Merge pull request #1218 from annietllnd/avh_ppocr

Update OCR example on AVH Learning Path

content/learning-paths/microcontrollers/avh_ppocr/end-to-end_workflow.md

@@ -22,16 +22,50 @@ Start by launching the [Arm Virtual Hardware AMI](/install-guides/avh/).
 
 Alternatively, you can also download the Corstone-300 FVP from the [Arm Ecosystem FVP](https://developer.arm.com/downloads/-/arm-ecosystem-fvps) page. For installation instructions see [Arm Ecosystem FVPs](/install-guides/fm_fvp/eco_fvp/).
 
-The code for this [project](https://github.com/ArmDeveloperEcosystem/Paddle-examples-for-AVH/tree/main/OCR-example), is available to download from [ArmDeveloperEcosystem](https://github.com/ArmDeveloperEcosystem/Paddle-examples-for-AVH) GitHub repository as well as [PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR/tree/dygraph/deploy/avh)’s GitHub repository (under the dygraph branch). 
+The code for this [project](https://github.com/ArmDeveloperEcosystem/Paddle-examples-for-AVH/tree/main/OCR-example), is available to download from [ArmDeveloperEcosystem](https://github.com/ArmDeveloperEcosystem/Paddle-examples-for-AVH) GitHub repository as well as [PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR/tree/dygraph/deploy/avh)’s GitHub repository (under the dygraph branch).
 
 Start by cloning the code repository on your running AVH AMI instance:
 
-```console
+```bash
 git clone https://github.com/ArmDeveloperEcosystem/Paddle-examples-for-AVH.git
-cd Paddle-examples-for-AVH/OCR-example/Text-recognition-example
+cd Paddle-examples-for-AVH
+```
+Run the setup scripts.
+```bash
+sudo bash scripts/config_cmsis_toolbox.sh
+sudo bash scripts/config_tvm.sh
+```
+Now you can navigate to the text recognition example directory.
+
+```bash
+cd ./ocr/text_recognition/
 ```
 
-In this directory, there is a script named [run_demo.sh](https://github.com/ArmDeveloperEcosystem/Paddle-examples-for-AVH/blob/main/OCR-example/run_demo.sh) that automates the entire process described in the End-to-end workflow diagram. 
+In this directory, there is a script named [run_demo.sh](https://github.com/ArmDeveloperEcosystem/Paddle-examples-for-AVH/blob/main/OCR-example/run_demo.sh) that automates the entire process described in the End-to-end workflow diagram.
+
+Update the FVP executable name in the `run_demo.sh` script. The `VHT_Platform` should match what is installed in the system. The executable starts with either `VHT_Corstone_SSE` or `FVP_Corstone_SSE`. Check which one is available in the `$PATH` by typing it out and using the Tab key to autocomplete. Then, using a code editor of your choice or `vim`, you can assign the correct executable:
+
+```console
+vim run_demo.sh
+```
+
+The final result should look something like this, with the right option uncommented:
+```
+if [ "$DEVICE" == "cortex-m55" ]; then
+ RUN_DEVICE_NAME="M55"
+# VHT_Platform="FVP_Corstone_SSE-300"
+ VHT_Platform="VHT_Corstone_SSE-300_Ethos-U55"
+ TVM_TARGET="cortex-m55"
+elif [ "$DEVICE" == "cortex-m85" ]; then
+ RUN_DEVICE_NAME="M85"
+# VHT_Platform="FVP_Corstone_SSE-310"
+ VHT_Platform="VHT_Corstone_SSE-310"
+ TVM_TARGET="cortex-m85"
+else
+ echo 'ERROR: --device only support cortex-m55/cortex-m85' >&2
+ exit 1
+fi
+```
 
 The `run_demo.sh` script automatically builds and executes the English text recognition application on the Corstone-300 platform included with Arm Virtual Hardware. Here is a list of steps performed by this script:
 
@@ -43,15 +77,21 @@ The `run_demo.sh` script automatically builds and executes the English text reco
 - Step 6. Run application binary on Corstone-300 FVP included in AVH
 
 Training the model usually takes a lot of time. In step 2, an already trained English text recognition model named [ocr_en.tar](https://paddleocr.bj.bcebos.com/tvm/ocr_en.tar) is used.
- 
-By default, the script uses the image shown below (QBHOUSE) as an example to verify the inference results on the Corstone-300 FVP with Arm Cortex-M55. 
+
+By default, the script uses the image shown below (QBHOUSE) as an example to verify the inference results on the Corstone-300 FVP with Arm Cortex-M55.
 
 ![QBHOUSE#center](./Figure4.png)
 
+Make the script executable with `chmod`.
+
+```bash
+chmod 777 run_demo.sh
+```
+
 You can now run the trained PaddleOCR text recognition model on the Corstone-300 FVP included on the AVH AMI with the following command:
 
 ```console
-./run_demo.sh
+./run_demo.sh --device cortex-m55 --model EN_PPOCRV3_REC
 ```
 
 The output from running the application on the Corstone-300 FVP is shown below: