release v1 model defs + weights

- Caffe reference ImageNet model
- AlexNet

Note that one can upgrade the weights locally by
`upgrade_net_proto_binary.bin` to avoid re-downloading.

diff --git a/examples/imagenet/alexnet_deploy.prototxt b/examples/imagenet/alexnet_deploy.prototxt
index 4059fd5..d010753 100644 (file)
--- a/examples/imagenet/alexnet_deploy.prototxt
+++ b/examples/imagenet/alexnet_deploy.prototxt
@@ -5,32 +5,30 @@ input_dim: 3
 input_dim: 227
 input_dim: 227
 layers {
-  layer {
-    name: "conv1"
-    type: "conv"
+  name: "conv1"
+  type: CONVOLUTION
+  blobs_lr: 1
+  blobs_lr: 2
+  weight_decay: 1
+  weight_decay: 0
+  convolution_param {
     num_output: 96
-    kernelsize: 11
+    kernel_size: 11
     stride: 4
-    blobs_lr: 1.
-    blobs_lr: 2.
-    weight_decay: 1.
-    weight_decay: 0.
   }
   bottom: "data"
   top: "conv1"
 }
 layers {
-  layer {
-    name: "relu1"
-    type: "relu"
-  }
+  name: "relu1"
+  type: RELU
   bottom: "conv1"
   top: "conv1"
 }
 layers {
-  layer {
-    name: "norm1"
-    type: "lrn"
+  name: "norm1"
+  type: LRN
+  lrn_param {
     local_size: 5
     alpha: 0.0001
     beta: 0.75
@@ -39,44 +37,42 @@ layers {
   top: "norm1"
 }
 layers {
-  layer {
-    name: "pool1"
-    type: "pool"
+  name: "pool1"
+  type: POOLING
+  pooling_param {
     pool: MAX
-    kernelsize: 3
+    kernel_size: 3
     stride: 2
   }
   bottom: "norm1"
   top: "pool1"
 }
 layers {
-  layer {
-    name: "conv2"
-    type: "conv"
+  name: "conv2"
+  type: CONVOLUTION
+  blobs_lr: 1
+  blobs_lr: 2
+  weight_decay: 1
+  weight_decay: 0
+  convolution_param {
     num_output: 256
-    group: 2
-    kernelsize: 5
     pad: 2
-    blobs_lr: 1.
-    blobs_lr: 2.
-    weight_decay: 1.
-    weight_decay: 0.
+    kernel_size: 5
+    group: 2
   }
   bottom: "pool1"
   top: "conv2"
 }
 layers {
-  layer {
-    name: "relu2"
-    type: "relu"
-  }
+  name: "relu2"
+  type: RELU
   bottom: "conv2"
   top: "conv2"
 }
 layers {
-  layer {
-    name: "norm2"
-    type: "lrn"
+  name: "norm2"
+  type: LRN
+  lrn_param {
     local_size: 5
     alpha: 0.0001
     beta: 0.75
@@ -85,176 +81,164 @@ layers {
   top: "norm2"
 }
 layers {
-  layer {
-    name: "pool2"
-    type: "pool"
+  name: "pool2"
+  type: POOLING
+  pooling_param {
     pool: MAX
-    kernelsize: 3
+    kernel_size: 3
     stride: 2
   }
   bottom: "norm2"
   top: "pool2"
 }
 layers {
-  layer {
-    name: "conv3"
-    type: "conv"
+  name: "conv3"
+  type: CONVOLUTION
+  blobs_lr: 1
+  blobs_lr: 2
+  weight_decay: 1
+  weight_decay: 0
+  convolution_param {
     num_output: 384
-    kernelsize: 3
     pad: 1
-    blobs_lr: 1.
-    blobs_lr: 2.
-    weight_decay: 1.
-    weight_decay: 0.
+    kernel_size: 3
   }
   bottom: "pool2"
   top: "conv3"
 }
 layers {
-  layer {
-    name: "relu3"
-    type: "relu"
-  }
+  name: "relu3"
+  type: RELU
   bottom: "conv3"
   top: "conv3"
 }
 layers {
-  layer {
-    name: "conv4"
-    type: "conv"
+  name: "conv4"
