diff --git a/ACL_TensorFlow/built-in/cv/Facenet_for_ACL/README.md b/ACL_TensorFlow/built-in/cv/Facenet_for_ACL/README.md
index 068560664a5deab6fd3d45bfb26026e81a2e5baa..4b581197385b3ff6f90f2d11107275d2ccf33b53 100644
--- a/ACL_TensorFlow/built-in/cv/Facenet_for_ACL/README.md
+++ b/ACL_TensorFlow/built-in/cv/Facenet_for_ACL/README.md
@@ -35,6 +35,74 @@ cd Modelzoo-TensorFlow/ACL_TensorFlow/built-in/cv/Facenet_for_ACL
    
    ```
 
+
+原始pb模型修改输入适配：
+
+github链接中原始的pb模型，输入int型batchsize和bool型phase_train来控制模型走训练还是推理分支，以及batch,通过FIFO队列来读取文件，组装后送到模型中推理pb包含训练bn和dropout分支对推理场景没用，所以裁剪模型如下：
+
+phase_train改为const类型，固定值为false,删除前面的FIFO节点，改造input节点为placeholder,接受输入数据，其他不变。
+具体操作如下：
+
+1.使用pb转pbtxt脚本
+python3 pb_to_pbtxt.py 20180408-102900.pb
+
+2.将protobuf.pbtxt编辑：
+
+1.删除第一个节点batch_size
+
+2.第二个节点phase_train的op修改为const
+
+3.删除第三个节点batch_join/fifo_queue
+
+4.删除第四个节点batch_join
+
+5.删除第五个节点image_batch
+
+6.修改input节点为:
+
+node {
+  name: "input"
+  op: "Placeholder"
+  attr {
+    key: "dtype"
+    value {
+      type: DT_FLOAT
+    }
+  }
+  attr {
+    key: "shape"
+    value {
+      shape {
+        dim {
+          size: -1
+        }
+        dim {
+          size: 160
+        }
+        dim {
+          size: 160
+        }
+        dim {
+          size: 3
+        }
+      }
+    }
+  }
+}
+
+7.删除第七个节点 label_batch
+
+
+3.保存后转为pb模型
+
+python3 pb_to_pbtxt.py protobuf.pbtxt
+
+修改模型名字 mv protobuf.pb facenet_tf.pb
+
+
+
+
+
  
 ### 3. 离线推理
 
diff --git a/ACL_TensorFlow/built-in/cv/Facenet_for_ACL/pb_to_pbtxt.py b/ACL_TensorFlow/built-in/cv/Facenet_for_ACL/pb_to_pbtxt.py
new file mode 100644
index 0000000000000000000000000000000000000000..81e3ff5d61f4546a547f41025baa57b0b71b02bb
--- /dev/null
+++ b/ACL_TensorFlow/built-in/cv/Facenet_for_ACL/pb_to_pbtxt.py
@@ -0,0 +1,27 @@
+import tensorflow as tf
+from tensorflow.python.platform import gfile
+from google.protobuf import text_format
+import sys
+
+def convert_pb_to_pbtxt(filename):
+    with gfile.FastGFile(filename, 'rb') as f:
+        graph_def = tf.GraphDef()
+        graph_def.ParseFromString(f.read())
+        tf.import_graph_def(graph_def, name='')
+        tf.train.write_graph(graph_def, './', 'protobuf.pbtxt', as_text=True)
+
+def convert_pbtxt_to_pb(filename):
+    with tf.gfile.FastGFile(filename, 'r') as f:
+        graph_def = tf.GraphDef()
+        file_content = f.read()
+        # Merges the human-readable string in `file_content` into `graph_def`.
+        text_format.Merge(file_content, graph_def)
+        tf.train.write_graph(graph_def, './', 'protobuf.pb', as_text=False)
+
+filepath = sys.argv[1]
+if filepath.endswith(".pbtxt"):
+    convert_pbtxt_to_pb(filepath)
+elif filepath.endswith(".pb"):
+    convert_pb_to_pbtxt(filepath)
+else:
+    print("Error! Please set the file path of pb or pbtxt!")
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