Commit 98841163 authored by Ross Girshick's avatar Ross Girshick
Browse files

upgrade prototxt to caffe proto v1

parent b6cb7757
name: "CaffeNet"
layers {
layer {
name: "data"
type: "window_data"
top: "data"
top: "label"
name: "data"
type: WINDOW_DATA
window_data_param {
source: "window_file_voc_2007_trainval.txt"
meanfile: "../../data/ilsvrc12/imagenet_mean.binaryproto"
batchsize: 128
cropsize: 227
mean_file: "../../data/ilsvrc12/imagenet_mean.binaryproto"
batch_size: 128
crop_size: 227
mirror: true
det_context_pad: 16
det_crop_mode: "warp"
det_fg_threshold: 0.5
det_bg_threshold: 0.5
det_fg_fraction: 0.25
fg_threshold: 0.5
bg_threshold: 0.5
fg_fraction: 0.25
context_pad: 16
crop_mode: "warp"
}
top: "data"
top: "label"
}
layers {
layer {
name: "conv1"
type: "conv"
bottom: "data"
top: "conv1"
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"
......@@ -30,242 +36,200 @@ 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"
}
bottom: "conv1"
top: "conv1"
name: "relu1"
type: RELU
}
layers {
layer {
name: "pool1"
type: "pool"
bottom: "conv1"
top: "pool1"
name: "pool1"
type: POOLING
pooling_param {
pool: MAX
kernelsize: 3
kernel_size: 3
stride: 2
}
bottom: "conv1"
top: "pool1"
}
layers {
layer {
name: "norm1"
type: "lrn"
bottom: "pool1"
top: "norm1"
name: "norm1"
type: LRN
lrn_param {
local_size: 5
alpha: 0.0001
beta: 0.75
}
bottom: "pool1"
top: "norm1"
}
layers {
layer {
name: "pad2"
type: "padding"
pad: 2
}
bottom: "norm1"
top: "pad2"
}
layers {
layer {
name: "conv2"
type: "conv"
top: "conv2"
name: "conv2"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 256
pad: 2
kernel_size: 5
group: 2
kernelsize: 5
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 1.
value: 1
}
blobs_lr: 1.
blobs_lr: 2.
weight_decay: 1.
weight_decay: 0.
}
bottom: "pad2"
top: "conv2"
}
layers {
layer {
name: "relu2"
type: "relu"
}
bottom: "conv2"
top: "conv2"
name: "relu2"
type: RELU
}
layers {
layer {
name: "pool2"
type: "pool"
bottom: "conv2"
top: "pool2"
name: "pool2"
type: POOLING
pooling_param {
pool: MAX
kernelsize: 3
kernel_size: 3
stride: 2
}
bottom: "conv2"
top: "pool2"
}
layers {
layer {
name: "norm2"
type: "lrn"
bottom: "pool2"
top: "norm2"
name: "norm2"
type: LRN
lrn_param {
local_size: 5
alpha: 0.0001
beta: 0.75
}
bottom: "pool2"
top: "norm2"
}
layers {
layer {
name: "pad3"
type: "padding"
pad: 1
}
bottom: "norm2"
top: "pad3"
}
layers {
layer {
name: "conv3"
type: "conv"
top: "conv3"
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: "pad3"
top: "conv3"
}
layers {
layer {
name: "relu3"
type: "relu"
}
bottom: "conv3"
top: "conv3"
name: "relu3"
type: RELU
}
layers {
layer {
name: "pad4"
type: "padding"
pad: 1
}
bottom: "conv3"
top: "pad4"
}
layers {
layer {
name: "conv4"
type: "conv"
top: "conv4"
name: "conv4"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 384
pad: 1
kernel_size: 3
group: 2
kernelsize: 3
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 1.
value: 1
}
blobs_lr: 1.
blobs_lr: 2.
weight_decay: 1.
weight_decay: 0.
}
bottom: "pad4"
top: "conv4"
}
layers {
layer {
name: "relu4"
type: "relu"
}
bottom: "conv4"
top: "conv4"
name: "relu4"
type: RELU
}
layers {
layer {
name: "pad5"
type: "padding"
pad: 1
}
bottom: "conv4"
top: "pad5"
}
layers {
layer {
name: "conv5"
type: "conv"
top: "conv5"
name: "conv5"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
group: 2
kernelsize: 3
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 1.
value: 1
}
blobs_lr: 1.
blobs_lr: 2.
weight_decay: 1.
weight_decay: 0.
