def METHOD_NAME(self):
    coco_gt = COCO(self.ann_file)
    coco_pred = coco_gt.loadRes(self.preds)
    coco_eval = COCOeval(coco_gt, coco_pred, iouType='segm')
    coco_eval.params.useCats = 0
    coco_eval.METHOD_NAME()
    coco_eval.accumulate()
    coco_eval.summarize()
    ap_labels = [
        'mAP 0.5:0.95', 'AP 0.5', 'AP 0.75', 'AP 0.5:0.95 S',
        'AP 0.5:0.95 M', 'AP 0.5:0.95 L'
    ]
    ap_metrics = coco_eval.stats[:6]
    eval_metrics = {la: m for la, m in zip(ap_labels, ap_metrics)}
    if self.calculate_precision_and_iou_metrics:
        precision_at_k, overall_iou, mean_iou = calculate_precision_at_k_and_iou_metrics(
            coco_gt, coco_pred)
        eval_metrics.update({
            f'P@{k}': m
            for k, m in zip([0.5, 0.6, 0.7, 0.8, 0.9], precision_at_k)
        })
        eval_metrics.update({
            'overall_iou': overall_iou,
            'mean_iou': mean_iou
        })
    return eval_metrics