Metavision SDK

https://docs.prophesee.ai/stable/
Admin
Metavision SDK is a comprehensive toolkit for event-based vision applications, offering...
Tokens:506,527
Snippets:5,095
Trust Score:9.9
Update:5 months ago
Show doc for...
Tokens:
Raw
### Run Simple Viewer with Event File

Source: https://docs.prophesee.ai/stable/samples/modules/core/simple_viewer.html

Provide the path to a RAW, DAT, or HDF5 file to start the sample with recorded data. This example uses 'spinner.raw'.

```bash
python metavision_simple_viewer.py -i spinner.raw
```

--------------------------------

### Run Simple Viewer for Live Camera

Source: https://docs.prophesee.ai/stable/samples/modules/core/simple_viewer.html

Execute this command to start the sample and display events from your live camera.

```bash
python metavision_simple_viewer.py
```

--------------------------------

### Get Min Supported Start Threshold

Source: https://docs.prophesee.ai/stable/api/python/hal/bindings.html

Retrieves the minimum supported value for the anti-flicker start threshold.

```APIDOC
## get_min_supported_start_threshold

### Description
Gets the minimum supported value for the anti-flicker start threshold.

### Return
- int - The minimum supported start threshold value.
```

--------------------------------

### Get Max Supported Start Threshold

Source: https://docs.prophesee.ai/stable/api/python/hal/bindings.html

Retrieves the maximum supported value for the anti-flicker start threshold.

```APIDOC
## get_max_supported_start_threshold

### Description
Gets the maximum supported value for the anti-flicker start threshold.

### Return
- int - The maximum supported start threshold value.
```

--------------------------------

### Run 3D Tracking Sample (Live Mode)

Source: https://docs.prophesee.ai/stable/samples/modules/cv3d/model_3d_tracking_python.html

Execute the sample using live stream from your camera. Ensure the specified path contains calibration, initial pose, and object description files.

```bash
python metavision_model_3d_tracking.py -i <base_path>/object

```

--------------------------------

### Run HAL Showcase Sample (Windows)

Source: https://docs.prophesee.ai/stable/samples/modules/hal/hal_showcase.html

Execute the HAL showcase sample on Windows to visualize event streams from a live camera.

```bash
metavision_hal_showcase.exe

```

--------------------------------

### Install HDF5 Tools on Ubuntu

Source: https://docs.prophesee.ai/stable/data/file_formats/hdf5.html

Install the hdf5-tools package on Ubuntu if you need to use command-line utilities like h5dump. This is a prerequisite for running the h5dump examples.

```bash
sudo apt -y install hdf5-tools
```

--------------------------------

### Run Generic Tracking Sample with Live Camera (Windows)

Source: https://docs.prophesee.ai/stable/samples/modules/analytics/tracking_generic_cpp.html

Start the generic tracking sample to process a live camera stream on Windows.

```bash
metavision_generic_tracking.exe

```

--------------------------------

### Get Start Threshold

Source: https://docs.prophesee.ai/stable/api/python/hal/bindings.html

Retrieves the current start threshold for the anti-flicker filter. Filtering begins when the number of successive periodic event bursts within the frequency band exceeds this threshold.

```APIDOC
## get_start_threshold

### Description
Gets the threshold above which Anti-flicker should start filtering.

### Return
- int - The threshold in number of bursts.
```

--------------------------------

### Run Generic Tracking Sample with Live Camera (Linux)

Source: https://docs.prophesee.ai/stable/samples/modules/analytics/tracking_generic_cpp.html

Start the generic tracking sample to process a live camera stream on Linux.

```bash
./metavision_generic_tracking

```

--------------------------------

### Stream Events with HAL Python API

Source: https://docs.prophesee.ai/stable/guides/events_streaming.html

A typical implementation in Python for streaming events using the HAL API. It involves getting decoders, starting the stream, and polling for buffers.

```python
i_cddecoder = device.get_i_event_cd_decoder()
i_cddecoder.add_event_buffer_callback(function_to_call_on_each_buffer)
i_eventsstreamdecoder = device.get_i_events_stream_decoder()
i_eventsstream = device.get_i_events_stream()
i_eventsstream.start()
while True:
    try:
        ret = i_eventsstream.poll_buffer()
        if ret < 0:
            break
        elif ret > 0:
            raw_data = i_eventsstream.get_latest_raw_data()
            if raw_data is not None:
                i_eventsstreamdecoder.decode(raw_data)
    except KeyboardInterrupt:
        break
i_eventsstream.stop()

```

--------------------------------

### Run XYT Tool with Camera Configuration (Windows)

Source: https://docs.prophesee.ai/stable/samples/modules/cv/xyt.html

Start the XYT tool on a live stream with camera settings loaded from a JSON file using the `-j` option on Windows. This allows pre-configuring biases, ROI, Anti-Flicker, STC, etc.

```bash
metavision_yxt.exe -j path\to\my_settings.json
```

--------------------------------

### Add Python Directories to Conda PYTHONPATH

Source: https://docs.prophesee.ai/stable/installation/windows.html

When using Anaconda, ensure that the Python installation and script directories are included in your `PYTHONPATH`. This example shows how to check and add the directory if it's missing.

```python
import sys
print(sys.path)
# Add %USERPROFILE%\AppData\Local\Programs\Python\Python310 to PYTHONPATH if the output of print(sys.path) does not mention it.
sys.path.append("%USERPROFILE%\AppData\Local\Programs\Python\Python310")
```

