Peter M. Groen / openbr

Commit 5f37e44fb324453e4854eecfa035b97a169e10c7

Authored by Josh Klontz
1 parent 94f8e680

added more transforms

Inline Side-by-side
Showing 4 changed files with 75 additions and 17 deletions
sdk/plugins/algorithms.cpp
  View file @5f37e44
... ... @@ -50,7 +50,7 @@ class AlgorithmsInitializer : public Initializer
50 50 Globals->abbreviations.insert("SmallSIFT", "Open+LimitSize(512)+KeyPointDetector(SIFT)+KeyPointDescriptor(SIFT):KeyPointMatcher(BruteForce)");
51 51 Globals->abbreviations.insert("SmallSURF", "Open+LimitSize(512)+KeyPointDetector(SURF)+KeyPointDescriptor(SURF):KeyPointMatcher(BruteForce)");
52 52 Globals->abbreviations.insert("ColorHist", "Open+LimitSize(512)!EnsureChannels(3)+SplitChannels+Hist(256,0,8)+Cat+Normalize(L1):L2");
53   - Globals->abbreviations.insert("IHH", "Open+SplitChannels/(Cvt(Gray)+Gradient+Bin(0,6.283,8,true))+Integral+Merge+IntegralSampler");
  53 + Globals->abbreviations.insert("IHH", "Open+(RG+MAdd(0.5))/(Cvt(Gray)+Gradient+Bin(0,360,8,true))+Merge+Integral+IntegralSampler+CvtFloat:L2");
54 54  
55 55 // Hash
56 56 Globals->abbreviations.insert("FileName", "Name+Identity:Identical");
... ...
sdk/plugins/cvt.cpp
  View file @5f37e44
... ... @@ -160,6 +160,63 @@ class EnsureChannelsTransform : public UntrainableTransform
160 160  
161 161 BR_REGISTER(Transform, EnsureChannelsTransform)
162 162  
  163 +/*!
  164 + * \ingroup transforms
  165 + * \brief Normalized RG color space.
  166 + * \author Josh Klontz \cite jklontz
  167 + */
  168 +class RGTransform : public UntrainableTransform
  169 +{
  170 + Q_OBJECT
  171 +
  172 + void project(const Template &src, Template &dst) const
  173 + {
  174 + if (src.m().type() != CV_8UC3)
  175 + qFatal("Expected CV_8UC3 images.");
  176 +
  177 + const Mat &m = src.m();
  178 + Mat R(m.size(), CV_8UC1); // R / (R+G+B)
  179 + Mat G(m.size(), CV_8UC1); // G / (R+G+B)
  180 +
  181 + for (int i=0; i<m.rows; i++)
  182 + for (int j=0; j<m.cols; j++) {
  183 + Vec3b v = m.at<Vec3b>(i,j);
  184 + uchar& b = v[0];
  185 + uchar& g = v[1];
  186 + uchar& r = v[2];
  187 +
  188 + R.at<uchar>(i, j) = saturate_cast<uchar>(255.0*r/(r+g+b));
  189 + G.at<uchar>(i, j) = saturate_cast<uchar>(255.0*g/(r+g+b));
  190 + }
  191 +
  192 + dst.append(R);
  193 + dst.append(G);
  194 + }
  195 +};
  196 +
  197 +BR_REGISTER(Transform, RGTransform)
  198 +
  199 +/*!
  200 + * \ingroup transforms
  201 + * \brief dst = a*src+b
  202 + * \author Josh Klontz \cite jklontz
  203 + */
  204 +class MAddTransform : public UntrainableTransform
  205 +{
  206 + Q_OBJECT
  207 + Q_PROPERTY(double a READ get_a WRITE set_a RESET reset_a STORED false)
  208 + Q_PROPERTY(double b READ get_b WRITE set_b RESET reset_b STORED false)
  209 + BR_PROPERTY(double, a, 1)
  210 + BR_PROPERTY(double, b, 0)
  211 +
  212 + void project(const Template &src, Template &dst) const
  213 + {
  214 + src.m().convertTo(dst.m(), src.m().depth(), a, b);
  215 + }
  216 +};
  217 +
  218 +BR_REGISTER(Transform, MAddTransform)
  219 +
163 220 } // namespace br
164 221  
165 222 #include "cvt.moc"
... ...
sdk/plugins/hist.cpp
  View file @5f37e44
... ... @@ -83,13 +83,13 @@ class BinTransform : public UntrainableTransform
83 83  
84 84 void project(const Template &src, Template &dst) const
85 85 {
86   - src.m().convertTo(dst, bins > 256 ? CV_16U : CV_8U, bins/(max-min));
  86 + src.m().convertTo(dst, bins > 256 ? CV_16U : CV_8U, bins/(max-min), -0.5 /* floor */);
87 87 if (!split) return;
88 88  
89 89 Mat input = dst;
90 90 QList<Mat> outputs; outputs.reserve(bins);
91 91 for (int i=0; i<bins; i++)
92   - outputs.append(input == i);
  92 + outputs.append(input == i); // Note: Matrix elements are 0 or 255
93 93 dst.clear(); dst.append(outputs);
94 94 }
95 95 };
... ...
sdk/plugins/integral.cpp
  View file @5f37e44
... ... @@ -2,6 +2,8 @@
