--- a
+++ b/metrics/meandice.py
@@ -0,0 +1,20 @@
+import numpy as np
+import torch
+
+
+def meandice(pred, gt, dices):
+    """
+    :return save img' dice value in IoUs
+    """
+    # dices = []
+    pred[pred < 0.5] = 0
+    pred[pred >= 0.5] = 1
+    gt[gt < 0.5] = 0
+    gt[gt >= 0.5] = 1
+    pred = pred.type(torch.LongTensor)
+    pred_np = pred.data.cpu().numpy()
+    gt = gt.data.cpu().numpy()
+    for x in range(pred.size()[0]):
+        dice = np.sum(pred_np[x][gt[x] == 1]) * 2 / float(np.sum(pred_np[x]) + np.sum(gt[x]))
+        dices.append(dice)
+    return dices