+  type: CONVOLUTION
+  blobs_lr: 1
+  blobs_lr: 2
+  weight_decay: 1
+  weight_decay: 0
+  convolution_param {
     num_output: 384
-    group: 2
-    kernelsize: 3
     pad: 1
-    blobs_lr: 1.
-    blobs_lr: 2.
-    weight_decay: 1.
-    weight_decay: 0.
+    kernel_size: 3
+    group: 2
   }
   bottom: "conv3"
   top: "conv4"
 }
 layers {
-  layer {
-    name: "relu4"
-    type: "relu"
-  }
+  name: "relu4"
+  type: RELU
   bottom: "conv4"
   top: "conv4"
 }
 layers {
-  layer {
-    name: "conv5"
-    type: "conv"
+  name: "conv5"
+  type: CONVOLUTION
+  blobs_lr: 1
+  blobs_lr: 2
+  weight_decay: 1
+  weight_decay: 0
+  convolution_param {
     num_output: 256
-    group: 2
-    kernelsize: 3
     pad: 1
-    blobs_lr: 1.
-    blobs_lr: 2.
-    weight_decay: 1.
-    weight_decay: 0.
+    kernel_size: 3
+    group: 2
   }
   bottom: "conv4"
   top: "conv5"
 }
 layers {
-  layer {
-    name: "relu5"
-    type: "relu"
-  }
+  name: "relu5"
+  type: RELU
   bottom: "conv5"
   top: "conv5"
 }
 layers {
-  layer {
-    name: "pool5"
-    type: "pool"
-    kernelsize: 3
+  name: "pool5"
+  type: POOLING
+  pooling_param {
     pool: MAX
+    kernel_size: 3
     stride: 2
   }
   bottom: "conv5"
   top: "pool5"
 }
 layers {
-  layer {
-    name: "fc6"
-    type: "innerproduct"
+  name: "fc6"
+  type: INNER_PRODUCT
+  blobs_lr: 1
+  blobs_lr: 2
+  weight_decay: 1
+  weight_decay: 0
+  inner_product_param {
     num_output: 4096
-    blobs_lr: 1.
-    blobs_lr: 2.
-    weight_decay: 1.
-    weight_decay: 0.
   }
   bottom: "pool5"
   top: "fc6"
 }
 layers {
-  layer {
-    name: "relu6"
-    type: "relu"
-  }
+  name: "relu6"
+  type: RELU
   bottom: "fc6"
   top: "fc6"
 }
 layers {
-  layer {
-    name: "drop6"
-    type: "dropout"
+  name: "drop6"
+  type: DROPOUT
+  dropout_param {
     dropout_ratio: 0.5
   }
   bottom: "fc6"
   top: "fc6"
 }
 layers {
-  layer {
-    name: "fc7"
-    type: "innerproduct"
+  name: "fc7"
+  type: INNER_PRODUCT
+  blobs_lr: 1
+  blobs_lr: 2
+  weight_decay: 1
+  weight_decay: 0
+  inner_product_param {
     num_output: 4096
-    blobs_lr: 1.
-    blobs_lr: 2.
-    weight_decay: 1.
-    weight_decay: 0.
   }
   bottom: "fc6"
   top: "fc7"
 }
 layers {
-  layer {
-    name: "relu7"
-    type: "relu"
-  }
+  name: "relu7"
+  type: RELU
   bottom: "fc7"
   top: "fc7"
 }
 layers {
-  layer {
-    name: "drop7"
-    type: "dropout"
+  name: "drop7"
+  type: DROPOUT
+  dropout_param {
     dropout_ratio: 0.5
   }
   bottom: "fc7"
   top: "fc7"
 }
 layers {
-  layer {
-    name: "fc8"
-    type: "innerproduct"
+  name: "fc8"
+  type: INNER_PRODUCT
+  blobs_lr: 1
+  blobs_lr: 2
+  weight_decay: 1
+  weight_decay: 0
+  inner_product_param {
     num_output: 1000
-    blobs_lr: 1.
-    blobs_lr: 2.
-    weight_decay: 1.
-    weight_decay: 0.
   }
   bottom: "fc7"
   top: "fc8"
 }
 layers {
-  layer {
-    name: "prob"
-    type: "softmax"
-  }
+  name: "prob"
+  type: SOFTMAX
   bottom: "fc8"
   top: "prob"
 }