2 2 #include <Eigen/Core>
3 3 #include <openbr_plugin.h>
4 4  
  5 +#include "core/opencvutils.h"
  6 +
5 7 using namespace cv;
6 8  
7 9 namespace br
... ... @@ -26,25 +28,25 @@ BR_REGISTER(Transform, IntegralTransform)
26 28  
27 29 /*!
28 30 * \ingroup transforms
29   - * \brief Sliding window object recognition from a multi-channel intergral image.
  31 + * \brief Sliding window feature extraction from a multi-channel intergral image.
30 32 * \author Josh Klontz \cite jklontz
31 33 */
32   -class IntegralSampler : public UntrainableTransform
  34 +class IntegralSamplerTransform : public UntrainableTransform
33 35 {
34 36 Q_OBJECT
35 37 Q_PROPERTY(int scales READ get_scales WRITE set_scales RESET reset_scales STORED false)
36 38 Q_PROPERTY(float scaleFactor READ get_scaleFactor WRITE set_scaleFactor RESET reset_scaleFactor STORED false)
37 39 Q_PROPERTY(float stepFactor READ get_stepFactor WRITE set_stepFactor RESET reset_stepFactor STORED false)
38 40 Q_PROPERTY(int minSize READ get_minSize WRITE set_minSize RESET reset_minSize STORED false)
39   - BR_PROPERTY(int, scales, 1)
40   - BR_PROPERTY(float, scaleFactor, 1.25)
  41 + BR_PROPERTY(int, scales, 3)
  42 + BR_PROPERTY(float, scaleFactor, 2)
41 43 BR_PROPERTY(float, stepFactor, 0.25)
42 44 BR_PROPERTY(int, minSize, 8)
43 45  
44 46 void project(const Template &src, Template &dst) const
45 47 {
46 48 typedef Eigen::Map< const Eigen::Matrix<qint32,Eigen::Dynamic,1> > InputDescriptor;
47   - typedef Eigen::Map< Eigen::Matrix<qint32,Eigen::Dynamic,1> > OutputDescriptor;
  49 + typedef Eigen::Map< Eigen::Matrix<float,Eigen::Dynamic,1> > OutputDescriptor;
48 50 const Mat &m = src.m();
49 51 if (m.depth() != CV_32S) qFatal("Expected CV_32S matrix depth.");
50 52 const int channels = m.channels();
... ... @@ -53,16 +55,16 @@ class IntegralSampler : public UntrainableTransform
53 55 int descriptors = 0;
54 56 int currentSize = min(m.rows, m.cols)-1;
55 57 for (int scale=0; scale<scales; scale++) {
56   - descriptors += ceil((m.rows-currentSize)*stepFactor/currentSize) *
57   - ceil((m.cols-currentSize)*stepFactor/currentSize);
  58 + descriptors += int(1+(m.rows-currentSize)/(currentSize*stepFactor)) *
  59 + int(1+(m.cols-currentSize)/(currentSize*stepFactor));
58 60 currentSize /= scaleFactor;
59 61 if (currentSize < minSize)
60 62 break;
61 63 }
62   - Mat n(descriptors, channels, CV_32SC1);
  64 + Mat n(descriptors, channels, CV_32FC1);
63 65  
64 66 const qint32 *dataIn = (qint32*)m.data;
65   - qint32 *dataOut = (qint32*)n.data;
  67 + float *dataOut = (float*)n.data;
66 68 currentSize = min(m.rows, m.cols)-1;
67 69 int index = 0;
68 70 for (int scale=0; scale<scales; scale++) {
... ... @@ -71,10 +73,10 @@ class IntegralSampler : public UntrainableTransform
71 73 for (int j=currentSize; j<m.cols; j+=currentStep) {
72 74 InputDescriptor a(dataIn+((i-currentSize)*rowStep+(j-currentSize)*channels), channels, 1);
73 75 InputDescriptor b(dataIn+((i-currentSize)*rowStep+ j *channels), channels, 1);
74   - InputDescriptor c(dataIn+( i *rowStep+(j-currentSize)*channels), channels, 1);
75   - InputDescriptor d(dataIn+( i *rowStep+ j *channels), channels, 1);
  76 + InputDescriptor c(dataIn+(i *rowStep+(j-currentSize)*channels), channels, 1);
  77 + InputDescriptor d(dataIn+(i *rowStep+ j *channels), channels, 1);
76 78 OutputDescriptor y(dataOut+(index*channels), channels, 1);
77   - y = d-b-c+a;
  79 + y = (d-b-c+a).cast<float>()/(currentSize*currentSize);
78 80 index++;
79 81 }
80 82 }
... ... @@ -82,12 +84,11 @@ class IntegralSampler : public UntrainableTransform
82 84 if (currentSize < minSize)
83 85 break;
84 86 }
85   -
86 87 dst.m() = n;
87 88 }
88 89 };
89 90  
90   -BR_REGISTER(Transform, IntegralSampler)
  91 +BR_REGISTER(Transform, IntegralSamplerTransform)
91 92  
92 93 /*!
93 94 * \ingroup transforms
... ...