def _evaluate_predictions(annotations_dir, results): """ Calculate the log-average miss rate for the provided results on the test set. """ gt = COCO(osp.join(annotations_dir, 'test.json')) dt = gt.loadRes(results) coco_eval = COCOeval(gt, dt, 'bbox') coco_eval.evaluate() coco_eval.accumulate() lamr = coco_eval.calculate_lamr() params = {'hRng': coco_eval.params.hRng[0], 'vRng': coco_eval.params.vRng[0], 'iouThr': coco_eval.params.iouThrs[0], 'maxDets': coco_eval.params.maxDets[2], 'areaRng': coco_eval.params.areaRng[0]} return lamr, params