   top: "fc7"
 }
+layer {
+  name: "drop7"
+  type: "Dropout"
+  bottom: "fc7"
+  top: "fc7"
+  dropout_param {
+    dropout_ratio: 0.5
+  }
+}
 layer {
   name: "score_fr"
   type: "Convolution"

voc-fcn32s/val.prototxt

@@ -6,7 +6,7 @@ layer {
   python_param {
     module: "voc_layers"
     layer: "VOCSegDataLayer"
-    param_str: "{\'voc_dir\': \'../../data/pascal/VOC2011\', \'seed\': 1337, \'split\': \'seg11valid\', \'mean\': (104.00699, 116.66877, 122.67892)}"
+    param_str: "{\'voc_dir\': \'../data/pascal/VOC2011\', \'seed\': 1337, \'split\': \'seg11valid\', \'mean\': (104.00699, 116.66877, 122.67892)}"
   }
 }
 layer {
@@ -428,6 +428,15 @@ layer {
   bottom: "fc6"
   top: "fc6"
 }
+layer {
+  name: "drop6"
+  type: "Dropout"
+  bottom: "fc6"
+  top: "fc6"
+  dropout_param {
+    dropout_ratio: 0.5
+  }
+}
 layer {
   name: "fc7"
   type: "Convolution"
@@ -454,6 +463,15 @@ layer {
   bottom: "fc7"
   top: "fc7"
 }
+layer {
+  name: "drop7"
+  type: "Dropout"
+  bottom: "fc7"
+  top: "fc7"
+  dropout_param {
+    dropout_ratio: 0.5
+  }
+}
 layer {
   name: "score_fr"
   type: "Convolution"

voc-fcn8s-atonce/net.py

@@ -16,10 +16,10 @@ def fcn(split):
     pydata_params = dict(split=split, mean=(104.00699, 116.66877, 122.67892),
             seed=1337)
     if split == 'train':
-        pydata_params['sbdd_dir'] = '../../data/sbdd/dataset'
+        pydata_params['sbdd_dir'] = '../data/sbdd/dataset'
         pylayer = 'SBDDSegDataLayer'
     else:
-        pydata_params['voc_dir'] = '../../data/pascal/VOC2011'
+        pydata_params['voc_dir'] = '../data/pascal/VOC2011'
         pylayer = 'VOCSegDataLayer'
     n.data, n.label = L.Python(module='voc_layers', layer=pylayer,
             ntop=2, param_str=str(pydata_params))

voc-fcn8s-atonce/train.prototxt

@@ -6,7 +6,7 @@ layer {
   python_param {
     module: "voc_layers"
     layer: "SBDDSegDataLayer"
-    param_str: "{\'sbdd_dir\': \'../../data/sbdd/dataset\', \'seed\': 1337, \'split\': \'train\', \'mean\': (104.00699, 116.66877, 122.67892)}"
+    param_str: "{\'sbdd_dir\': \'../data/sbdd/dataset\', \'seed\': 1337, \'split\': \'train\', \'mean\': (104.00699, 116.66877, 122.67892)}"
   }
 }
 layer {

voc-fcn8s-atonce/val.prototxt

@@ -6,7 +6,7 @@ layer {
   python_param {
     module: "voc_layers"
     layer: "VOCSegDataLayer"
-    param_str: "{\'voc_dir\': \'../../data/pascal/VOC2011\', \'seed\': 1337, \'split\': \'seg11valid\', \'mean\': (104.00699, 116.66877, 122.67892)}"
+    param_str: "{\'voc_dir\': \'../data/pascal/VOC2011\', \'seed\': 1337, \'split\': \'seg11valid\', \'mean\': (104.00699, 116.66877, 122.67892)}"
   }
 }
 layer {

voc-fcn8s/net.py

@@ -16,10 +16,10 @@ def fcn(split):
     pydata_params = dict(split=split, mean=(104.00699, 116.66877, 122.67892),
             seed=1337)
     if split == 'train':
-        pydata_params['sbdd_dir'] = '../../data/sbdd/dataset'
+        pydata_params['sbdd_dir'] = '../data/sbdd/dataset'
         pylayer = 'SBDDSegDataLayer'
     else:
-        pydata_params['voc_dir'] = '../../data/pascal/VOC2011'
+        pydata_params['voc_dir'] = '../data/pascal/VOC2011'
         pylayer = 'VOCSegDataLayer'
     n.data, n.label = L.Python(module='voc_layers', layer=pylayer,
             ntop=2, param_str=str(pydata_params))

voc-fcn8s/train.prototxt

@@ -6,7 +6,7 @@ layer {
   python_param {
     module: "voc_layers"
     layer: "SBDDSegDataLayer"
-    param_str: "{\'sbdd_dir\': \'../../data/sbdd/dataset\', \'seed\': 1337, \'split\': \'train\', \'mean\': (104.00699, 116.66877, 122.67892)}"
+    param_str: "{\'sbdd_dir\': \'../data/sbdd/dataset\', \'seed\': 1337, \'split\': \'train\', \'mean\': (104.00699, 116.66877, 122.67892)}"
   }
 }
 layer {
@@ -428,6 +428,15 @@ layer {
   bottom: "fc6"
   top: "fc6"
 }
+layer {
+  name: "drop6"
+  type: "Dropout"
+  bottom: "fc6"
+  top: "fc6"
+  dropout_param {
+    dropout_ratio: 0.5
+  }
+}
 layer {
   name: "fc7"
   type: "Convolution"
@@ -454,6 +463,15 @@ layer {
   bottom: "fc7"
   top: "fc7"
 }
+layer {
+  name: "drop7"
+  type: "Dropout"
+  bottom: "fc7"
+  top: "fc7"
+  dropout_param {
+    dropout_ratio: 0.5
+  }
+}
 layer {
   name: "score_fr"
   type: "Convolution"

voc-fcn8s/val.prototxt

@@ -6,7 +6,7 @@ layer {
   python_param {
     module: "voc_layers"
     layer: "VOCSegDataLayer"
-    param_str: "{\'voc_dir\': \'../../data/pascal/VOC2011\', \'seed\': 1337, \'split\': \'seg11valid\', \'mean\': (104.00699, 116.66877, 122.67892)}"
+    param_str: "{\'voc_dir\': \'../data/pascal/VOC2011\', \'seed\': 1337, \'split\': \'seg11valid\', \'mean\': (104.00699, 116.66877, 122.67892)}"
   }
 }
 layer {
@@ -428,6 +428,15 @@ layer {
   bottom: "fc6"
   top: "fc6"
 }
+layer {
+  name: "drop6"
+  type: "Dropout"
+  bottom: "fc6"
+  top: "fc6"
+  dropout_param {
+    dropout_ratio: 0.5
+  }
+}
 layer {
   name: "fc7"
   type: "Convolution"
@@ -454,6 +463,15 @@ layer {
   bottom: "fc7"
   top: "fc7"
 }
+layer {
+  name: "drop7"
+  type: "Dropout"
+  bottom: "fc7"
+  top: "fc7"
+  dropout_param {
+    dropout_ratio: 0.5
+  }
+}
 layer {
   name: "score_fr"
   type: "Convolution"