Bug in eval.py while computing fp statistics. [with proposed solution]

[srimannarayanabaratam]

Line https://github.com/traveller59/kitti-object-eval-python/blob/master/eval.py#L277 only applies the nstuff filter when metric =0 i.e; evaluating on image 2D bbbox. The current implementation gives poor performance when evaluation is done through bev or 3D iou.

Also, the official kitti evaluate_object.cpp [download their dev kit] does not "explicitly" filters the fps for metric=0. Rather, they use the box_overlap method corresponding to the respective metric (image2D/bev/3D).

So, I suggest a simple fix for the same as shown below.

if compute_fp:
    # count fp
    for i in range(det_size):
        if (not (assigned_detection[i] or ignored_det[i] == -1
                 or ignored_det[i] == 1 or ignored_threshold[i])):
            fp += 1
    nstuff = 0
    # do not consider detections falling under neutral zones as fp
    if metric==0:
        overlaps_dt_dc = image_box_overlap(dt_bboxes, dc_bboxes, 0)
    elif metric==1:
        overlaps_dt_dc = bev_box_overlap(dt_bboxes, dc_bboxes, 0)
    else:   # metric==2:
        overlaps_dt_dc = d3_box_overlap(dt_bboxes, dc_bboxes, 0)
    for i in range(dc_bboxes.shape[0]):
        for j in range(det_size):
            if (assigned_detection[j]):
                continue
            if (ignored_det[j] == -1 or ignored_det[j] == 1):
                continue
            if (ignored_threshold[j]):
                continue
            if overlaps_dt_dc[j, i] > min_overlap:
                assigned_detection[j] = True
                nstuff += 1
    fp -= nstuff