--- a
+++ b/metrics/meansensitivity.py
@@ -0,0 +1,38 @@
+import torch
+import numpy as np
+
+
+def get_sensitivity(SR, GT, threshold=0.5):
+    """
+    cal each img sensitivity
+    """
+    # Sensitivity == Recall
+    SR = SR > threshold
+    GT = GT == torch.max(GT)
+
+    # TP : True Positive
+    # FN : False Negative
+    TP = ((SR == 1) + (GT == 1)) == 2
+    FN = ((SR == 0) + (GT == 1)) == 2
+
+    SE = float(torch.sum(TP)) / (float(torch.sum(TP + FN)) + 1e-6)
+
+    return SE
+
+
+def meansensitivity_seg(pred, gt, sens):
+    """
+    :return save img' sensitivity values in sens
+    """
+    gt_tensor = gt
+    gt_tensor = gt_tensor.cpu()
+    pred[pred < 0.5] = 0
+    pred[pred >= 0.5] = 1
+    pred = pred.type(torch.LongTensor)
+    # TO CPU
+    # pred_np = pred.data.cpu().numpy()
+    # gt = gt.data.cpu().numpy()
+    for x in range(pred.size()[0]):
+        sen = get_sensitivity(pred[x], gt_tensor[x])
+        sens.append(sen)
+    return sens
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