diff --git a/examples/imagenet/alexnet_train.prototxt b/examples/imagenet/alexnet_train.prototxt
index c5394dc..32a96cf 100644 (file)
--- a/examples/imagenet/alexnet_train.prototxt
+++ b/examples/imagenet/alexnet_train.prototxt
@@ -1,23 +1,27 @@
 name: "AlexNet"
 layers {
-  layer {
-    name: "data"
-    type: "data"
+  name: "data"
+  type: DATA
+  data_param {
     source: "ilsvrc12_train_leveldb"
-    meanfile: "../../data/ilsvrc12/imagenet_mean.binaryproto"
-    batchsize: 256
-    cropsize: 227
+    mean_file: "../../data/ilsvrc12/imagenet_mean.binaryproto"
+    batch_size: 256
+    crop_size: 227
     mirror: true
   }
   top: "data"
   top: "label"
 }
 layers {
-  layer {
-    name: "conv1"
-    type: "conv"
+  name: "conv1"
+  type: CONVOLUTION
+  blobs_lr: 1
+  blobs_lr: 2
+  weight_decay: 1
+  weight_decay: 0
+  convolution_param {
     num_output: 96
-    kernelsize: 11
+    kernel_size: 11
     stride: 4
     weight_filler {
       type: "gaussian"
@@ -25,28 +29,22 @@ layers {
     }
     bias_filler {
       type: "constant"
-      value: 0.
+      value: 0
     }
-    blobs_lr: 1.
-    blobs_lr: 2.
-    weight_decay: 1.
-    weight_decay: 0.
   }
   bottom: "data"
   top: "conv1"
 }
 layers {
-  layer {
-    name: "relu1"
-    type: "relu"
-  }
+  name: "relu1"
+  type: RELU
   bottom: "conv1"
   top: "conv1"
 }
 layers {
-  layer {
-    name: "norm1"
-    type: "lrn"
+  name: "norm1"
+  type: LRN
+  lrn_param {
     local_size: 5
     alpha: 0.0001
     beta: 0.75
@@ -55,24 +53,28 @@ layers {
   top: "norm1"
 }
 layers {
-  layer {
-    name: "pool1"
-    type: "pool"
+  name: "pool1"
+  type: POOLING
+  pooling_param {
     pool: MAX
-    kernelsize: 3
+    kernel_size: 3
     stride: 2
   }
   bottom: "norm1"
   top: "pool1"
 }
 layers {
-  layer {
-    name: "conv2"
-    type: "conv"
+  name: "conv2"
+  type: CONVOLUTION
+  blobs_lr: 1
+  blobs_lr: 2
+  weight_decay: 1
+  weight_decay: 0
+  convolution_param {
     num_output: 256
-    group: 2
-    kernelsize: 5
     pad: 2
+    kernel_size: 5
+    group: 2
     weight_filler {
       type: "gaussian"
       std: 0.01
@@ -81,26 +83,20 @@ layers {
       type: "constant"
       value: 0.1
     }
-    blobs_lr: 1.
-    blobs_lr: 2.
-    weight_decay: 1.
-    weight_decay: 0.
   }
   bottom: "pool1"
   top: "conv2"
 }
 layers {
-  layer {
-    name: "relu2"
-    type: "relu"
-  }
+  name: "relu2"
+  type: RELU
   bottom: "conv2"
   top: "conv2"
 }
 layers {
-  layer {
-    name: "norm2"
-    type: "lrn"
+  name: "norm2"
+  type: LRN
+  lrn_param {
     local_size: 5
     alpha: 0.0001
     beta: 0.75
@@ -109,55 +105,57 @@ layers {
   top: "norm2"
 }
 layers {
-  layer {
-    name: "pool2"
-    type: "pool"
+  name: "pool2"
+  type: POOLING
+  pooling_param {
     pool: MAX
-    kernelsize: 3
+    kernel_size: 3
     stride: 2
   }
   bottom: "norm2"
   top: "pool2"
 }
 layers {
-  layer {
-    name: "conv3"
-    type: "conv"
+  name: "conv3"
+  type: CONVOLUTION
+  blobs_lr: 1
+  blobs_lr: 2
+  weight_decay: 1
+  weight_decay: 0
+  convolution_param {
     num_output: 384
-    kernelsize: 3
     pad: 1
+    kernel_size: 3
     weight_filler {
       type: "gaussian"
       std: 0.01
     }
     bias_filler {
       type: "constant"
-      value: 0.
+      value: 0
     }
-    blobs_lr: 1.
-    blobs_lr: 2.
-    weight_decay: 1.
-    weight_decay: 0.
   }
   bottom: "pool2"
   top: "conv3"
 }
 layers {
-  layer {
-    name: "relu3"
-    type: "relu"
-  }
+  name: "relu3"
+  type: RELU
   bottom: "conv3"
   top: "conv3"
 }
 layers {
-  layer {
-    name: "conv4"
-    type: "conv"
+  name: "conv4"
+  type: CONVOLUTION
+  blobs_lr: 1
