Merge branch 'main' of https://github.com/AndreasKaratzas/orin

README.md

@@ -1,5 +1,5 @@
 
-# Orin
+# Setting up the NVIDIA Jetson Orin Nano
 
 This tutorial was written for the NVIDIA Jetson Orin Nano Developer Kit (8 GB). The tutorial was written on `2024-2-13:19-42-5`. Details of the board are:
 
@@ -24,19 +24,21 @@ This tutorial was written for the NVIDIA Jetson Orin Nano Developer Kit (8 GB).
 | VPI | 3.0.10 |
 | Vulkan | 1.3.204 |
 
-__IMPORTANT WARNING__ : To flash the board, the host must be running on __Ubuntu 20.04__. 
+__IMPORTANT WARNING__: The host must be running on __Ubuntu 20.04__ to flash the board. 
 
 
 ### Flashing the Board
 
-The board can be flashed using the SDK Manager. The SDK Manager can be downloaded from the [NVIDIA website](https://developer.nvidia.com/nvidia-sdk-manager). To flash the board, force the board in recovery mode by following the steps in [https://www.youtube.com/watch?v=q4fGac-nrTI&t=218s](JetsonHacks Tutorial). Then, select the following options:
+
+The board can be flashed using the SDK Manager. The SDK Manager can be downloaded from the [NVIDIA website](https://developer.nvidia.com/nvidia-sdk-manager). To flash the board, force the board into recovery mode by following the steps in [JetsonHacks Tutorial](https://www.youtube.com/watch?v=q4fGac-nrTI&t=218s). Then, select the following options:
 
 - Host Machine: Ubuntu 20.04
 - Target Hardware: Jetson Orin Nano Developer Kit 8 GB
 - Target OS: Jetpack 6.0 DP
 - DeepStream: 6.0
 
-In my case, I had already mounted a `NVME SSD` as a storage component. Most tutorials do SD cards, but for performance reasons, I went with an mainstream 1 TB NVME SSD. Select the `pre-config` option to setup the board and initialize with a username and a password. For simplicity, the username and password are set to `nvidia`. The board will be flashed and the board will be ready to use.
+In my case, I had already mounted an `NVME SSD` as a storage component. Most tutorials do SD cards, but I went with a mainstream 1 TB NVME SSD for performance reasons. Select the `pre-config` option to set the board and initialize it with a username and a password. For simplicity, the username and password are set to `nvidia`. The board will be flashed, and it will be ready to use.
+
 
 ### Setting up the Board
 
@@ -63,6 +65,7 @@ chmod +x Miniconda3-latest-Linux-aarch64.sh
 ./Miniconda3-latest-Linux-aarch64.sh
 ```
 
+
 ### Checking CUDA and cuDNN
 
 Before we advance on checking CUDA and cuDNN, we need to verify `gcc` and `nvidia-smi`:
@@ -90,14 +93,37 @@ make clean && make
 ./mnistCUDNN
 ```
 
-### Monitoring the Board
 
+### Monitoring the Board
 
 To monitor the board, we will install `jetson-stats`:
 ```bash
 sudo pip3 install -U jetson-stats
 ```
 
+To check your board details and version of different software using `jtop`, as well as the usage across its computing resources and power consumption, there are some Python scripts that use `jtop`. For example [`jtop_properties.py`](https://github.com/rbonghi/jetson_stats/blob/master/examples/jtop_properties.py) is a quick way to monitor the aforementioned.
+
+
+### VS Code
+
+If you are a Visual Studio Code user, it is supported on the Jetson. Run the following commands:
+
+```bash
+cd Downloads/
+wget -qO- https://packages.microsoft.com/keys/microsoft.asc | gpg --dearmor > packages.microsoft.gpg
+sudo install -o root -g root -m 644 packages.microsoft.gpg /etc/apt/trusted.gpg.d/
+sudo sh -c 'echo "deb [arch=amd64,arm64,armhf signed-by=/etc/apt/trusted.gpg.d/packages.microsoft.gpg] https://packages.microsoft.com/repos/code stable main" > /etc/apt/sources.list.d/vscode.list'
+rm -f packages.microsoft.gpg
+sudo apt install apt-transport-https
+sudo apt update
+sudo apt install code
+```
+
+
+### Case
+
+For my board, I bought the [Yahboom CUBE nano case](https://www.amazon.com/Yahboom-Dissipation-Protect-Cooling-Antenna/dp/B0CD71X8SV). On [their page](http://www.yahboom.net/study/CUBE_NANO), there are also [tutorials](https://youtu.be/anbMcWsagn8) and [code](https://drive.google.com/drive/folders/1A4L1ec-Na1_K0K1LXdnzSCva2iZ02YVX) for setting up the case and configuring the OLED screen that comes with it. Finally, there is also a [GitHub repo](https://github.com/YahboomTechnology/Jetson-CUBE-case) associated with the case.
+
 
 ### Install PyTorch