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why the features devided by max_radio_radius_ #38

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shekmun opened this issue Mar 30, 2020 · 0 comments

shekmun commented Mar 30, 2020

feat[0] =candidate_pixel_locations(max_id,0)/max_radio_radius_; is divided by max_radio_radius_.

When the random forest is training, the candidated position is calculated with the array candidate_pixel_locations.
double project_x1 = rotation(0,0) * candidate_pixel_locations(j,0) + rotation(0,1) * candidate_pixel_locations(j,1);----(1)

But when calculating the binary features, the stored feature (which is divided by max_radio_radius_) is used.
double x1 = rand_forest[iter].nodes_[currnode].feat[0];
...
double project_x1 = rotation(0,0) * x1 + rotation(0,1) * y1;----(2)

which meas that the above code (1) and (2) is not using the same candidate_pixel_locations.

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