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Rev | Author | Line No. | Line |
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3 | PointedEar | 1 | #if !defined OFINDER |
2 | #define OFINDER |
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3 | |||
5 | PointedEar | 4 | #include <opencv2/core/core.hpp> |
5 | #include <opencv2/imgproc/imgproc.hpp> |
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3 | PointedEar | 6 | |
7 | class ObjectFinder { |
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8 | |||
9 | private: |
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10 | |||
11 | float hranges[2]; |
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12 | const float* ranges[3]; |
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13 | int channels[3]; |
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14 | |||
15 | float threshold; |
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16 | cv::MatND histogram; |
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17 | cv::SparseMat shistogram; |
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18 | bool isSparse; |
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19 | |||
20 | public: |
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21 | |||
22 | ObjectFinder() : threshold(0.1f), isSparse(false) { |
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23 | |||
24 | ranges[0]= hranges; // all channels have the same range |
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25 | ranges[1]= hranges; |
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26 | ranges[2]= hranges; |
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27 | } |
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28 | |||
29 | // Sets the threshold on histogram values [0,1] |
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30 | void setThreshold(float t) { |
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31 | |||
32 | threshold= t; |
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33 | } |
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34 | |||
35 | // Gets the threshold |
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36 | float getThreshold() { |
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37 | |||
38 | return threshold; |
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39 | } |
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40 | |||
41 | // Sets the reference histogram |
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42 | void setHistogram(const cv::MatND& h) { |
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43 | |||
44 | isSparse= false; |
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45 | histogram= h; |
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46 | cv::normalize(histogram,histogram,1.0); |
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47 | } |
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48 | |||
49 | // Sets the reference histogram |
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50 | void setHistogram(const cv::SparseMat& h) { |
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51 | |||
52 | isSparse= true; |
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53 | shistogram= h; |
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54 | cv::normalize(shistogram,shistogram,1.0,cv::NORM_L2); |
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55 | } |
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56 | |||
57 | // Finds the pixels belonging to the histogram |
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58 | cv::Mat find(const cv::Mat& image) { |
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59 | |||
60 | cv::Mat result; |
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61 | |||
62 | hranges[0]= 0.0; // range [0,255] |
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63 | hranges[1]= 255.0; |
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64 | channels[0]= 0; // the three channels |
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65 | channels[1]= 1; |
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66 | channels[2]= 2; |
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67 | |||
68 | if (isSparse) { // call the right function based on histogram type |
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69 | |||
70 | cv::calcBackProject(&image, |
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71 | 1, // one image |
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72 | channels, // vector specifying what histogram dimensions belong to what image channels |
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73 | shistogram, // the histogram we are using |
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74 | result, // the resulting back projection image |
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75 | ranges, // the range of values, for each dimension |
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76 | 255.0 // the scaling factor is chosen such that a histogram value of 1 maps to 255 |
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77 | ); |
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78 | |||
79 | } else { |
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80 | |||
81 | cv::calcBackProject(&image, |
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82 | 1, // one image |
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83 | channels, // vector specifying what histogram dimensions belong to what image channels |
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84 | histogram, // the histogram we are using |
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85 | result, // the resulting back projection image |
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86 | ranges, // the range of values, for each dimension |
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87 | 255.0 // the scaling factor is chosen such that a histogram value of 1 maps to 255 |
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88 | ); |
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89 | } |
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90 | |||
91 | |||
92 | // Threshold back projection to obtain a binary image |
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93 | if (threshold>0.0) |
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94 | cv::threshold(result, result, 255*threshold, 255, cv::THRESH_BINARY); |
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95 | |||
96 | return result; |
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97 | } |
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98 | |||
99 | cv::Mat find(const cv::Mat& image, float minValue, float maxValue, int *channels, int dim) { |
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100 | |||
101 | cv::Mat result; |
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102 | |||
103 | hranges[0]= minValue; |
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104 | hranges[1]= maxValue; |
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105 | |||
106 | for (int i=0; i<dim; i++) |
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107 | this->channels[i]= channels[i]; |
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108 | |||
109 | if (isSparse) { // call the right function based on histogram type |
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110 | |||
111 | cv::calcBackProject(&image, |
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112 | 1, // we only use one image at a time |
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113 | channels, // vector specifying what histogram dimensions belong to what image channels |
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114 | shistogram, // the histogram we are using |
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115 | result, // the resulting back projection image |
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116 | ranges, // the range of values, for each dimension |
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117 | 255.0 // the scaling factor is chosen such that a histogram value of 1 maps to 255 |
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118 | ); |
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119 | |||
120 | } else { |
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121 | |||
122 | cv::calcBackProject(&image, |
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123 | 1, // we only use one image at a time |
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124 | channels, // vector specifying what histogram dimensions belong to what image channels |
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125 | histogram, // the histogram we are using |
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126 | result, // the resulting back projection image |
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127 | ranges, // the range of values, for each dimension |
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128 | 255.0 // the scaling factor is chosen such that a histogram value of 1 maps to 255 |
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129 | ); |
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130 | } |
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131 | |||
132 | // Threshold back projection to obtain a binary image |
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133 | if (threshold>0.0) |
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134 | cv::threshold(result, result, 255*threshold, 255, cv::THRESH_BINARY); |
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135 | |||
136 | return result; |
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137 | } |
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138 | |||
139 | }; |
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140 | |||
141 | |||
142 | #endif |