Update README.md

README.md

@@ -24,23 +24,37 @@ features that cover core deep learning frameworks, basic model libraries, end-to
 components as well as service platforms. For more details, please refer
 to [PaddlePaddle Github](https://github.com/PaddlePaddle/Paddle) for details.
 
-## Running environment and prerequisites
+## Example
+
+We provide 4 use cases in this reposiotry ([ocr](./ocr), [object_classification](./object_classification), [object_detection](./object_detection) and [object_segmentation](./object_segmentation))
+To run the demos in Arm Virtual Hardware context, please follow these 3 steps:
 
-If you haven't configured the environment yet, please run the following command to set up the dependencies for this
-repository.
+#### 1. Set up running environment
 
+When you try to run the demo for the first time, you need to set up the running environment in AVH instance by the following command.
 ```bash
 cd /path/to/Paddle-examples-for-AVH
-bash scripts/config_cmsis_toolbox.sh
-bash scripts/config_tvm.sh
+sudo bash scripts/config_cmsis_toolbox.sh
+sudo bash scripts/config_tvm.sh
 ```
+#### 2. Run the demo
 
-## Example
+You must specify the model name (by parameter `--model`) and the device name (by parameter `--device`) when you run the demo.
+```bash
+cd /path/to/usecase
+bash run_demo.sh --model model_name --device device_name
+```
+Parameter options can be found in the following table. 
+
+| Use Case | Model Name | Device Name| 
+|-------------------------------------------|-------------|------------|
+|object_classification| MobileNetV3<br>PP_LCNet | cortex-m55<br>cortex-m85 |
+|ocr| CH_PPOCRV2_CLS <br> EN_PPOCRV3_REC| cortex-m55<br>cortex-m85 |
+|object_detection| Picodet | cortex-m55<br>cortex-m85 |
+|object_segmentation| PP_HumanSeg | cortex-m55<br>cortex-m85 |
 
-We have divided the repository into several sections based on common tasks in the computer vision field. Please refer to
-the table below for details.
+For example, to run object classfication demo with PP-LCNet model on Arm Cortex-M55 platform, input the following command:
 
-| Task                                      | Model       | Cortex-M55 | Cortex-M85 |
-|-------------------------------------------|-------------|------------|------------|
-| [Classification](./object_classification) | MobileNetV3 | ✅          | ✅          | 
-| [Classification](./object_classification) | PP_LCNet    | ✅          | ✅          | 
+```bash
+bash run_demo.sh --model PP_LCNet --device cortex-m55
+```