Caffe
Public Member Functions | Protected Member Functions | Protected Attributes | List of all members
caffe::SPPLayer< Dtype > Class Template Reference

Does spatial pyramid pooling on the input image by taking the max, average, etc. within regions so that the result vector of different sized images are of the same size. More...

#include <spp_layer.hpp>

Inheritance diagram for caffe::SPPLayer< Dtype >:
caffe::Layer< Dtype >

Public Member Functions

 SPPLayer (const LayerParameter &param)
 
virtual void LayerSetUp (const vector< Blob< Dtype > *> &bottom, const vector< Blob< Dtype > *> &top)
 Does layer-specific setup: your layer should implement this function as well as Reshape. More...
 
virtual void Reshape (const vector< Blob< Dtype > *> &bottom, const vector< Blob< Dtype > *> &top)
 Adjust the shapes of top blobs and internal buffers to accommodate the shapes of the bottom blobs. More...
 
virtual const char * type () const
 Returns the layer type.
 
virtual int ExactNumBottomBlobs () const
 Returns the exact number of bottom blobs required by the layer, or -1 if no exact number is required. More...
 
virtual int ExactNumTopBlobs () const
 Returns the exact number of top blobs required by the layer, or -1 if no exact number is required. More...
 
- Public Member Functions inherited from caffe::Layer< Dtype >
 Layer (const LayerParameter &param)
 
void SetUp (const vector< Blob< Dtype > *> &bottom, const vector< Blob< Dtype > *> &top)
 Implements common layer setup functionality. More...
 
Dtype Forward (const vector< Blob< Dtype > *> &bottom, const vector< Blob< Dtype > *> &top)
 Given the bottom blobs, compute the top blobs and the loss. More...
 
void Backward (const vector< Blob< Dtype > *> &top, const vector< bool > &propagate_down, const vector< Blob< Dtype > *> &bottom)
 Given the top blob error gradients, compute the bottom blob error gradients. More...
 
vector< shared_ptr< Blob< Dtype > > > & blobs ()
 Returns the vector of learnable parameter blobs.
 
const LayerParameter & layer_param () const
 Returns the layer parameter.
 
virtual void ToProto (LayerParameter *param, bool write_diff=false)
 Writes the layer parameter to a protocol buffer.
 
Dtype loss (const int top_index) const
 Returns the scalar loss associated with a top blob at a given index.
 
void set_loss (const int top_index, const Dtype value)
 Sets the loss associated with a top blob at a given index.
 
virtual int MinBottomBlobs () const
 Returns the minimum number of bottom blobs required by the layer, or -1 if no minimum number is required. More...
 
virtual int MaxBottomBlobs () const
 Returns the maximum number of bottom blobs required by the layer, or -1 if no maximum number is required. More...
 
virtual int MinTopBlobs () const
 Returns the minimum number of top blobs required by the layer, or -1 if no minimum number is required. More...
 
virtual int MaxTopBlobs () const
 Returns the maximum number of top blobs required by the layer, or -1 if no maximum number is required. More...
 
virtual bool EqualNumBottomTopBlobs () const
 Returns true if the layer requires an equal number of bottom and top blobs. More...
 
virtual bool AutoTopBlobs () const
 Return whether "anonymous" top blobs are created automatically by the layer. More...
 
virtual bool AllowForceBackward (const int bottom_index) const
 Return whether to allow force_backward for a given bottom blob index. More...
 
bool param_propagate_down (const int param_id)
 Specifies whether the layer should compute gradients w.r.t. a parameter at a particular index given by param_id. More...
 
void set_param_propagate_down (const int param_id, const bool value)
 Sets whether the layer should compute gradients w.r.t. a parameter at a particular index given by param_id.
 

Protected Member Functions

virtual void Forward_cpu (const vector< Blob< Dtype > *> &bottom, const vector< Blob< Dtype > *> &top)
 Using the CPU device, compute the layer output.
 
virtual void Backward_cpu (const vector< Blob< Dtype > *> &top, const vector< bool > &propagate_down, const vector< Blob< Dtype > *> &bottom)
 Using the CPU device, compute the gradients for any parameters and for the bottom blobs if propagate_down is true.
 
virtual LayerParameter GetPoolingParam (const int pyramid_level, const int bottom_h, const int bottom_w, const SPPParameter spp_param)
 
- Protected Member Functions inherited from caffe::Layer< Dtype >
virtual void Forward_gpu (const vector< Blob< Dtype > *> &bottom, const vector< Blob< Dtype > *> &top)
 Using the GPU device, compute the layer output. Fall back to Forward_cpu() if unavailable.
 
virtual void Backward_gpu (const vector< Blob< Dtype > *> &top, const vector< bool > &propagate_down, const vector< Blob< Dtype > *> &bottom)
 Using the GPU device, compute the gradients for any parameters and for the bottom blobs if propagate_down is true. Fall back to Backward_cpu() if unavailable.
 
