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
