def get_ap()

in siammot/eval/eval_det_ap.py [0:0]

• 21 lines of code
• 10 McCabe index (conditional complexity)

def get_ap(vid_class_gt: DataSample, vid_class_pred: DataSample, filter_fn, eval_frame_idxs, iou_thresh=[0.5]):
    """
    :param vid_class_gt: the ground truths for a specific class, in DataSample format
    :param vid_class_pred: the predictions for a specific class, in DataSample format
    :param filter_fn: a callable function to filter out detections
    :param eval_frame_idxs: the frame indexs where evaluation happens
    :param iou_thresh: the list of iou threshod that determines whether a detection is TP
    :returns
           vid_scores: the confidence for every predicted entity (a Python list)
           vid_pr_ious: the iou between the predicted entity and its matching gt entity (a Python list)
           vid_gt_ious: the iou between the gt entity and its matching predicted entity (a Python list)
    """
    if not isinstance(iou_thresh, list):
        iou_thresh = [iou_thresh]
    vid_scores = [[] for _ in iou_thresh]
    vid_pr_ious = [[] for _ in iou_thresh]
    vid_gt_ious = [[] for _ in iou_thresh]
    for frame_idx in eval_frame_idxs:

        gt_entities = vid_class_gt.get_entities_for_frame_num(frame_idx)
        pred_entities = vid_class_pred.get_entities_for_frame_num(frame_idx)

        # Remove detections for evaluation that are within ignore regions
        if filter_fn is not None:
            # Filter out ignored gt entities
            gt_entities, ignore_gt_entities = filter_fn(gt_entities, meta_data=vid_class_gt.metadata)
            # Filter out predicted entities that overlaps with ignored gt entities
            pred_entities, ignore_pred_entities = filter_fn(pred_entities, ignore_gt_entities)

        # sort the entity based on confidence scores
        pred_entities = sorted(pred_entities, key=lambda x: x.confidence, reverse=True)
        iou_matrix = bbs_iou(pred_entities, gt_entities)
        scores = [entity.confidence for entity in pred_entities]
        for i, _iou in enumerate(iou_thresh):
            # pred_ious, gt_ious = target_matching(pred_entities, gt_entities)
            pred_ious, gt_ious = greedy_matching(copy.deepcopy(iou_matrix), _iou)
            vid_scores[i] += scores
            vid_pr_ious[i] += pred_ious
            vid_gt_ious[i] += gt_ious

    return vid_scores, vid_pr_ious, vid_gt_ious