| 125 | |
| 126 | public: |
| 127 | virtual void |
| 128 | onInit() |
| 129 | { |
| 130 | node_ = getNodeHandle(); |
| 131 | private_node_ = getPrivateNodeHandle(); |
| 132 | |
| 133 | num_class1 = 0; |
| 134 | num_class0 = 0; |
| 135 | num_TP_class1 = 0; |
| 136 | num_FP_class1 = 0; |
| 137 | num_TP_class0 = 0; |
| 138 | num_FP_class0 = 0; |
| 139 | |
| 140 | int qs; |
| 141 | if(!private_node_.getParam("Q_Size",qs)){ |
| 142 | ROS_ERROR("could not find Q_Size parameter"); |
| 143 | qs=3; |
| 144 | } |
| 145 | |
| 146 | int NS; |
| 147 | if(!private_node_.getParam("num_Training_Samples",NS)){ |
| 148 | NS = 350; // default sets asside very little for training |
| 149 | private_node_.setParam("num_Training_Samples",NS); |
| 150 | } |
| 151 | HDAC_.setMaxSamples(NS); |
| 152 | |
| 153 | // Published Messages |
| 154 | pub_rois_ = node_.advertise<Rois>("HaarDispAdaOutputRois",qs); |
| 155 | pub_Color_Image_ = node_.advertise<Image>("HaarDispAdaColorImage",qs); |
| 156 | pub_Disparity_Image_= node_.advertise<DisparityImage>("HaarDispAdaDisparityImage",qs); |
| 157 | |
| 158 | // Subscribe to Messages |
| 159 | sub_image_.subscribe(node_,"Color_Image",qs); |
| 160 | sub_disparity_.subscribe(node_, "Disparity_Image",qs); |
| 161 | sub_rois_.subscribe(node_,"input_rois",qs); |
| 162 | |
| 163 | // Sync the Synchronizer |
| 164 | approximate_sync_.reset(new ApproximateSync(ApproximatePolicy(qs), |
| 165 | sub_image_, |
| 166 | sub_disparity_, |
| 167 | sub_rois_)); |
| 168 | |
| 169 | approximate_sync_->registerCallback(boost::bind(&HaarDispAdaNodelet::imageCb, |
| 170 | this, |
| 171 | _1, |
| 172 | _2, |
| 173 | _3)); |
| 174 | } |
| 175 | int |
| 176 | get_mode() |
| 177 | { |
nothing calls this directly
no test coverage detected