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define pascal finetuning models

This commit is contained in:
Ross Girshick 2014-03-13 16:35:27 -07:00 коммит произвёл Evan Shelhamer
Родитель fc79306482
Коммит f4a2c14b13
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368
models/pascal_finetune.prototxt Normal file
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name: "CaffeNet"
layers {
layer {
name: "data"
type: "window_data"
source: "/work5/rbg/convnet-selective-search/selective-search-data/window_file_2007_train.txt"
meanfile: "/home/rbg/working/caffe-rbg/data/ilsvrc2012_mean.binaryproto"
batchsize: 128
cropsize: 227
mirror: true
det_fg_threshold: 0.6
det_bg_threshold: 0.3
det_fg_fraction: 0.25
}
top: "data"
top: "label"
}
layers {
layer {
name: "conv1"
type: "conv"
num_output: 96
kernelsize: 11
stride: 4
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
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"
}
layers {
layer {
name: "pool1"
type: "pool"
pool: MAX
kernelsize: 3
stride: 2
}
bottom: "conv1"
top: "pool1"
}
layers {
layer {
name: "norm1"
type: "lrn"
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"
num_output: 256
group: 2
kernelsize: 5
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
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"
}
layers {
layer {
name: "pool2"
type: "pool"
pool: MAX
kernelsize: 3
stride: 2
}
bottom: "conv2"
top: "pool2"
}
layers {
layer {
name: "norm2"
type: "lrn"
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"
num_output: 384
kernelsize: 3
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
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"
}
layers {
layer {
name: "pad4"
type: "padding"
pad: 1
}
bottom: "conv3"
top: "pad4"
}
layers {
layer {
name: "conv4"
type: "conv"
num_output: 384
group: 2
kernelsize: 3
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
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"
}
layers {
layer {
name: "pad5"
type: "padding"
pad: 1
}
bottom: "conv4"
top: "pad5"
}
layers {
layer {
name: "conv5"
type: "conv"
num_output: 256
group: 2
kernelsize: 3
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
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"
}
layers {
layer {
name: "pool5"
type: "pool"
kernelsize: 3
pool: MAX
stride: 2
}
bottom: "conv5"
top: "pool5"
}
layers {
layer {
name: "fc6"
type: "innerproduct"
num_output: 4096
weight_filler {
type: "gaussian"
std: 0.005
}
bias_filler {
type: "constant"
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"
}
layers {
layer {
name: "drop6"
type: "dropout"
dropout_ratio: 0.5
}
bottom: "fc6"
top: "fc6"
}
layers {
layer {
name: "fc7"
type: "innerproduct"
num_output: 4096
weight_filler {
type: "gaussian"
std: 0.005
}
bias_filler {
type: "constant"
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"
}
layers {
layer {
name: "drop7"
type: "dropout"
dropout_ratio: 0.5
}
bottom: "fc7"
top: "fc7"
}
layers {
layer {
name: "fc8"
type: "innerproduct"
num_output: 21
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
blobs_lr: 1.
blobs_lr: 2.
weight_decay: 1.
weight_decay: 0.
can_clobber: false
}
bottom: "fc7"
top: "fc8"
}
layers {
layer {
name: "loss"
type: "softmax_loss"
}
bottom: "fc8"
bottom: "label"
}

14
models/pascal_finetune_solver.prototxt Normal file
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train_net: "examples/pascal_finetune.prototxt"
test_net: "examples/pascal_finetune_val.prototxt"
test_iter: 100
test_interval: 400
base_lr: 0.0001
lr_policy: "step"
gamma: 0.1
stepsize: 50000
display: 20
max_iter: 400000
momentum: 0.9
weight_decay: 0.0005
snapshot: 10000
snapshot_prefix: "./snapshots/pascal_finetune_train"

376
models/pascal_finetune_val.prototxt Normal file
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name: "CaffeNet"
layers {
layer {
name: "data"
type: "window_data"
source: "/work5/rbg/convnet-selective-search/selective-search-data/window_file_2007_val.txt"
meanfile: "/home/rbg/working/caffe-rbg/data/ilsvrc2012_mean.binaryproto"
batchsize: 128
cropsize: 227
mirror: true
det_fg_threshold: 0.6
det_bg_threshold: 0.3
det_fg_fraction: 0.5
}
top: "data"
top: "label"
}
layers {
layer {
name: "conv1"
type: "conv"
num_output: 96
kernelsize: 11
stride: 4
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
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"
}
layers {
layer {
name: "pool1"
type: "pool"
pool: MAX
kernelsize: 3
stride: 2
}
bottom: "conv1"
top: "pool1"
}
layers {
layer {
name: "norm1"
type: "lrn"
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"
num_output: 256
group: 2
kernelsize: 5
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
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"
}
layers {
layer {
name: "pool2"
type: "pool"
pool: MAX
kernelsize: 3
stride: 2
}
bottom: "conv2"
top: "pool2"
}
layers {
layer {
name: "norm2"
type: "lrn"
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"
num_output: 384
kernelsize: 3
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
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"
}
layers {
layer {
name: "pad4"
type: "padding"
pad: 1
}
bottom: "conv3"
top: "pad4"
}
layers {
layer {
name: "conv4"
type: "conv"
num_output: 384
group: 2
kernelsize: 3
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
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"
}
layers {
layer {
name: "pad5"
type: "padding"
pad: 1
}
bottom: "conv4"
top: "pad5"
}
layers {
layer {
name: "conv5"
type: "conv"
num_output: 256
group: 2
kernelsize: 3
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
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"
}
layers {
layer {
name: "pool5"
type: "pool"
kernelsize: 3
pool: MAX
stride: 2
}
bottom: "conv5"
top: "pool5"
}
layers {
layer {
name: "fc6"
type: "innerproduct"
num_output: 4096
weight_filler {
type: "gaussian"
std: 0.005
}
bias_filler {
type: "constant"
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"
}
layers {
layer {
name: "drop6"
type: "dropout"
dropout_ratio: 0.5
}
bottom: "fc6"
top: "fc6"
}
layers {
layer {
name: "fc7"
type: "innerproduct"
num_output: 4096
weight_filler {
type: "gaussian"
std: 0.005
}
bias_filler {
type: "constant"
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"
}
layers {
layer {
name: "drop7"
type: "dropout"
dropout_ratio: 0.5
}
bottom: "fc7"
top: "fc7"
}
layers {
layer {
name: "fc8"
type: "innerproduct"
num_output: 21
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
blobs_lr: 1.
blobs_lr: 2.
weight_decay: 1.
weight_decay: 0.
}
bottom: "fc7"
top: "fc8"
}
layers {
layer {
name: "prob"
type: "softmax"
}
bottom: "fc8"
top: "prob"
}
layers {
layer {
name: "accuracy"
type: "accuracy"
}
bottom: "prob"
bottom: "label"
top: "accuracy"
}