Update web-toolkit.md

- Additional use-cases verified
- Misc minor updates
- Remove _review.md

Author: annietllnd

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

@@ -31,9 +31,9 @@ operatingsystems:
     - Linux
     - macOS
 
-#draft: true
-#cascade:
-#    draft: true
+draft: true
+cascade:
+    draft: true
 
 
 ### FIXED, DO NOT MODIFY

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

@@ -34,24 +34,24 @@ make
 
 ## Generate the firmware image
 
-Copy the `.elf` file to the `input_case1_secboot` directory.
+The examples repository contains scripts to generate the image file. Copy the `.elf` file to the `input_case1_secboot` directory.
 
 ```bash
 cd ../we2_image_gen_local/
 cp ../EPII_CM55M_APP_S/obj_epii_evb_icv30_bdv10/gnu_epii_evb_WLCSP65/EPII_CM55M_gnu_epii_evb_WLCSP65_s.elf input_case1_secboot/
 ```
-The examples repository contains scripts to generate the image. Run the script corresponding to the OS of your host machine.
 
-### Linux
+Run the script corresponding to the OS of your host machine. This will create a file named `output.img` in the `output_case1_sec_wlcsp` directory.
 
-```bash
-./we2_local_image_gen project_case1_blp_wlcsp.json
-```
 
-### macOS
-```console
+{{< tabpane code=true >}}
+  {{< tab header="Linux" language="shell">}}
+./we2_local_image_gen project_case1_blp_wlcsp.json
+  {{< /tab >}}
+  {{< tab header="MacOS" language="shell">}}
 ./we2_local_image_gen_macOS_arm64 project_case1_blp_wlcsp.json
-```
+  {{< /tab >}}
+{{< /tabpane >}}
 
 Your terminal output should end with the following.
 

content/learning-paths/microcontrollers/yolo-on-himax/build-firmware.md

@@ -67,18 +67,15 @@ git version 2.39.3
 
 Install the make build tool, which is used to build the firmware in the next section.
 
-### Linux
-
-```bash
+{{< tabpane code=true >}}
+  {{< tab header="Linux" language="shell">}}
 sudo apt update
 sudo apt install make -y
-```
-
-### macOS
-
-```console
+  {{< /tab >}}
+  {{< tab header="MacOS" language="shell">}}
 brew install make
-```
+  {{< /tab >}}
+{{< /tabpane >}}
 
 Successful installation of make will show the following when the `make --version` command is run.
 
@@ -96,26 +93,25 @@ To run this learning path on macOS, you need to verify that your installation is
 {{% /notice %}}
 ## Install Arm GNU toolchain
 
-### Linux
-
-The toolchain is used to cross-compile from the host architecture (x86) to the embedded device architecture (AArch64).
+The toolchain is used to compile code from the host to the embedded device architecture.
 
-```bash
+{{< tabpane code=true >}}
+  {{< tab header="Linux" language="shell">}}
 cd $HOME
 wget https://developer.arm.com/-/media/Files/downloads/gnu/13.2.rel1/binrel/arm-gnu-toolchain-13.2.rel1-x86_64-arm-none-eabi.tar.xz
 tar -xvf arm-gnu-toolchain-13.2.rel1-x86_64-arm-none-eabi.tar.xz
 export PATH="$HOME/arm-gnu-toolchain-13.2.Rel1-x86_64-arm-none-eabi/bin/:$PATH"
-```
-### macOS
-```console
+  {{< /tab >}}
+  {{< tab header="MacOS" language="shell">}}
 cd $HOME
 wget https://developer.arm.com/-/media/Files/downloads/gnu/13.3.rel1/binrel/arm-gnu-toolchain-13.3.rel1-darwin-arm64-arm-none-eabi.tar.xz
 tar -xvf arm-gnu-toolchain-13.3.rel1-darwin-arm64-arm-none-eabi.tar.xz
 export PATH="$HOME/arm-gnu-toolchain-13.3.rel1-darwin-arm64-arm-none-eabi/bin/:$PATH"
-```
+  {{< /tab >}}
+{{< /tabpane >}}
 
 {{% notice %}}
-You can add the above command to the `.bashrc` file. This was, the Arm GNU toolchain is configured from new terminal sessions as well.
+You can add the `export` command to the `.bashrc` file. This was, the Arm GNU toolchain is configured from new terminal sessions as well.
 {{% /notice %}}
 
 

content/learning-paths/microcontrollers/yolo-on-himax/dev-env.md

@@ -19,15 +19,15 @@ pip install -r xmodem/requirements.txt
 
 ## Connect the module
 
-Insert the Flexible printed circuit (FPC) into the Grove Vision AI V2 module. Lift the dark grey latch on the connector as per the image below.
+To prepare for the next steps, it's time to get the board set up. Insert the Flexible printed circuit (FPC) into the Grove Vision AI V2 module. Lift the dark grey latch on the connector as per the image below.
 
 ![unlatched](./unlatched.jpg)
 
 Then, slide the FPC connector in with the metal pins facing down and close the dark grey latch to fasten the connector.
 
 ![latched](./latched.jpg)
 
-Then connect the Groove Vision AI V2 Module to your computer via the USB-C cable.
+Now you can connect the Groove Vision AI V2 Module to your computer via the USB-C cable.
 
