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@davisking
davisking committed Oct 4, 2017
2 parents 2425dca + ea9aae0 commit 7352ef0
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Showing 3 changed files with 58 additions and 22 deletions.
42 changes: 24 additions & 18 deletions dlib/dnn/layers.h
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Original file line number Diff line number Diff line change
Expand Up @@ -164,7 +164,6 @@ namespace dlib

// set the initial bias values to zero
biases(params,filters.size()) = 0;

}

template <typename SUBNET>
Expand Down Expand Up @@ -346,24 +345,37 @@ namespace dlib
static_assert(0 <= _padding_x && _padding_x < _nc, "The padding must be smaller than the filter size.");

cont_(
num_con_outputs o
) :
learning_rate_multiplier(1),
weight_decay_multiplier(1),
bias_learning_rate_multiplier(1),
bias_weight_decay_multiplier(0),
num_filters_(o.num_outputs),
padding_y_(_padding_y),
padding_x_(_padding_x)
{
DLIB_CASSERT(num_filters_ > 0);
}

long num_filters() const { return _num_filters; }
cont_() : cont_(num_con_outputs(_num_filters)) {}

long num_filters() const { return num_filters_; }
long nr() const { return _nr; }
long nc() const { return _nc; }
long stride_y() const { return _stride_y; }
long stride_x() const { return _stride_x; }
long padding_y() const { return padding_y_; }
long padding_x() const { return padding_x_; }

void set_num_filters(long num)
{
DLIB_CASSERT(num > 0);
DLIB_CASSERT(get_layer_params().size() == 0,
"You can't change the number of filters in cont_ if the parameter tensor has already been allocated.");
num_filters_ = num;
}

double get_learning_rate_multiplier () const { return learning_rate_multiplier; }
double get_weight_decay_multiplier () const { return weight_decay_multiplier; }
void set_learning_rate_multiplier(double val) { learning_rate_multiplier = val; }
Expand Down Expand Up @@ -402,6 +414,7 @@ namespace dlib
weight_decay_multiplier(item.weight_decay_multiplier),
bias_learning_rate_multiplier(item.bias_learning_rate_multiplier),
bias_weight_decay_multiplier(item.bias_weight_decay_multiplier),
num_filters_(item.num_filters_),
padding_y_(item.padding_y_),
padding_x_(item.padding_x_)
{
Expand All @@ -427,25 +440,26 @@ namespace dlib
weight_decay_multiplier = item.weight_decay_multiplier;
bias_learning_rate_multiplier = item.bias_learning_rate_multiplier;
bias_weight_decay_multiplier = item.bias_weight_decay_multiplier;
num_filters_ = item.num_filters_;
return *this;
}

template <typename SUBNET>
void setup (const SUBNET& sub)
{
long num_inputs = _nr*_nc*sub.get_output().k();
long num_outputs = _num_filters;
long num_outputs = num_filters_;
// allocate params for the filters and also for the filter bias values.
params.set_size(num_inputs*_num_filters + _num_filters);
params.set_size(num_inputs*num_filters_ + num_filters_);

dlib::rand rnd(std::rand());
randomize_parameters(params, num_inputs+num_outputs, rnd);

filters = alias_tensor(sub.get_output().k(),_num_filters, _nr, _nc);
biases = alias_tensor(1,_num_filters);
filters = alias_tensor(sub.get_output().k(), num_filters_, _nr, _nc);
biases = alias_tensor(1,num_filters_);

