tidied up formatting

Author: Your Name

content/learning-paths/microcontrollers/yolo-on-himax/_index.md

@@ -20,15 +20,14 @@ author_primary: Chaodong Gong, Alex Su, Kieran Hejmadi
 
 ### Tags
 skilllevels: Beginner
-subjects: Object Detection
+subjects: ML
 armips:
     - Cortex M55
     - Ethos U55
 tools_software_languages:
     - Himax SDK
     - bash scripting
 operatingsystems:
-    - Windows
     - Linux
 
 

content/learning-paths/microcontrollers/yolo-on-himax/face_detection.jpg

@@ -8,9 +8,9 @@ layout: learningpathall
 
 ## Set up the development environment
 
-### Step 2.1. Install Ubuntu
+### Step 1.1. Install Ubuntu
 
-Himax SDK needs to be compiled in a Linux environment. If you use a Windows computer, it is recommended to install WSL, by searching Ubuntu 22.04.3 LTS in Microsoft store. This learning path has been validated on Ubuntu 22.04 LTS. However, we expect other linux distributions to work. To verify the Linux distribution you are using you can run the `cat /etc/*release*` command. 
+This learning path has been tested on Ubuntu. If you use a Windows computer, it is recommended to install WSL, by searching Ubuntu 22.04.3 LTS in Microsoft store. This learning path has been validated on Ubuntu 22.04 LTS. However, we expect other linux distributions to work. To verify the Linux distribution you are using you can run the `cat /etc/*release*` command. 
 
 ```bash
 cat /etc/*release*
@@ -25,11 +25,11 @@ DISTRIB_DESCRIPTION="Ubuntu 22.04.5 LTS"
 ...
 ```
 
-### Step 2.2. (Optional) Install Microsoft VS Code
+### Step 1.2. (Optional) Install Microsoft VS Code
 
 This is only optional. You can use any text editor to view/change code. By typing “wsl” in VS Code terminal, you can switch to Linux environment.
 
-### Step 2.3. Install python 3
+### Step 1.3. Install python 3
 
 Go to website python.org to download and install.
 Verify python is installed by
@@ -38,7 +38,7 @@ You should see an output like the following.
 ```output
 Python 3.12.7
 ```
-### Step 2.4. Install python-pip
+### Step 1.4. Install python-pip
 
 ```bash
 sudo apt update
@@ -52,7 +52,7 @@ If `pip3` is correctly installed you should see an output similar to tht followi
 pip 24.2 from <path to pip3>/pip (python 3.12)
 ```
 
-### Step 2.5. Install make
+### Step 1.5. Install make
 
 You will need to install the make build tool in order to build the firmware in the following section.
 
@@ -73,7 +73,7 @@ This is free software: you are free to change and redistribute it.
 There is NO WARRANTY, to the extent permitted by law.
 ```
 
-### Step 2.6. Install ARM GNU toolchain
+### Step 1.6. Install ARM GNU toolchain
 
 ```bash
 cd ~

content/learning-paths/microcontrollers/yolo-on-himax/how-to-1.md

@@ -22,7 +22,7 @@ git version 2.39.3
 
 If not, please follow the steps to install git on your system.
 
-### Step 3.1. Clone the project
+### Step 2.1. Clone the Himax project
 
 You will first need to recusively clone the Himax repository. This will also clone the necessary sub repos such as Arm CMSIS. 
 
@@ -31,7 +31,7 @@ git clone --recursive https://github.com/HimaxWiseEyePlus/Seeed_Grove_Vision_AI_
 cd Seeed_Grove_Vision_AI_Module_V2
 ```
 
-### Step 3.2. Compile the firmware
+### Step 2.2. Compile the firmware
 
 The make build tool is used to compile the source code. This should take up around 2-3 minutes depending on the number of CPU cores available.
 
@@ -42,7 +42,7 @@ make
 ```
 