+  blobs_lr: 2
+  weight_decay: 1
+  weight_decay: 0
+  convolution_param {
     num_output: 384
-    group: 2
-    kernelsize: 3
     pad: 1
+    kernel_size: 3
+    group: 2
     weight_filler {
       type: "gaussian"
       std: 0.01
@@ -166,30 +164,28 @@ layers {
       type: "constant"
       value: 0.1
     }
-    blobs_lr: 1.
-    blobs_lr: 2.
-    weight_decay: 1.
-    weight_decay: 0.
   }
   bottom: "conv3"
   top: "conv4"
 }
 layers {
-  layer {
-    name: "relu4"
-    type: "relu"
-  }
+  name: "relu4"
+  type: RELU
   bottom: "conv4"
   top: "conv4"
 }
 layers {
-  layer {
-    name: "conv5"
-    type: "conv"
+  name: "conv5"
+  type: CONVOLUTION
+  blobs_lr: 1
+  blobs_lr: 2
+  weight_decay: 1
+  weight_decay: 0
+  convolution_param {
     num_output: 256
-    group: 2
-    kernelsize: 3
     pad: 1
+    kernel_size: 3
+    group: 2
     weight_filler {
       type: "gaussian"
       std: 0.01
@@ -198,37 +194,35 @@ layers {
       type: "constant"
       value: 0.1
     }
-    blobs_lr: 1.
-    blobs_lr: 2.
-    weight_decay: 1.
-    weight_decay: 0.
   }
   bottom: "conv4"
   top: "conv5"
 }
 layers {
-  layer {
-    name: "relu5"
-    type: "relu"
-  }
+  name: "relu5"
+  type: RELU
   bottom: "conv5"
   top: "conv5"
 }
 layers {
-  layer {
-    name: "pool5"
-    type: "pool"
-    kernelsize: 3
+  name: "pool5"
+  type: POOLING
+  pooling_param {
     pool: MAX
+    kernel_size: 3
     stride: 2
   }
   bottom: "conv5"
   top: "pool5"
 }
 layers {
-  layer {
-    name: "fc6"
-    type: "innerproduct"
+  name: "fc6"
+  type: INNER_PRODUCT
+  blobs_lr: 1
+  blobs_lr: 2
+  weight_decay: 1
+  weight_decay: 0
+  inner_product_param {
     num_output: 4096
     weight_filler {
       type: "gaussian"
@@ -238,35 +232,33 @@ layers {
       type: "constant"
       value: 0.1
     }
-    blobs_lr: 1.
-    blobs_lr: 2.
-    weight_decay: 1.
-    weight_decay: 0.
   }
   bottom: "pool5"
   top: "fc6"
 }
 layers {
-  layer {
-    name: "relu6"
-    type: "relu"
-  }
+  name: "relu6"
+  type: RELU
   bottom: "fc6"
   top: "fc6"
 }
 layers {
-  layer {
-    name: "drop6"
-    type: "dropout"
+  name: "drop6"
+  type: DROPOUT
+  dropout_param {
     dropout_ratio: 0.5
   }
   bottom: "fc6"
   top: "fc6"
 }
 layers {
-  layer {
-    name: "fc7"
-    type: "innerproduct"
+  name: "fc7"
+  type: INNER_PRODUCT
+  blobs_lr: 1
+  blobs_lr: 2
+  weight_decay: 1
+  weight_decay: 0
+  inner_product_param {
     num_output: 4096
     weight_filler {
       type: "gaussian"
@@ -276,35 +268,33 @@ layers {
       type: "constant"
       value: 0.1
     }
-    blobs_lr: 1.
-    blobs_lr: 2.
-    weight_decay: 1.
-    weight_decay: 0.
   }
   bottom: "fc6"
   top: "fc7"
 }
 layers {
-  layer {
-    name: "relu7"
-    type: "relu"
-  }
+  name: "relu7"
+  type: RELU
   bottom: "fc7"
   top: "fc7"
 }
 layers {
-  layer {
-    name: "drop7"
-    type: "dropout"
+  name: "drop7"
+  type: DROPOUT
+  dropout_param {
     dropout_ratio: 0.5
   }
   bottom: "fc7"
   top: "fc7"
 }
 layers {
-  layer {
-    name: "fc8"
-    type: "innerproduct"
+  name: "fc8"
+  type: INNER_PRODUCT
+  blobs_lr: 1
+  blobs_lr: 2
+  weight_decay: 1
+  weight_decay: 0
+  inner_product_param {
     num_output: 1000
     weight_filler {
       type: "gaussian"
@@ -312,21 +302,15 @@ layers {
     }
     bias_filler {
       type: "constant"
-      value: 0.
+      value: 0
     }
-    blobs_lr: 1.
-    blobs_lr: 2.
-    weight_decay: 1.
-    weight_decay: 0.
   }
   bottom: "fc7"
   top: "fc8"
 }
 layers {
-  layer {
-    name: "loss"
-    type: "softmax_loss"
-  }
+  name: "loss"
+  type: SOFTMAX_LOSS
   bottom: "fc8"
   bottom: "label"
 }

diff --git a/examples/imagenet/alexnet_val.prototxt b/examples/imagenet/alexnet_val.prototxt
index aff33d0..3fd6296 100644 (file)
--- a/examples/imagenet/alexnet_val.prototxt
+++ b/examples/imagenet/alexnet_val.prototxt
@@ -1,40 +1,38 @@
 name: "AlexNet"
 layers {
-  layer {
-    name: "data"
-    type: "data"
+  name: "data"
+  type: DATA
+  data_param {
     source: "ilsvrc12_val_leveldb"
-    meanfile: "../../data/ilsvrc12/imagenet_mean.binaryproto"
-    batchsize: 50
-    cropsize: 227
+    mean_file: "../../data/ilsvrc12/imagenet_mean.binaryproto"
+    batch_size: 50
+    crop_size: 227
     mirror: false
   }
   top: "data"
   top: "label"
 }
 layers {
-  layer {
-    name: "conv1"
-    type: "conv"
+  name: "conv1"
+  type: CONVOLUTION
+  convolution_param {
     num_output: 96
-    kernelsize: 11
+    kernel_size: 11
     stride: 4
   }
   bottom: "data"
   top: "conv1"
 }
 layers {
-  layer {
-    name: "relu1"
-    type: "relu"
-  }
+  name: "relu1"
+  type: RELU
   bottom: "conv1"
   top: "conv1"
 }
 layers {
-  layer {
-    name: "norm1"
-    type: "lrn"
+  name: "norm1"
+  type: LRN
+  lrn_param {
     local_size: 5
     alpha: 0.0001
     beta: 0.75
@@ -43,40 +41,38 @@ layers {
   top: "norm1"
 }
 layers {
-  layer {
-    name: "pool1"
-    type: "pool"
+  name: "pool1"
+  type: POOLING
+  pooling_param {
     pool: MAX
-    kernelsize: 3
+    kernel_size: 3
     stride: 2
   }
   bottom: "norm1"
   top: "pool1"
 }
 layers {
-  layer {
-    name: "conv2"
-    type: "conv"
+  name: "conv2"
+  type: CONVOLUTION
+  convolution_param {
     num_output: 256
-    group: 2
-    kernelsize: 5
     pad: 2
+    kernel_size: 5
+    group: 2
   }
   bottom: "pool1"
   top: "conv2"
 }
 layers {
-  layer {
-    name: "relu2"
-    type: "relu"
-  }
+  name: "relu2"
+  type: RELU
   bottom: "conv2"
   top: "conv2"
 }
 layers {
-  layer {
-    name: "norm2"
-    type: "lrn"
+  name: "norm2"
+  type: LRN
+  lrn_param {
     local_size: 5
     alpha: 0.0001
     beta: 0.75
@@ -85,161 +81,147 @@ layers {
   top: "norm2"
 }
 layers {
-  layer {
-    name: "pool2"
-    type: "pool"
+  name: "pool2"
+  type: POOLING
+  pooling_param {
     pool: MAX
-    kernelsize: 3
+    kernel_size: 3
     stride: 2
   }
   bottom: "norm2"
   top: "pool2"
 }
 layers {
-  layer {
-    name: "conv3"
-    type: "conv"
+  name: "conv3"
+  type: CONVOLUTION
+  convolution_param {
     num_output: 384
-    kernelsize: 3
     pad: 1
+    kernel_size: 3
   }
   bottom: "pool2"
   top: "conv3"
 }
 layers {
-  layer {
-    name: "relu3"
-    type: "relu"
-  }
