--- a
+++ b/drunet/loss.py
@@ -0,0 +1,22 @@
+import tensorflow.keras.backend as K
+import tensorflow.keras as keras
+import tensorflow as tf
+
+
+def dice_loss(y_true, y_pred):
+    def dice_coeff():
+        smooth = 1
+        y_true_f = tf.reshape(y_true, [-1])
+        y_pred_f = tf.reshape(y_pred, [-1])
+        intersection = tf.reduce_mean(y_true_f * y_pred_f)
+        score = (2. * intersection + smooth) / (tf.reduce_mean(y_true_f) + tf.reduce_mean(y_pred_f) + smooth)
+        return score
+
+    return 1 - dice_coeff()
+
+
+def bce_dice_loss(y_true, y_pred):
+    losses = keras.losses.binary_crossentropy(y_true, y_pred) + dice_loss(y_true, y_pred)
+    return losses
+
+