 
-### Step 3.3. Generate firmware image file
+### Step 2.3. Generate firmware image file
 
 ```bash
 cd ../we2_image_gen_local/

content/learning-paths/microcontrollers/yolo-on-himax/how-to-2.md

@@ -8,20 +8,17 @@ layout: learningpathall
 
 ## Flash The Firmware
 
-### Step 4.1. Install xmodem.
+### Step 3.1. Install xmodem.
 
-Change the directory
-```bash
-cd $HOME/Seeed_Grove_Vision_AI_Module_V2 # If you cloned the repo to a different location replace $HOME with the path. 
-```
 
 `Xmodem` is a basic file transfer protocol. Run the following command to install the dependencies for xmodem. 
 
-```python
+```bash
+cd $HOME/Seeed_Grove_Vision_AI_Module_V2 # If you cloned the repo to a different location replace $HOME with the path. 
 pip install -r xmodem/requirements.txt
 ```
 
-### Step 4.2. Connect the module to PC by USB cable.
+### Step 3.2. Connect the module to PC by USB cable.
 
 You will need to insert the FPC cable cable into the Grove Vision AI V2 module. Lift the dark grey latch on the connector as per the image below.
 
@@ -33,7 +30,7 @@ Then, slide the FPC connector in with the metal pins facing down and close the d
 
 Then connect the Groove Vision AI V2 Module to your computer via USB-C.
 
-### Step 4.4. Flash the firmware by the following commands:
+### Step 3.4. Flash the firmware by the following commands:
 
 ```python
 python xmodem\xmodem_send.py --port=[your COM number] --baudrate=921600 --protocol=xmodem --file=we2_image_gen_local\output_case1_sec_wlcsp\output.img 

content/learning-paths/microcontrollers/yolo-on-himax/how-to-3.md

@@ -7,21 +7,19 @@ layout: learningpathall
 ---
 
 
-### Step 5.1. Close the terminal session.
+### Step 4.1. Connect module to PC with USB cable.
 
-### Step 5.2. Connect module to PC with USB cable.
+Exit the terminal session and connect the module to the PC via your USB-C cable. 
 
-
-
-### Step 5.3. Download the Himax AI web toolkit.  
+### Step 4.2. Download the Himax AI web toolkit.  
 
 The Himax AI web toolkit enables a browser-based graphical user interface (GUI) where the live camera feed can be displayed. 
 
 Download the Himax AI Web toolkit by clicking on this [link](https://github.com/HimaxWiseEyePlus/Seeed_Grove_Vision_AI_Module_V2/releases/download/v1.1/Himax_AI_web_toolkit.zip)
 
 Unzip the archived file and double click `index.html.`. This will open the GUI within your default browser.
 
-### Step 5.4. Connect to the Grove Vision AI
+### Step 4.3. Connect to the Grove Vision AI
 
 Select 'Grove Vision AI(V2)` in the top-right hand corner and press connect button. 
 

content/learning-paths/microcontrollers/yolo-on-himax/how-to-4.md

@@ -15,16 +15,27 @@ Change the directory to the where the makefile is located.
 cd $HOME/Seeed_Grove_Vision_AI_Module_V2/EPII_CM55M_APP_S/ # replace $HOME with the location of the project
 ```
 
-Using a text editor, for example visual studio code or nano, modify the `APP_TYPE` field in the makefile from the default value of `allon_sensor_tflm` to one of the following. 
+Using a text editor, for example visual studio code or nano, modify the `APP_TYPE` field in the makefile from the default value of `allon_sensor_tflm` to one of the values in the table below 
 
 
-|Parameter|Description|
+|APP_TYPE =|Description|
 |---|---|
 |tflm_folov8_od|Object detection|
 |tflm_folov8_pose|Pose detection|
 |tflm_fd_fm|Face detection|
 
+### Regenerate the Firmware Image
+
 Go back to the 'Build The Firmware' section and start from Step 3.2. to regenerate the firmware image. 
 
 The images below are examples images from the model. 
 
+#### Objection Detection
+![object_detection](./object_detection.jpg)
+
+#### Pose Estimation
+![Pose estimation](./pose_estimation.jpg)
+
+#### Face Detection
+![object_detection](./face_detection.jpg)
+