+  name: "relu3"
+  type: RELU
   bottom: "conv3"
   top: "conv3"
 }
 layers {
-  layer {
-    name: "conv4"
-    type: "conv"
+  name: "conv4"
+  type: CONVOLUTION
+  convolution_param {
     num_output: 384
-    group: 2
-    kernelsize: 3
     pad: 1
+    kernel_size: 3
+    group: 2
   }
   bottom: "conv3"
   top: "conv4"
 }
 layers {
-  layer {
-    name: "relu4"
-    type: "relu"
-  }
+  name: "relu4"
+  type: RELU
   bottom: "conv4"
   top: "conv4"
 }
 layers {
-  layer {
-    name: "conv5"
-    type: "conv"
+  name: "conv5"
+  type: CONVOLUTION
+  convolution_param {
     num_output: 256
-    group: 2
-    kernelsize: 3
     pad: 1
+    kernel_size: 3
+    group: 2
   }
   bottom: "conv4"
   top: "conv5"
 }
 layers {
-  layer {
-    name: "relu5"
-    type: "relu"
-  }
+  name: "relu5"
+  type: RELU
   bottom: "conv5"
   top: "conv5"
 }
 layers {
-  layer {
-    name: "pool5"
-    type: "pool"
-    kernelsize: 3
+  name: "pool5"
+  type: POOLING
+  pooling_param {
     pool: MAX
+    kernel_size: 3
     stride: 2
   }
   bottom: "conv5"
   top: "pool5"
 }
 layers {
-  layer {
-    name: "fc6"
-    type: "innerproduct"
+  name: "fc6"
+  type: INNER_PRODUCT
+  inner_product_param {
     num_output: 4096
   }
   bottom: "pool5"
   top: "fc6"
 }
 layers {
-  layer {
-    name: "relu6"
-    type: "relu"
-  }
+  name: "relu6"
+  type: RELU
   bottom: "fc6"
   top: "fc6"
 }
 layers {
-  layer {
-    name: "drop6"
-    type: "dropout"
+  name: "drop6"
+  type: DROPOUT
+  dropout_param {
     dropout_ratio: 0.5
   }
   bottom: "fc6"
   top: "fc6"
 }
 layers {
-  layer {
-    name: "fc7"
-    type: "innerproduct"
+  name: "fc7"
+  type: INNER_PRODUCT
+  inner_product_param {
     num_output: 4096
   }
   bottom: "fc6"
   top: "fc7"
 }
 layers {
-  layer {
-    name: "relu7"
-    type: "relu"
-  }
+  name: "relu7"
+  type: RELU
   bottom: "fc7"
   top: "fc7"
 }
 layers {
-  layer {
-    name: "drop7"
-    type: "dropout"
+  name: "drop7"
+  type: DROPOUT
+  dropout_param {
     dropout_ratio: 0.5
   }
   bottom: "fc7"
   top: "fc7"
 }
 layers {
-  layer {
-    name: "fc8"
-    type: "innerproduct"
+  name: "fc8"
+  type: INNER_PRODUCT
+  inner_product_param {
     num_output: 1000
   }
   bottom: "fc7"
   top: "fc8"
 }
 layers {
-  layer {
-    name: "prob"
-    type: "softmax"
-  }
+  name: "prob"
+  type: SOFTMAX
   bottom: "fc8"
   top: "prob"
 }
 layers {
-  layer {
-    name: "accuracy"
-    type: "accuracy"
-  }
+  top: "accuracy"
+  name: "accuracy"
+  type: ACCURACY
   bottom: "prob"
   bottom: "label"
-  top: "accuracy"
 }

