def _get_perfect_scoremap(self, image_id, ignore_score):
mask = get_mask(self._MASK_ROOT, self._MASK_PATHS[image_id],
self._IGNORE_PATHS[image_id])
ignore_region = mask == 255
scoremap = mask.astype(np.float)
scoremap[ignore_region] = ignore_score
return scoremap
def _get_constant_scoremap(self, image_id, value):
mask = get_mask(self._MASK_ROOT, self._MASK_PATHS[image_id],
self._IGNORE_PATHS[image_id])
scoremap = np.ones_like(mask).astype(np.float)
return scoremap * value
import os
import evaluation
gt_dir = "/home/taylor/SemirNet/data/test/mask"
# predict_dir = "/home/taylor/SemirNet/data/test/dsc_results"
predict_dir = "/home/taylor/SemirNet/ckpt/BDRAR/(BDRAR)sbu_prediction_3001"
IOU = []
ACC_all = []
ACC_mirror = []
BER = []
masklist = os.listdir(gt_dir)
for i, maskname in enumerate(masklist):
print(i, maskname)
gt = evaluation.get_mask(maskname, gt_dir)
predict = evaluation.get_predict_mask(maskname, predict_dir)
iou = evaluation.iou(predict, gt)
acc_all = evaluation.accuracy_all(predict, gt)
acc_mirror = evaluation.accuracy_mirror(predict, gt)
ber = evaluation.ber(predict, gt)
print("iou : {}".format(iou))
print("acc : {}".format(acc_all))
print("acc : {}".format(acc_mirror))
print("ber : {}".format(ber))
IOU.append(iou)
ACC_all.append(acc_all)
ACC_mirror.append(acc_mirror)
BER.append(ber)