Update old version of caffemodels in different models. Updates notes

caffe_models/SqueezeNet_v1.0/caffe_model/train_val.prototxt

@@ -20,7 +20,7 @@ layer {
     mean_value: 123
   }
   data_param {
-    source: "examples/imagenet/ilsvrc12_train_lmdb"
+    source: "bvlc_caffe/examples/imagenet/ilsvrc12_train_lmdb"
     batch_size: 32 #*iter_size
     backend: LMDB
   }
@@ -40,7 +40,7 @@ layer {
     mean_value: 123
   }
   data_param {
-    source: "examples/imagenet/ilsvrc12_val_lmdb"
+    source: "bvlc_caffe/examples/imagenet/ilsvrc12_val_lmdb"
     batch_size: 25 #not *iter_size
     backend: LMDB
   }

caffe_models/SqueezeNet_v1.1/caffe_model/train_val.prototxt

@@ -20,8 +20,8 @@ layer {
     mean_value: 123
   }
   data_param {
-    source: "examples/imagenet/ilsvrc12_train_lmdb"
-    batch_size: 32
+    source: "bvlc_caffe/examples/imagenet/ilsvrc12_train_lmdb"
+    batch_size: 128
     backend: LMDB
   }
 }
@@ -40,7 +40,7 @@ layer {
     mean_value: 123
   }
   data_param {
-    source: "examples/imagenet/ilsvrc12_val_lmdb"
+    source: "bvlc_caffe/examples/imagenet/ilsvrc12_val_lmdb"
     batch_size: 25 #not *iter_size
     backend: LMDB
   }

caffe_models/denoiser/caffe_model/notes.txt

@@ -1,2 +1,7 @@
 net-240x360-64-64-test.prototxt/net-200x200-64-64-test.prototxt decomposed model
 net-HxW-64-64_iter_970.caffemodel retrained decomposed model
+
+Use
+--image_scale 1
+to run denoiser.  The graph is trained assuming the input pixels
+are in the range [0..1].

caffe_models/googlenet/caffe_model/deploy.prototxt

@@ -1,17 +1,10 @@
 name: "GoogleNet"
-#layer {
-#  name: "data"
-#  type: "Input"
-#  top: "data"
-#  input_param { shape: { dim: 10 dim: 3 dim: 224 dim: 224 } }
-#}
-input : "data" 
-    input_shape {
-     dim: 10 
-     dim: 3 
-     dim: 224 
-     dim: 224 
-    }
+layer {
+  name: "data"
+  type: "Input"
+  top: "data"
+  input_param { shape: { dim: 10 dim: 3 dim: 224 dim: 224 } }
+}
 layer {
   name: "conv1/7x7_s2"
   type: "Convolution"
@@ -2113,10 +2106,10 @@ layer {
   top: "inception_5b/output"
 }
 layer {
-  name: "pool5_7x7_s1"
+  name: "pool5/7x7_s1"
   type: "Pooling"
   bottom: "inception_5b/output"
-  top: "pool5_7x7_s1"
+  top: "pool5/7x7_s1"
   pooling_param {
     pool: AVE
     kernel_size: 7
@@ -2126,16 +2119,16 @@ layer {
 layer {
   name: "pool5/drop_7x7_s1"
   type: "Dropout"
-  bottom: "pool5_7x7_s1"
-  top: "pool5_7x7_s1"
+  bottom: "pool5/7x7_s1"
+  top: "pool5/7x7_s1"
   dropout_param {
     dropout_ratio: 0.4
   }
 }
 layer {
   name: "loss3/classifier"
   type: "InnerProduct"
-  bottom: "pool5_7x7_s1"
+  bottom: "pool5/7x7_s1"
   top: "loss3/classifier"
   param {
     lr_mult: 1

caffe_models/inception_v1/caffe_model/notes.txt

@@ -19,3 +19,12 @@ Following options are required for the preprocessing for host fixed:
 Inception_v1-no_asym_padding.prototxt patched prototxt that does not require asymmetric padding
 - can be used for benchmarking or power measurements
 - functionally not correct because of wrong padding of the first layer (pad_left=3,pad_right=3 instead of pad_left=2,pad_right=3)
+
+Compressed graphs:
+1. compressed-51p.prototxt / compressed-51p.caffemodel
+- 51% of original MACs (factor 1.98)
+- Latest one saved in compressed/1.98
+
+2. compressed-45p.prototxt / compressed-45p.caffemodel
+- 45% of original MACs (factor 2.2)
+- Latest one saved in compressed/2.2