Peter M. Groen / openbr

Commit 7722465207513f7503b52678f5de58e12fe3fcc8

Authored by Jordan Cheney
1 parent 66a1fdbf

Update to docs and better method for getting output of net

Inline Side-by-side
Showing 1 changed file with 9 additions and 4 deletions
openbr/plugins/classification/caffe.cpp
  View file @7722465
1 #include <openbr/plugins/openbr_internal.h> 1 #include <openbr/plugins/openbr_internal.h>
2 #include <openbr/core/opencvutils.h> 2 #include <openbr/core/opencvutils.h>
3 -#include <openbr/core/qtutils.h>  
4 3
5 -#include <opencv2/imgproc/imgproc.hpp>  
6 #include <caffe/caffe.hpp> 4 #include <caffe/caffe.hpp>
7 5
8 using caffe::Caffe; 6 using caffe::Caffe;
@@ -101,8 +99,9 @@ protected: @@ -101,8 +99,9 @@ protected:
101 99
102 dataLayer->AddMatVector(src.toVector().toStdVector(), std::vector<int>(src.size(), 0)); 100 dataLayer->AddMatVector(src.toVector().toStdVector(), std::vector<int>(src.size(), 0));
103 101
104 - Blob<float> *output = net->ForwardPrefilled()[1]; // index 0 is the labels from the data layer (in this case the 0 array we passed in above).  
105 - // index 1 is the ouput of the final layer, which is what we want 102 + net->ForwardPrefilled();
  103 + Blob<float> *output = net->blobs().back().get();
  104 +
106 int dimFeatures = output->count() / dataLayer->batch_size(); 105 int dimFeatures = output->count() / dataLayer->batch_size();
107 for (int n = 0; n < dataLayer->batch_size(); n++) 106 for (int n = 0; n < dataLayer->batch_size(); n++)
108 dst += Mat(1, dimFeatures, CV_32FC1, output->mutable_cpu_data() + output->offset(n)); 107 dst += Mat(1, dimFeatures, CV_32FC1, output->mutable_cpu_data() + output->offset(n));
@@ -115,6 +114,9 @@ protected: @@ -115,6 +114,9 @@ protected:
115 * \brief This transform treats the output of the network as a feature vector and appends it unchanged to dst. Dst will have 114 * \brief This transform treats the output of the network as a feature vector and appends it unchanged to dst. Dst will have
116 * length equal to the batch size of the network. 115 * length equal to the batch size of the network.
117 * \author Jordan Cheney \cite JordanCheney 116 * \author Jordan Cheney \cite JordanCheney
  117 + * \br_property QString model path to prototxt model file
  118 + * \br_property QString weights path to caffemodel file
  119 + * \br_property int gpuDevice ID of GPU to use. gpuDevice < 0 runs on the CPU only.
118 */ 120 */
119 class CaffeFVTransform : public CaffeBaseTransform 121 class CaffeFVTransform : public CaffeBaseTransform
120 { 122 {
@@ -139,6 +141,9 @@ BR_REGISTER(Transform, CaffeFVTransform) @@ -139,6 +141,9 @@ BR_REGISTER(Transform, CaffeFVTransform)
139 * using the keys "Labels" and "Confidences" respectively. The length of these lists is equivalent to the provided batch size. 141 * using the keys "Labels" and "Confidences" respectively. The length of these lists is equivalent to the provided batch size.
140 * If batch size == 1, the results are stored as a float and int using the keys "Label", and "Confidence" respectively. 142 * If batch size == 1, the results are stored as a float and int using the keys "Label", and "Confidence" respectively.
141 * \author Jordan Cheney \cite jcheney 143 * \author Jordan Cheney \cite jcheney
  144 + * \br_property QString model path to prototxt model file
  145 + * \br_property QString weights path to caffemodel file
  146 + * \br_property int gpuDevice ID of GPU to use. gpuDevice < 0 runs on the CPU only.
142 */ 147 */
143 class CaffeClassifierTransform : public CaffeBaseTransform 148 class CaffeClassifierTransform : public CaffeBaseTransform
144 { 149 {