verifyCornerAccuracyWRTDatasetOnItsOwnMethod.m

%{
 * Copyright (C) 2020-2030, The Regents of The University of Michigan.
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 * AUTHOR: Bruce JK Huang (bjhuang[at]umich.edu)
 * WEBSITE: https://www.brucerobot.com/
%}

function cost = verifyCornerAccuracyWRTDatasetOnItsOwnMethod(method, indices, opt, bag_data, P)
    
    validate_methods = {'baseline', 'GN', 'GL_1', 'GL1-R'};
    chosen_method = find(strcmp(method, validate_methods));
    if isfield(method, 'optimized_method') || strcmpi(method, "baseline" ) 
        chosen_method = 1;
    end
    
    for i = 1:length(indices) % which validation data
        current_index = indices(i);
        cost_array = zeros(bag_data(current_index).num_tag, opt.num_lidar_target_pose);
        current_num_poses = bag_data(current_index).num_tag * opt.num_lidar_target_pose * opt.correspondance_per_pose;
        for j = 1:bag_data(current_index).num_tag % which tag in the validation dataset
            for k=1:opt.num_lidar_target_pose % which scan in the validation dataset
                if chosen_method == 1
                    current_corners_X = [bag_data(current_index).baseline(j).scan(k).corners];
                elseif chosen_method == 2
                    current_corners_X = [bag_data(current_index).baseline(j).scan(k).corners];
                elseif chosen_method == 3
                    current_corners_X = [bag_data(current_index).lidar_target(j).scan(k).corners];
                elseif chosen_method == 4
                    current_corners_X = [bag_data(current_index).lidar_target(j).scan(k).refined_corners];
                end
                current_corners_Y = [bag_data(current_index).camera_target(j).corners];
                scan_cost = verifyCornerAccuracy(current_corners_X(:, 1:4), current_corners_Y(:, 1:4), P);
                cost_array(j, k) = scan_cost;
            end
        end
        cost(i).name = bag_data(current_index).bagfile;
        cost(i).total_cost = sum(sum(cost_array, 2), 1);
        cost(i).num_pose = current_num_poses;
        cost(i).RMSE = sqrt(sum(sum(cost_array, 2), 1)/current_num_poses); % total cost of this dataset
%         cost(i).std = std(cost_array'); % std of cost of each scan
    end
end