ANSCORE/modules/ANSMOT/ByteTrackEigen/src/EigenBoundingBoxIoUMatching.cpp

#include "EigenBoundingBoxIoUMatching.h"
namespace ByteTrackEigen {
    /**
     * Calculates the Intersection over Union (IoU) for pairs of bounding boxes.
     *
     * @param track_boxes Matrix of tracking boxes, expected to be in the format (N, 4).
     * @param detection_boxes Matrix of detection boxes, expected to be in the format (M, 4).
     * @return Matrix of IoU values, with dimensions (N, M).
     */
    Eigen::MatrixXd box_iou_batch(const Eigen::MatrixXd& track_boxes, const Eigen::MatrixXd& detection_boxes) {
        // Validate the shape of input matrices
        if (track_boxes.cols() != 4 || detection_boxes.cols() != 4) {
            throw std::invalid_argument("Input matrices must have 4 columns each.");
        }

        int N = (int)track_boxes.rows();
        int M = (int)detection_boxes.rows();

        // Calculate areas of the track boxes and detection boxes
        Eigen::VectorXd track_areas = (track_boxes.col(2) - track_boxes.col(0))
            .cwiseProduct(track_boxes.col(3) - track_boxes.col(1));
        Eigen::VectorXd detection_areas = (detection_boxes.col(2) - detection_boxes.col(0))
            .cwiseProduct(detection_boxes.col(3) - detection_boxes.col(1));

        // Initialize the IoU matrix
        Eigen::MatrixXd iou_matrix(N, M);

        // Compute IoU for each pair of boxes
        for (int i = 0; i < N; ++i) {
            for (int j = 0; j < M; ++j) {
                // Calculate intersection box coordinates
                double inter_x_min = std::max(track_boxes(i, 0), detection_boxes(j, 0));
                double inter_y_min = std::max(track_boxes(i, 1), detection_boxes(j, 1));
                double inter_x_max = std::min(track_boxes(i, 2), detection_boxes(j, 2));
                double inter_y_max = std::min(track_boxes(i, 3), detection_boxes(j, 3));

                // Compute intersection area
                double inter_width = std::max(inter_x_max - inter_x_min, 0.0);
                double inter_height = std::max(inter_y_max - inter_y_min, 0.0);
                double inter_area = inter_width * inter_height;

                // Calculate IoU
                iou_matrix(i, j) = inter_area / (track_areas(i) + detection_areas(j) - inter_area);
            }
        }

        return iou_matrix;
    }

    /**
     * Computes the IoU-based distance matrix for tracking purposes.
     *
     * @param track_list_a Vector of KalmanBBoxTrack, representing the first set of tracks.
     * @param track_list_b Vector of KalmanBBoxTrack, representing the second set of tracks.
     * @return A matrix representing the cost of matching tracks in track_list_a to track_list_b.
     */
    Eigen::MatrixXd iou_distance(
        const std::vector<KalmanBBoxTrack>& track_list_a,
        const std::vector<KalmanBBoxTrack>& track_list_b
    ) {
        size_t m = track_list_a.size();
        size_t n = track_list_b.size();

        // Extract bounding boxes from tracks
        Eigen::MatrixXd tlbr_list_a(m, 4);
        for (size_t i = 0; i < m; i++) {
            tlbr_list_a.row(i) = track_list_a[i].tlbr();
        }

        Eigen::MatrixXd tlbr_list_b(n, 4);
        for (size_t i = 0; i < n; i++) {
            tlbr_list_b.row(i) = track_list_b[i].tlbr();
        }

        // Calculate IoUs and form the cost matrix
        Eigen::MatrixXd ious;
        if (tlbr_list_a.rows() == 0 || tlbr_list_b.rows() == 0) {
            ious = Eigen::MatrixXd::Zero(tlbr_list_a.rows(), tlbr_list_b.rows());
        }
        else {
            ious = box_iou_batch(tlbr_list_a, tlbr_list_b);
        }
        Eigen::MatrixXd cost_matrix = Eigen::MatrixXd::Ones(m, n) - ious;

        return cost_matrix;
    }

    /**
     * Matches detections to tracks based on the highest IoU.
     *
     * @param tlbr_boxes Matrix of bounding boxes for detections (N, 4).
     * @param tracks Vector of KalmanBBoxTrack representing the current tracks.
     * @return Vector of updated track IDs after matching.
     */
    std::vector<int> match_detections_with_tracks(
        const Eigen::MatrixXd& tlbr_boxes,
        const std::vector<KalmanBBoxTrack>& tracks
    ) {
        size_t m = tracks.size();
        size_t n = tlbr_boxes.rows();

        // Clone the input track_ids to operate on
        std::vector<int> track_ids(n, -1);

        // Extract bounding boxes from tracks
        Eigen::MatrixXd track_boxes(m, 4);
        for (size_t i = 0; i < m; i++) {
            track_boxes.row(i) = tracks[i].tlbr();
        }

        // Calculate IoU matrix
        Eigen::MatrixXd iou = box_iou_batch(track_boxes, tlbr_boxes);

        // Match detections with tracks based on IoU
        for (size_t i = 0; i < m; i++) {
            int idx_max = -1;
            double max_val = 0;
            for (size_t j = 0; j < n; j++) {
                if (iou(i, j) > max_val) {
                    max_val = iou(i, j);
                    idx_max = (int)j;
                }
            }

            // Assign track IDs based on highest IoU
            if (max_val > 0) {
                track_ids[idx_max] = tracks[i].get_track_id();
            }
        }

        return track_ids;
    }

}