Xbox 360 v1 Camera

Setting up the Xbox 360 v1 Camera on Jetson Nano with Ubuntu

Overview

In this tutorial, we will cover the steps to set up the Xbox 360 v1 camera on a Nvidia Jetson Nano running Ubuntu. This camera can be used for various applications such as computer vision and machine learning.

Requirements

• Nvidia Jetson Nano with Ubuntu installed
• USB 2.0 cable (for connecting the Xbox 360 v1 camera to the Jetson Nano)
• Xbox 360 v1 camera

Steps

1. Connect the Xbox 360 v1 camera to the Jetson Nano using a USB 2.0 cable.
2. Open a terminal window on the Jetson Nano by clicking on the top-left corner of the screen and selecting “Terminal”.
3. Update the package lists by running the following command:

   sudo apt update
   

4. Install libuvc, which is required to communicate with the Xbox 360 v1 camera:

   sudo apt install libuvc-dev
   

5. Reboot the Jetson Nano by running the following command:

   sudo reboot
   

6. After the reboot, open a new terminal window and run the following command to verify that the Xbox 360 v1 camera is recognized by the system:

   ls /dev/video*
   

   You should see an output similar to this:

   /dev/video0
   

7. Run the following command to test the camera feed in VLC media player:

   vlc v4l2:// :v4l-vbi-fmt=none :v4l-chroma=h264 :v4l-chroma-cap=0 :v4l-fps=30 :v4l-input=1 :v4l-std=pal :v4l-frequency=525 :live-caching=300
   

8. If the camera feed is working correctly, you can proceed to develop your computer vision or machine learning applications using libraries like OpenCV.

Conclusion

In this tutorial, we covered the steps to set up the Xbox 360 v1 camera on a Nvidia Jetson Nano running Ubuntu. By following these steps, you should be able to use the camera for various applications such as computer vision and machine learning.

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Download and Install Python 3.8 on Nvidia Jetson Nano

Install Dependencies

Before we begin, let’s make sure the system has the necessary tools and libraries. Open a terminal on your Nvidia Jetson Nano and run the following commands:

sudo apt update
sudo apt install -y build-essential libssl-dev libffi-dev python3.8-dev

• sudo apt update: Updates the package lists on your system.
• sudo apt install -y build-essential libssl-dev libffi-dev python3.8-dev: Installs essential build tools and libraries required for Python compilation.

Download and Install Python 3.8

Now, let’s download and install Python 3.8. In the same terminal, execute the following commands:

wget https://www.python.org/ftp/python/3.8.12/Python-3.8.12.tgz
tar xvf Python-3.8.12.tgz
cd Python-3.8.12
./configure --enable-optimizations
make -j4
sudo make altinstall

• wget https://www.python.org/ftp/python/3.8.12/Python-3.8.12.tgz: Downloads the Python 3.8 source code archive.
• tar xvf Python-3.8.12.tgz: Extracts the contents of the archive.
• cd Python-3.8.12: Navigates into the extracted directory.
• ./configure --enable-optimizations: Configures the Python build with optimizations.
• make -j4: Compiles Python. The -j4 flag specifies the number of parallel processes (adjust as needed).
• sudo make altinstall: Installs Python with a version-specific executable (python3.8).

These commands download, configure, compile, and install Python 3.8 on your Nvidia Jetson Nano. This version is installed alongside the default Python versions and does not replace them.

Install Python 3.8 and Pip on Nvidia Jetson Nano

1. Download get-pip.py Script

Download the get-pip.py script using wget:

wget https://bootstrap.pypa.io/get-pip.py

2. Install Python 3.8 and Pip

Use the following command to install Python 3.8 and Pip:

python3 get-pip.py --prefix=/usr/local/python3.8

3. Update Bash Configuration

Open the .bashrc file for editing:

sudo nano ~/.bashrc

Add the following line to the bottom of the file:

export PATH="/usr/local/python3.8/bin:$PATH"

Save the file and apply the changes:

source ~/.bashrc

4. Verify Installation

Check the Python and Pip versions to ensure successful installation:

python3.8 --version
pip3.8 --version

These commands download and install Python 3.8 along with Pip on your Nvidia Jetson Nano. The .bashrc update ensures that the new Python version is available in your system’s PATH. Verify the installation by checking the versions of Python and Pip.

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5. Download OpenCV: Download OpenCV from its official website (https://opencv.org/releases/) and install it using the following command:

   sudo apt-get install libopencv-dev python-opencv
   

6. Download Numpy: Download Numpy from its official website (https://numpy.org/install/) and install it using pip:

   pip install numpy
   

7. Download Pycuda: Download Pycuda from its official website (https://pypi.org/project/pycuda/) and install it using the following command:

   sudo apt-get install python3-dev libcupti-dev libcupti-dev-common libnvvm-dev libnvvm3 libnvvm3-dev libnvvm3-bin libnvvm3-dev-common libnvvm3-bin-common libnvvm3-dev-doc libnvvm3-dev-doc-common cuda-nvcc cuda-command-line-tools-10-2 cuda-libraries-10-2 cuda-libraries-dev-10-2
   

8. Download CUDA: Download CUDA from its official website (https://developer.nvidia.com/cuda-downloads) and install it using the following command:

   sudo dpkg -i cuda-repo-ubuntu1804-10-2-local_10.2.89-1_amd64.deb
   sudo apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub
   sudo apt-get update
   sudo apt-get install cuda
   

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2. Clone the GitHub Repository: Use the following command to clone the repository:

   git clone https://github.com/raymondlo84/nvidia-jetson-ai-monitor
   

3. Navigate to the Cloned Directory: After cloning, use the cd command to navigate to the directory.

4. Install Dependencies: Use pip to install the necessary dependencies:

   pip install -r requirements.txt
   

5. Run the Script: To run the script, use the following command:

   python main.py
   

6. Configure the Script: The script has a configuration file named config.py. You can modify this file to configure various aspects of the script such as the frequency at which the script checks for GPU usage, CPU temperature, and other metrics.

7. Check the Output: Once you have run the script, it will start monitoring your NVIDIA Jetson Nano’s GPU usage, CPU temperature, and other metrics. The output can be viewed in the console or redirected to a file for later analysis.