}
bottom: "pad5"
top: "conv5"
}
layers {
layer {
name: "relu5"
type: "relu"
}
bottom: "conv5"
top: "conv5"
name: "relu5"
type: RELU
}
layers {
layer {
name: "pool5"
type: "pool"
kernelsize: 3
bottom: "conv5"
top: "pool5"
name: "pool5"
type: POOLING
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
bottom: "conv5"
top: "pool5"
}
layers {
layer {
name: "fc6"
type: "innerproduct"
bottom: "pool5"
top: "fc6"
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"
......@@ -273,37 +237,35 @@ layers {
}
bias_filler {
type: "constant"
value: 1.
value: 1
}
blobs_lr: 1.
blobs_lr: 2.
weight_decay: 1.
weight_decay: 0.
}
bottom: "pool5"
top: "fc6"
}
layers {
layer {
name: "relu6"
type: "relu"
}
bottom: "fc6"
top: "fc6"
name: "relu6"
type: RELU
}
layers {
layer {
name: "drop6"
type: "dropout"
dropout_ratio: 0.5
}
bottom: "fc6"
top: "fc6"
name: "drop6"
type: DROPOUT
dropout_param {
dropout_ratio: 0.5
}
}
layers {
layer {
name: "fc7"
type: "innerproduct"
bottom: "fc6"
top: "fc7"
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"
......@@ -311,39 +273,35 @@ layers {
}
bias_filler {
type: "constant"
value: 1.
value: 1
}
blobs_lr: 1.
blobs_lr: 2.
weight_decay: 1.
weight_decay: 0.
}
bottom: "fc6"
top: "fc7"
}
layers {
layer {
name: "relu7"
type: "relu"
}
bottom: "fc7"
top: "fc7"
name: "relu7"
type: RELU
}
layers {
layer {
name: "drop7"
type: "dropout"
dropout_ratio: 0.5
}
bottom: "fc7"
top: "fc7"
name: "drop7"
type: DROPOUT
dropout_param {
dropout_ratio: 0.5
}
}
layers {
layer {
# We name this fc8_pascal so that the initialization
# network doesn't populate this layer with its fc8
name: "fc8_pascal"
type: "innerproduct"
bottom: "fc7"
top: "fc8_pascal"
name: "fc8_pascal"
type: INNER_PRODUCT
blobs_lr: 10
blobs_lr: 20
weight_decay: 1
weight_decay: 0
inner_product_param {
num_output: 21
weight_filler {
type: "gaussian"
......@@ -353,19 +311,11 @@ layers {
type: "constant"
value: 0
}
blobs_lr: 10.
blobs_lr: 20.
weight_decay: 1.
weight_decay: 0.
}
bottom: "fc7"
top: "fc8_pascal"
}
layers {
layer {
name: "loss"
type: "softmax_loss"
}
bottom: "fc8_pascal"
bottom: "label"
name: "loss"
type: SOFTMAX_LOSS
}
name: "CaffeNet"
layers {
layer {
name: "data"
type: "window_data"
top: "data"
top: "label"
name: "data"
type: WINDOW_DATA
window_data_param {
source: "window_file_voc_2007_test.txt"
meanfile: "../../data/ilsvrc12/imagenet_mean.binaryproto"
batchsize: 128
cropsize: 227
mean_file: "../../data/ilsvrc12/imagenet_mean.binaryproto"
batch_size: 128
crop_size: 227
mirror: true
det_context_pad: 16
det_crop_mode: "warp"
det_fg_threshold: 0.5
det_bg_threshold: 0.5
det_fg_fraction: 0.25
fg_threshold: 0.5
bg_threshold: 0.5
fg_fraction: 0.25
context_pad: 16
crop_mode: "warp"
}
top: "data"
top: "label"
}
layers {
layer {
name: "conv1"
type: "conv"
bottom: "data"
top: "conv1"
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"
......@@ -30,242 +36,200 @@ 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"
}
bottom: "conv1"
top: "conv1"
name: "relu1"
type: RELU
}
layers {
layer {
name: "pool1"
type: "pool"
bottom: "conv1"
top: "pool1"
name: "pool1"
type: POOLING
pooling_param {
pool: MAX
kernelsize: 3
kernel_size: 3
stride: 2
}
bottom: "conv1"
top: "pool1"
}
layers {
layer {
name: "norm1"
type: "lrn"
bottom: "pool1"
top: "norm1"
name: "norm1"
type: LRN
lrn_param {
local_size: 5
alpha: 0.0001
beta: 0.75
}
bottom: "pool1"
top: "norm1"
}
layers {
layer {
name: "pad2"
type: "padding"
pad: 2
}
bottom: "norm1"
top: "pad2"
}
layers {