diff --git a/examples/imagenet/get_caffe_alexnet_model.sh b/examples/imagenet/get_caffe_alexnet_model.sh
index 167c937..399e2a0 100755 (executable)
--- a/examples/imagenet/get_caffe_alexnet_model.sh
+++ b/examples/imagenet/get_caffe_alexnet_model.sh
@@ -3,7 +3,7 @@
 # for ilsvrc image classification and deep feature extraction
 
 MODEL=caffe_alexnet_model
-CHECKSUM=91df0e19290ef78324de9eecb258a77f
+CHECKSUM=29eb495b11613825c1900382f5286963
 
 if [ -f $MODEL ]; then
   echo "Model already exists. Checking md5..."

diff --git a/examples/imagenet/get_caffe_reference_imagenet_model.sh b/examples/imagenet/get_caffe_reference_imagenet_model.sh
index 7a85613..2381dbd 100755 (executable)
--- a/examples/imagenet/get_caffe_reference_imagenet_model.sh
+++ b/examples/imagenet/get_caffe_reference_imagenet_model.sh
@@ -3,7 +3,7 @@
 # for ilsvrc image classification and deep feature extraction
 
 MODEL=caffe_reference_imagenet_model
-CHECKSUM=bf44bac4a59aa7792b296962fe483f2b
+CHECKSUM=af678f0bd3cdd2437e35679d88665170
 
 if [ -f $MODEL ]; then
   echo "Model already exists. Checking md5..."
@@ -23,6 +23,6 @@ fi
 
 echo "Downloading..."
 
-wget --no-check-certificate https://www.dropbox.com/s/n3jups0gr7uj0dv/$MODEL
+wget --no-check-certificate https://www.dropbox.com/s/7qkokvr7x0esljl/$MODEL
 
 echo "Done. Please run this command again to verify that checksum = $CHECKSUM."