// set the initial bias values to zero
biases(params,_num_filters) = 0;
biases(params,filters.size()) = 0;
}

template <typename SUBNET>
Expand Down Expand Up @@ -484,7 +498,7 @@ namespace dlib
{
serialize("cont_1", out);
serialize(item.params, out);
serialize(_num_filters, out);
serialize(item.num_filters_, out);
serialize(_nr, out);
serialize(_nc, out);
serialize(_stride_y, out);
Expand All @@ -503,15 +517,14 @@ namespace dlib
{
std::string version;
deserialize(version, in);
long num_filters;
long nr;
long nc;
int stride_y;
int stride_x;
if (version == "cont_1")
{
deserialize(item.params, in);
deserialize(num_filters, in);
deserialize(item.num_filters_, in);
deserialize(nr, in);
deserialize(nc, in);
deserialize(stride_y, in);
Expand All @@ -526,14 +539,6 @@ namespace dlib
deserialize(item.bias_weight_decay_multiplier, in);
if (item.padding_y_ != _padding_y) throw serialization_error("Wrong padding_y found while deserializing dlib::con_");
if (item.padding_x_ != _padding_x) throw serialization_error("Wrong padding_x found while deserializing dlib::con_");
if (num_filters != _num_filters)
{
std::ostringstream sout;
sout << "Wrong num_filters found while deserializing dlib::con_" << std::endl;
sout << "expected " << _num_filters << " but found " << num_filters << std::endl;
throw serialization_error(sout.str());
}

if (nr != _nr) throw serialization_error("Wrong nr found while deserializing dlib::con_");
if (nc != _nc) throw serialization_error("Wrong nc found while deserializing dlib::con_");
if (stride_y != _stride_y) throw serialization_error("Wrong stride_y found while deserializing dlib::con_");
Expand Down Expand Up @@ -592,6 +597,7 @@ namespace dlib
double weight_decay_multiplier;
double bias_learning_rate_multiplier;
double bias_weight_decay_multiplier;
long num_filters_;

int padding_y_;
int padding_x_;
Expand Down
31 changes: 31 additions & 0 deletions dlib/dnn/layers_abstract.h
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Original file line number Diff line number Diff line change
Expand Up @@ -941,6 +941,24 @@ namespace dlib
- #get_bias_weight_decay_multiplier() == 0
!*/

cont_(
num_con_outputs o
);
/*!
ensures
- #num_filters() == o.num_outputs
- #nr() == _nr
- #nc() == _nc
- #stride_y() == _stride_y
- #stride_x() == _stride_x
- #padding_y() == _padding_y
- #padding_x() == _padding_x
- #get_learning_rate_multiplier() == 1
- #get_weight_decay_multiplier() == 1
- #get_bias_learning_rate_multiplier() == 1
- #get_bias_weight_decay_multiplier() == 0
!*/

long num_filters(
) const;
/*!
Expand All @@ -950,6 +968,19 @@ namespace dlib
of filters.
!*/

void set_num_filters(
long num
);
/*!
requires
- num > 0
- get_layer_params().size() == 0
(i.e. You can't change the number of filters in cont_ if the parameter
tensor has already been allocated.)
ensures
- #num_filters() == num
!*/

long nr(
) const;
/*!
Expand Down
7 changes: 3 additions & 4 deletions tools/python/src/face_recognition.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -166,7 +166,7 @@ boost::python::list chinese_whispers_clustering(boost::python::list descriptors,
edges.push_back(sample_pair(i,j));
}
}
const auto num_clusters = chinese_whispers(edges, labels);
chinese_whispers(edges, labels);
for (size_t i = 0; i < labels.size(); ++i)
{
clusters.append(labels[i]);
Expand Down Expand Up @@ -242,7 +242,6 @@ boost::python::list get_face_chips (

boost::python::list chips_list;

int num_faces = faces.size();
std::vector<chip_details> dets;
for (auto& f : faces)
dets.push_back(get_face_chip_details(f, size, padding));
Expand All @@ -253,9 +252,9 @@ boost::python::list get_face_chips (
{
boost::python::list img;

for(int row=0; row<size; row++) {
for(size_t row=0; row<size; row++) {
boost::python::list row_list;
for(int col=0; col<size; col++) {
for(size_t col=0; col<size; col++) {
rgb_pixel pixel = chip(row, col);
boost::python::list item;

Expand Down

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