 {{% notice Note %}}
 The development board may have two USB-C connectors. If you are running into issues connecting the board in the next step, make sure you are using the right one.
@@ -37,17 +37,16 @@ The development board may have two USB-C connectors. If you are running into iss
 
 You'll need to provide the communication port (COM) which the board is connected to in order to flash the image. There are commands to list all COMs available on your machine. Once your board is connected through USB, it'll show up in this list. The COM identifier will start with **tty**, which may help you determine which one it is. You can run the command before and after plugging in the board if you are unsure.
 
-### Linux
 
-```bash
+{{< tabpane code=true >}}
+  {{< tab header="Linux" language="shell">}}
 sudo grep -i 'tty' /var/log/dmesg
-```
-
-### MacOS
-
-```console
+  {{< /tab >}}
+  {{< tab header="MacOS" language="shell">}}
 ls /dev/tty.*
-```
+  {{< /tab >}}
+{{< /tabpane >}}
+
 
 {{% notice Note %}}
 If the port seems unavailable, try changing the permissions temporarily using the `chmod` command. Be sure to reset them afterwards, as this may pose a computer security vulnerability.
@@ -64,11 +63,13 @@ The full path to the port is needed in the next step, so be sure to note it down
 Run the python script below to flash the firmware.
 
 ```bash
-python xmodem\xmodem_send.py --port=<COM port> --baudrate=921600 --protocol=xmodem --file=we2_image_gen_local\output_case1_sec_wlcsp\output.img
+python xmodem\xmodem_send.py --port=<COM port> \
+--baudrate=921600 --protocol=xmodem \
+--file=we2_image_gen_local\output_case1_sec_wlcsp\output.img
 ```
 
 {{% notice Note %}}
-When you run other example models demonstrated in the later section [Object detection and additional models](/learning-paths/microcontrollers/yolo-on-himax/how-to-5/), you need to adapt this command with the right image file.
+When you run other example models demonstrated in the later section [Run additional models in the web toolkit](/learning-paths/microcontrollers/yolo-on-himax/web-toolkit/), you need to adapt this command with `--model` argument.
 {{% /notice %}}
 
 After the firmware image burning is completed, the message `Do you want to end file transmission and reboot system? (y)` is displayed. Press the reset button indicated in the image below.

content/learning-paths/microcontrollers/yolo-on-himax/flash-and-run.md

@@ -1,14 +1,12 @@
 ---
-title: (optional) Run additional models in the web toolkit
+title: Run additional models in the web toolkit
 weight: 6
 
-#draft: true
-
 ### FIXED, DO NOT MODIFY
 layout: learningpathall
 ---
 
-In this section, you will view a live camera feed with the ML application running.
+In this section, you will view a live camera feed with a computer vision application running.
 
 ## Modify the Makefile
 
@@ -18,12 +16,11 @@ Change the directory to the where the Makefile is located. If you cloned the rep
 cd $HOME/Seeed_Grove_Vision_AI_Module_V2/EPII_CM55M_APP_S/
 ```
 
-The table shows the different options available to use with the web toolkit. Modify the `APP_TYPE` field in the `makefile` to one of the values in the table. Then, to the xmodem argument, pass the `--model` argument.
+The table shows the different options available to use with the web toolkit. Modify the `APP_TYPE` field in the `makefile` to one of the values in the table. Then pass the `--model` argument to the python `xmodem` command.
 
-|APP_TYPE           |Description        | --model argument |
+|APP_TYPE           |Description        | Model argument |
 |---                |---                |---
 |tflm_yolov8_od     |Object detection   | model_zoo\tflm_yolov8_od\yolov8n_od_192_delete_transpose_0xB7B000.tflite 0xB7B000 0x00000 |
-|tflm_yolov8_pose   |Pose detection     | model_zoo\tflm_yolov8_pose\yolov8n_pose_256_vela_3_9_0x3BB000.tflite 0x3BB000 0x00000 |
 |tflm_fd_fm         |Face detection     | model_zoo\tflm_fd_fm\0_fd_0x200000.tflite 0x200000 0x00000 model_zoo\tflm_fd_fm\1_fm_0x280000.tflite 0x280000 0x00000 model_zoo\tflm_fd_fm\2_il_0x32A000.tflite 0x32A000 0x00000 |
 
 {{% notice Note %}}
@@ -47,17 +44,17 @@ Use the commands from [Flash firmware onto the microcontroller](/learning-paths/
 cd ../we2_image_gen_local/
 cp ../EPII_CM55M_APP_S/obj_epii_evb_icv30_bdv10/gnu_epii_evb_WLCSP65/EPII_CM55M_gnu_epii_evb_WLCSP65_s.elf input_case1_secboot/
 ```
+Run the script corresponding to the OS of your host machine.
 
-### Linux
-
-```bash
+{{< tabpane code=true >}}
+  {{< tab header="Linux" language="shell">}}
 ./we2_local_image_gen project_case1_blp_wlcsp.json
-```
-
-### macOS
-```console
+  {{< /tab >}}
+  {{< tab header="MacOS" language="shell">}}
 ./we2_local_image_gen_macOS_arm64 project_case1_blp_wlcsp.json
-```
+  {{< /tab >}}
+{{< /tabpane >}}
+
 
 Finally, use `xmodem` to flash the image.
 
@@ -92,9 +89,6 @@ The images below are captured images from the models run in the toolkit.
 ### Objection detection
 ![object_detection](./object_detection.jpg)
 
-### Pose estimation
-![Pose estimation](./pose_estimation.jpg)
-
 ### Face detection
 ![object_detection](./face_detection.jpg)