virtual void CheckBlobCounts (const vector< Blob< Dtype > *> &bottom, const vector< Blob< Dtype > *> &top)
 
void SetLossWeights (const vector< Blob< Dtype > *> &top)
 

Protected Attributes

int pyramid_height_
 
int bottom_h_
 
int bottom_w_
 
int num_
 
int channels_
 
int kernel_h_
 
int kernel_w_
 
int pad_h_
 
int pad_w_
 
bool reshaped_first_time_
 
shared_ptr< SplitLayer< Dtype > > split_layer_
 the internal Split layer that feeds the pooling layers
 
vector< Blob< Dtype > * > split_top_vec_
 top vector holder used in call to the underlying SplitLayer::Forward
 
vector< vector< Blob< Dtype > * > * > pooling_bottom_vecs_
 bottom vector holder used in call to the underlying PoolingLayer::Forward
 
vector< shared_ptr< PoolingLayer< Dtype > > > pooling_layers_
 the internal Pooling layers of different kernel sizes
 
vector< vector< Blob< Dtype > * > * > pooling_top_vecs_
 top vector holders used in call to the underlying PoolingLayer::Forward
 
vector< Blob< Dtype > * > pooling_outputs_
 pooling_outputs stores the outputs of the PoolingLayers
 
vector< FlattenLayer< Dtype > * > flatten_layers_
 the internal Flatten layers that the Pooling layers feed into
 
vector< vector< Blob< Dtype > * > * > flatten_top_vecs_
 top vector holders used in call to the underlying FlattenLayer::Forward
 
vector< Blob< Dtype > * > flatten_outputs_
 flatten_outputs stores the outputs of the FlattenLayers
 
vector< Blob< Dtype > * > concat_bottom_vec_
 bottom vector holder used in call to the underlying ConcatLayer::Forward
 
shared_ptr< ConcatLayer< Dtype > > concat_layer_
 the internal Concat layers that the Flatten layers feed into
 
- Protected Attributes inherited from caffe::Layer< Dtype >
LayerParameter layer_param_
 
Phase phase_
 
vector< shared_ptr< Blob< Dtype > > > blobs_
 
vector< bool > param_propagate_down_
 
vector< Dtype > loss_
 

Detailed Description

template<typename Dtype>
class caffe::SPPLayer< Dtype >

Does spatial pyramid pooling on the input image by taking the max, average, etc. within regions so that the result vector of different sized images are of the same size.

Member Function Documentation

§ ExactNumBottomBlobs()

template<typename Dtype >
virtual int caffe::SPPLayer< Dtype >::ExactNumBottomBlobs ( ) const
inlinevirtual

Returns the exact number of bottom blobs required by the layer, or -1 if no exact number is required.

This method should be overridden to return a non-negative value if your layer expects some exact number of bottom blobs.

Reimplemented from caffe::Layer< Dtype >.

§ ExactNumTopBlobs()

template<typename Dtype >
virtual int caffe::SPPLayer< Dtype >::ExactNumTopBlobs ( ) const
inlinevirtual

Returns the exact number of top blobs required by the layer, or -1 if no exact number is required.

This method should be overridden to return a non-negative value if your layer expects some exact number of top blobs.

Reimplemented from caffe::Layer< Dtype >.

§ LayerSetUp()

template<typename Dtype >
void caffe::SPPLayer< Dtype >::LayerSetUp ( const vector< Blob< Dtype > *> &  bottom,
const vector< Blob< Dtype > *> &  top 
)
virtual

Does layer-specific setup: your layer should implement this function as well as Reshape.

Parameters
bottomthe preshaped input blobs, whose data fields store the input data for this layer
topthe allocated but unshaped output blobs

This method should do one-time layer specific setup. This includes reading and processing relevent parameters from the layer_param_. Setting up the shapes of top blobs and internal buffers should be done in Reshape, which will be called before the forward pass to adjust the top blob sizes.

Reimplemented from caffe::Layer< Dtype >.

§ Reshape()

template<typename Dtype >
void caffe::SPPLayer< Dtype >::Reshape ( const vector< Blob< Dtype > *> &  bottom,
const vector< Blob< Dtype > *> &  top 
)
virtual

Adjust the shapes of top blobs and internal buffers to accommodate the shapes of the bottom blobs.

Parameters
bottomthe input blobs, with the requested input shapes
topthe top blobs, which should be reshaped as needed

This method should reshape top blobs as needed according to the shapes of the bottom (input) blobs, as well as reshaping any internal buffers and making any other necessary adjustments so that the layer can accommodate the bottom blobs.

Implements caffe::Layer< Dtype >.


The documentation for this class was generated from the following files: