Add updated environment setup instructions for Raspberry Pi OS Bookworm compatibility

lite/examples/audio_classification/raspberry_pi/README.md

@@ -16,6 +16,73 @@ with Raspberry Pi OS (preferably updated to Buster).
 Raspberry Pi doesn't have a microphone integrated on its board, so you need to
 plug in a USB microphone to record audio.
 
+
+## Setup Environment
+
+To ensure the TensorFlow Lite examples run smoothly on Raspberry Pi OS based on Debian Bookworm (2024 release), setting up a Python virtual environment is crucial. This setup guarantees compatibility with Python 3.9 and effectively manages the dependencies for your examples.
+
+### Install Python 3.9.0
+
+Follow these steps to install Python from source:
+
+1. **Install Build Dependencies**: Begin by updating your system and installing the required packages:
+   ```bash
+   sudo apt update
+   sudo apt install -y build-essential zlib1g-dev libncurses5-dev libgdbm-dev libnss3-dev libssl-dev libreadline-dev libffi-dev wget
+   ```
+
+2. **Compile and Install Python**: Download, extract, and install Python:
+   ```bash
+   wget https://www.python.org/ftp/python/3.9.0/Python-3.9.0.tar.xz
+   tar xf Python-3.9.0.tar.xz
+   cd Python-3.9.0
+   ./configure --enable-optimizations --prefix=/usr
+   make -j $(nproc)
+   sudo make altinstall
+   ```
+
+3. **Verify Python Installation**: Ensure Python 3.9.0 is installed successfully:
+   ```bash
+   python3.9 --version
+   ```
+
+4. **Change Directory**: Move out of the Python source directory:
+   ```bash
+   cd ..
+   ```
+
+### Optional: Cleanup After Installation
+
+To optimize disk space after the Python installation:
+
+1. **Remove Python Source Files**: Next, use `sudo` to  remove the downloaded archive and the extracted Python source directory:
+   ```bash
+   sudo rm -rf Python-3.9.0.tar.xz Python-3.9.0
+   ```
+
+2. **Remove Build Dependencies**: Optionally, uninstall the build dependencies if they are no longer necessary:
+   ```bash
+   sudo apt remove --purge -y build-essential zlib1g-dev libncurses5-dev libgdbm-dev libnss3-dev libssl-dev libreadline-dev libffi-dev wget
+   sudo apt autoremove -y
+   ```
+
+### Virtual Environment Setup
+
+Prepare and activate a virtual environment for the TensorFlow Lite examples:
+
+1. **Create the Environment**: 
+   ```bash
+   python3.9 -m venv /usr/local/venvs/tflite
+   ```
+
+2. **Activate the Environment**: Always reactivate the virtual environment in new sessions:
+   ```bash
+   source /usr/local/venvs/tflite/bin/activate
+   ```
+
+**Note**: Remember to reactivate the `tflite` environment with `/usr/local/venvs/tflite/bin/activate` each time you work on the TensorFlow Lite examples.
+
+
 ## Install the TensorFlow Lite runtime
 
 In this project, all you need from the TensorFlow Lite API is the `Interpreter`

lite/examples/image_classification/raspberry_pi/README.md

@@ -24,6 +24,72 @@ to the Raspberry Pi. It's okay if you're using SSH to access the Pi shell
 attached to the Pi to see the camera stream.
 
 
+## Setup Environment
+
+To ensure the TensorFlow Lite examples run smoothly on Raspberry Pi OS based on Debian Bookworm (2024 release), setting up a Python virtual environment is crucial. This setup guarantees compatibility with Python 3.9 and effectively manages the dependencies for your examples.
+
+### Install Python 3.9.0
+
+Follow these steps to install Python from source:
+
+1. **Install Build Dependencies**: Begin by updating your system and installing the required packages:
+   ```bash
+   sudo apt update
+   sudo apt install -y build-essential zlib1g-dev libncurses5-dev libgdbm-dev libnss3-dev libssl-dev libreadline-dev libffi-dev wget
+   ```
+
+2. **Compile and Install Python**: Download, extract, and install Python:
+   ```bash
+   wget https://www.python.org/ftp/python/3.9.0/Python-3.9.0.tar.xz
+   tar xf Python-3.9.0.tar.xz
+   cd Python-3.9.0
+   ./configure --enable-optimizations --prefix=/usr
+   make -j $(nproc)
+   sudo make altinstall
+   ```
+
+3. **Verify Python Installation**: Ensure Python 3.9.0 is installed successfully:
+   ```bash
+   python3.9 --version
+   ```
+
+4. **Change Directory**: Move out of the Python source directory:
+   ```bash
+   cd ..
+   ```
+
+### Optional: Cleanup After Installation
+
+To optimize disk space after the Python installation:
+
+1. **Remove Python Source Files**: Next, use `sudo` to  remove the downloaded archive and the extracted Python source directory:
+   ```bash
+   sudo rm -rf Python-3.9.0.tar.xz Python-3.9.0
+   ```
+
+2. **Remove Build Dependencies**: Optionally, uninstall the build dependencies if they are no longer necessary:
+   ```bash
+   sudo apt remove --purge -y build-essential zlib1g-dev libncurses5-dev libgdbm-dev libnss3-dev libssl-dev libreadline-dev libffi-dev wget
+   sudo apt autoremove -y
+   ```
+
+### Virtual Environment Setup
+
+Prepare and activate a virtual environment for the TensorFlow Lite examples:
+
+1. **Create the Environment**: 
+   ```bash
+   python3.9 -m venv /usr/local/venvs/tflite
+   ```
+
+2. **Activate the Environment**: Always reactivate the virtual environment in new sessions:
+   ```bash
+   source /usr/local/venvs/tflite/bin/activate
+   ```
+
+**Note**: Remember to reactivate the `tflite` environment with `/usr/local/venvs/tflite/bin/activate` each time you work on the TensorFlow Lite examples.
+
+
 ## Install the TensorFlow Lite runtime
 
 In this project, all you need from the TensorFlow Lite API is the `Interpreter`

lite/examples/image_segmentation/raspberry_pi/README.md

@@ -23,6 +23,73 @@ Raspberry Pi. It's okay if you're using SSH to access the Pi shell (you don't
 need to use a keyboard connected to the Pi)—you only need a monitor attached to
 the Pi to see the camera stream.
 
+
+## Setup Environment
+
+To ensure the TensorFlow Lite examples run smoothly on Raspberry Pi OS based on Debian Bookworm (2024 release), setting up a Python virtual environment is crucial. This setup guarantees compatibility with Python 3.9 and effectively manages the dependencies for your examples.
+
+### Install Python 3.9.0
+
+Follow these steps to install Python from source:
+
+1. **Install Build Dependencies**: Begin by updating your system and installing the required packages:
+   ```bash
+   sudo apt update
+   sudo apt install -y build-essential zlib1g-dev libncurses5-dev libgdbm-dev libnss3-dev libssl-dev libreadline-dev libffi-dev wget
+   ```
+
+2. **Compile and Install Python**: Download, extract, and install Python:
+   ```bash
+   wget https://www.python.org/ftp/python/3.9.0/Python-3.9.0.tar.xz
+   tar xf Python-3.9.0.tar.xz
+   cd Python-3.9.0
+   ./configure --enable-optimizations --prefix=/usr
+   make -j $(nproc)
+   sudo make altinstall
+   ```
+
+3. **Verify Python Installation**: Ensure Python 3.9.0 is installed successfully:
+   ```bash
+   python3.9 --version
+   ```
+
+4. **Change Directory**: Move out of the Python source directory:
+   ```bash
+   cd ..
+   ```
+
+### Optional: Cleanup After Installation
+
+To optimize disk space after the Python installation:
+
+1. **Remove Python Source Files**: Next, use `sudo` to  remove the downloaded archive and the extracted Python source directory:
+   ```bash
+   sudo rm -rf Python-3.9.0.tar.xz Python-3.9.0
+   ```
+
+2. **Remove Build Dependencies**: Optionally, uninstall the build dependencies if they are no longer necessary:
+   ```bash
+   sudo apt remove --purge -y build-essential zlib1g-dev libncurses5-dev libgdbm-dev libnss3-dev libssl-dev libreadline-dev libffi-dev wget
+   sudo apt autoremove -y
+   ```
+
+### Virtual Environment Setup
+
+Prepare and activate a virtual environment for the TensorFlow Lite examples:
+
+1. **Create the Environment**: 
+   ```bash
+   python3.9 -m venv /usr/local/venvs/tflite
+   ```
+
+2. **Activate the Environment**: Always reactivate the virtual environment in new sessions:
+   ```bash
+   source /usr/local/venvs/tflite/bin/activate
+   ```
+
+**Note**: Remember to reactivate the `tflite` environment with `/usr/local/venvs/tflite/bin/activate` each time you work on the TensorFlow Lite examples.
+
+
 ## Install the TensorFlow Lite runtime
 
 In this project, all you need from the TensorFlow Lite API is the `Interpreter`

lite/examples/object_detection/raspberry_pi/README.md

@@ -24,6 +24,73 @@ Raspberry Pi. It's okay if you're using SSH to access the Pi shell (you don't
 need to use a keyboard connected to the Pi)—you only need a monitor attached to
 the Pi to see the camera stream.
 
