Update images

tutorials/source_en/advanced_use/on_device_inference.md

@@ -17,7 +17,7 @@
 
 MindSpore Lite is a lightweight deep neural network inference engine that provides the inference function for models trained by MindSpore on the device side. This tutorial describes how to use and compile MindSpore Lite.
 
-![](./images/on_device_inference_frame.png)
+![](./images/on_device_inference_frame.jpg)
 
 Figure 1 On-device inference frame diagram
 
@@ -173,7 +173,7 @@ To perform on-device model inference using MindSpore, perform the following step
 
 Use the `.ms` model file and image data as input to create a session and implement inference on the device.
 
-![](./images/side_infer_process.png)
+![](./images/side_infer_process.jpg)
 
 1. Load the `.ms` model file to the memory buffer. The ReadFile function needs to be implemented by users, according to the [C++ tutorial](http://www.cplusplus.com/doc/tutorial/files/).
    ```cpp

tutorials/source_zh_cn/advanced_use/on_device_inference.md

@@ -17,7 +17,7 @@
 
 MindSpore Lite是一个轻量级的深度神经网络推理引擎，提供了将MindSpore训练出的模型在端侧进行推理的功能。本教程介绍MindSpore Lite的编译方法和使用指南。
 
-![](./images/on_device_inference_frame.png)
+![](./images/on_device_inference_frame.jpg)
 
 图1：端侧推理架构图
 
@@ -173,7 +173,7 @@ MindSpore进行端侧模型推理的步骤如下。
 
 将`.ms`模型文件和图片数据作为输入，创建`session`在端侧实现推理。
 
-![](./images/side_infer_process.png)
+![](./images/side_infer_process.jpg)
 
 图2：端侧推理时序图