From 3871b5baeae79228c974507226c0e5759f1365fb Mon Sep 17 00:00:00 2001
From: chengchunlei <0510568@163.com>
Date: Mon, 26 Oct 2020 10:07:15 +0800
Subject: [PATCH] update dnmetis/README.md.

---
 dnmetis/README.md | 15 +++++++--------
 1 file changed, 7 insertions(+), 8 deletions(-)

diff --git a/dnmetis/README.md b/dnmetis/README.md
index ca11d01..20558dd 100644
--- a/dnmetis/README.md
+++ b/dnmetis/README.md
@@ -28,19 +28,18 @@ If you want to acknowledge how to generate om from pb，pls download efficientne
 
 ## 3.Start execute the inference:
 
-sh run_efficientnet-b8.sh
-
-or 
-
-python3.7 main.py --model=./model/efficientnet-b8.om --image_size='672,672,3' --inputs='images:0' --outputs='Softmax:0' --precision=fp16
+bash run_inference.sh
 
 
-## 4.ATC offline model generate (optional):
+## 4.Top1 Accuracy of entire Imagenet2012-val Datasets(5w pictures):
+
+![输入图片说明](https://images.gitee.com/uploads/images/2020/0919/010210_5cf496fc_5418572.png "屏幕截图.png")
+
+
+## 5.modify main.py for your own model:
 
 1.download  efficientnet-b8 model(.pb) URL: obs://hwwheel23/efficientnet-b8.pb 
 
 2.atc --model=$MODEL_DIR/efficientnet-b8.pb --framework=3 --input_shape='images:1,672,672,3' --output=$MODEL_DIR/efficientnet-b8 --mode=0 --out_nodes='Softmax:0' --soc_version=Ascend310  --input_fp16_nodes=images --output_type=FP16
 
-## 5.Imagenet2012-val Top1 Accuracy:
 
-![输入图片说明](https://images.gitee.com/uploads/images/2020/0919/010210_5cf496fc_5418572.png "屏幕截图.png")