+
+## Setup Environment
+
+To ensure the TensorFlow Lite examples run smoothly on Raspberry Pi OS based on Debian Bookworm (2024 release), setting up a Python virtual environment is crucial. This setup guarantees compatibility with Python 3.9 and effectively manages the dependencies for your examples.
+
+### Install Python 3.9.0
+
+Follow these steps to install Python from source:
+
+1. **Install Build Dependencies**: Begin by updating your system and installing the required packages:
+   ```bash
+   sudo apt update
+   sudo apt install -y build-essential zlib1g-dev libncurses5-dev libgdbm-dev libnss3-dev libssl-dev libreadline-dev libffi-dev wget
+   ```
+
+2. **Compile and Install Python**: Download, extract, and install Python:
+   ```bash
+   wget https://www.python.org/ftp/python/3.9.0/Python-3.9.0.tar.xz
+   tar xf Python-3.9.0.tar.xz
+   cd Python-3.9.0
+   ./configure --enable-optimizations --prefix=/usr
+   make -j $(nproc)
+   sudo make altinstall
+   ```
+
+3. **Verify Python Installation**: Ensure Python 3.9.0 is installed successfully:
+   ```bash
+   python3.9 --version
+   ```
+
+4. **Change Directory**: Move out of the Python source directory:
+   ```bash
+   cd ..
+   ```
+
+### Optional: Cleanup After Installation
+
+To optimize disk space after the Python installation:
+
+1. **Remove Python Source Files**: Next, use `sudo` to  remove the downloaded archive and the extracted Python source directory:
+   ```bash
+   sudo rm -rf Python-3.9.0.tar.xz Python-3.9.0
+   ```
+
+2. **Remove Build Dependencies**: Optionally, uninstall the build dependencies if they are no longer necessary:
+   ```bash
+   sudo apt remove --purge -y build-essential zlib1g-dev libncurses5-dev libgdbm-dev libnss3-dev libssl-dev libreadline-dev libffi-dev wget
+   sudo apt autoremove -y
+   ```
+
+### Virtual Environment Setup
+
+Prepare and activate a virtual environment for the TensorFlow Lite examples:
+
+1. **Create the Environment**: 
+   ```bash
+   python3.9 -m venv /usr/local/venvs/tflite
+   ```
+
+2. **Activate the Environment**: Always reactivate the virtual environment in new sessions:
+   ```bash
+   source /usr/local/venvs/tflite/bin/activate
+   ```
+
+**Note**: Remember to reactivate the `tflite` environment with `/usr/local/venvs/tflite/bin/activate` each time you work on the TensorFlow Lite examples.
+
+
 ## Download the example files
 
 First, clone this Git repo onto your Raspberry Pi like this:

lite/examples/pose_estimation/raspberry_pi/README.md

@@ -16,6 +16,73 @@ This sample can run on Raspberry Pi or any computer that has a camera. It uses
 OpenCV to capture images from the camera and TensorFlow Lite to run inference on
 the input image.
 
+
+## Setup Environment
+
+To ensure the TensorFlow Lite examples run smoothly on Raspberry Pi OS based on Debian Bookworm (2024 release), setting up a Python virtual environment is crucial. This setup guarantees compatibility with Python 3.9 and effectively manages the dependencies for your examples.
+
+### Install Python 3.9.0
+
+Follow these steps to install Python from source:
+
+1. **Install Build Dependencies**: Begin by updating your system and installing the required packages:
+   ```bash
+   sudo apt update
+   sudo apt install -y build-essential zlib1g-dev libncurses5-dev libgdbm-dev libnss3-dev libssl-dev libreadline-dev libffi-dev wget
+   ```
+
+2. **Compile and Install Python**: Download, extract, and install Python:
+   ```bash
+   wget https://www.python.org/ftp/python/3.9.0/Python-3.9.0.tar.xz
+   tar xf Python-3.9.0.tar.xz
+   cd Python-3.9.0
+   ./configure --enable-optimizations --prefix=/usr
+   make -j $(nproc)
+   sudo make altinstall
+   ```
+
+3. **Verify Python Installation**: Ensure Python 3.9.0 is installed successfully:
+   ```bash
+   python3.9 --version
+   ```
+
+4. **Change Directory**: Move out of the Python source directory:
+   ```bash
+   cd ..
+   ```
+
+### Optional: Cleanup After Installation
+
+To optimize disk space after the Python installation:
+
+1. **Remove Python Source Files**: Next, use `sudo` to  remove the downloaded archive and the extracted Python source directory:
+   ```bash
+   sudo rm -rf Python-3.9.0.tar.xz Python-3.9.0
+   ```
+
+2. **Remove Build Dependencies**: Optionally, uninstall the build dependencies if they are no longer necessary:
+   ```bash
+   sudo apt remove --purge -y build-essential zlib1g-dev libncurses5-dev libgdbm-dev libnss3-dev libssl-dev libreadline-dev libffi-dev wget
+   sudo apt autoremove -y
+   ```
+
+### Virtual Environment Setup
+
+Prepare and activate a virtual environment for the TensorFlow Lite examples:
+
+1. **Create the Environment**: 
+   ```bash
+   python3.9 -m venv /usr/local/venvs/tflite
+   ```
+
+2. **Activate the Environment**: Always reactivate the virtual environment in new sessions:
+   ```bash
+   source /usr/local/venvs/tflite/bin/activate
+   ```
+
+**Note**: Remember to reactivate the `tflite` environment with `/usr/local/venvs/tflite/bin/activate` each time you work on the TensorFlow Lite examples.
+
+
 ## Install the dependencies
 
 *   Run this script to install the Python dependencies, and download the TFLite