--------------------------------

### Process Camera Events with C++ Callback

Source: https://docs.prophesee.ai/stable/get_started/get_started_cpp.html

This is the main example for processing camera events. It sets up a camera, registers a callback function to count and print events, starts the camera, and runs until the stream ends.

```cpp
#include <metavision/sdk/stream/camera.h>
#include <metavision/sdk/base/events/event_cd.h>

// this function will be associated to the camera callback
void count_events(const Metavision::EventCD *begin, const Metavision::EventCD *end) {
    int counter = 0;

    // this loop allows us to get access to each event received in this callback
    for (const Metavision::EventCD *ev = begin; ev != end; ++ev) {
        ++counter; // count each event

        // print each event
        std::cout << "Event received: coordinates (" << ev->x << ", " << ev->y << "), t: " << ev->t
                  << ", polarity: " << ev->p << std::endl;
    }

    // report
    std::cout << "There were " << counter << " events in this callback" << std::endl;
}

// main loop
int main(int argc, char *argv[]) {
    Metavision::Camera cam; // create the camera

    if (argc >= 2) {
        // if we passed a file path, open it
        cam = Metavision::Camera::from_file(argv[1]);
    } else {
        // open the first available camera
        cam = Metavision::Camera::from_first_available();
    }

    // to analyze the events, we add a callback that will be called periodically to give access to the latest events
    cam.cd().add_callback(count_events);

    // start the camera
    cam.start();

    // keep running while the camera is on or the recording is not finished
    while (cam.is_running()) {}

    // the recording is finished, stop the camera.
    // Note: we will never get here with a live camera
    cam.stop();
}

```

--------------------------------

### Run Simple Window Sample

Source: https://docs.prophesee.ai/stable/samples/modules/ui/simple_window.html

Execute the simple window sample on Linux or Windows. Ensure the sample is compiled first.

```bash
./metavision_simple_window

```

```bash
metavision_simple_window.exe

```

--------------------------------

### Run Simple Recorder Sample

Source: https://docs.prophesee.ai/stable/samples/modules/core/simple_recorder.html

Execute this command in your terminal to start the simple recorder sample. Ensure your camera is plugged in.

```bash
python metavision_simple_recorder.py

```

--------------------------------

### Install Vcpkg Dependencies

Source: https://docs.prophesee.ai/stable/installation/windows_openeb.html

Install the necessary dependencies using vcpkg with the specified triplet and installation root.

```bash
vcpkg install --triplet x64-windows --x-install-root installed
```

--------------------------------

### Run HAL Showcase Sample (Linux)

Source: https://docs.prophesee.ai/stable/samples/modules/hal/hal_showcase.html

Execute the HAL showcase sample on Linux to visualize event streams from a live camera.

```bash
./metavision_hal_showcase

```

--------------------------------

### Install Python Dependencies

Source: https://docs.prophesee.ai/stable/installation/windows.html

Upgrade pip and install the necessary project dependencies using the `pip install` command within your activated virtual environment. This command installs packages from multiple requirement files.

```shell
C:\tmp\prophesee\py3venv\Scripts\python -m pip install pip --upgrade
C:\tmp\prophesee\py3venv\Scripts\python -m pip install -r "C:\Program Files\Prophesee\share\metavision\python_requirements\requirements_openeb.txt" -r "C:\Program Files\Prophesee\share\metavision\python_requirements\requirements_sdk_advanced.txt" -r "C:\Program Files\Prophesee\share\metavision\python_requirements\requirements_pytorch_cpu.txt"
```

--------------------------------

### Run PSM Sample with Camera Configuration (Windows)

Source: https://docs.prophesee.ai/stable/samples/modules/analytics/psm_cpp.html

Execute the particle size measurement sample with a live camera stream and load camera settings from a JSON file on Windows.

```bash
metavision_psm.exe -j path\to\my_settings.json

```

--------------------------------

### start

Source: https://docs.prophesee.ai/stable/genindex.html

Starts the event stream.

```APIDOC
## start

### Description
Initiates the streaming of events from the sensor or data source.

### Method
metavision_hal.I_EventsStream
```

--------------------------------

### Install OpenEB to Default Directory

Source: https://docs.prophesee.ai/stable/installation/windows_openeb.html

Builds and installs OpenEB to the default installation directory (C:\Program Files\Prophesee). This command requires administrator privileges.

```bash
cmake --build . --config Release --target install
```

--------------------------------

### Load Camera Settings for Live Stream (Windows)

Source: https://docs.prophesee.ai/stable/samples/modules/cv/sparse_flow_cpp.html

Start the sample on a live stream, loading camera settings (biases, ROI, etc.) from a JSON file using the '--input-camera-config' option.

```bash
metavision_sparse_optical_flow.exe -j path\to\my_settings.json

```

--------------------------------

### Install YOLOv8 Requirements

Source: https://docs.prophesee.ai/stable/tutorials/other/train_and_test_event_based_yolo_detection_model.html

Installs all necessary Python packages for YOLOv8 by referencing the `requirements.txt` file. It's recommended to perform this installation within a virtual environment.

```bash
pip install -r requirements.txt
```

--------------------------------

### Display Help for Synced Camera Streams Slicer (Windows)

Source: https://docs.prophesee.ai/stable/samples/modules/stream/synced_camera_slicer_cpp.html

View available command-line options for the sample on Windows.

```bash
metavision_synced_camera_streams_slicer.exe -h

```

--------------------------------

### start

Source: https://docs.prophesee.ai/stable/api/cpp/hal/facilities.html

Starts streaming events from the camera or data source.

```APIDOC
## start

### Description
Starts streaming events from the camera or data source.

### Method
void start()

```

--------------------------------

### Run Generic Tracking Sample with Camera Configuration (Windows)

Source: https://docs.prophesee.ai/stable/samples/modules/analytics/tracking_generic_cpp.html

Launch the generic tracking sample with a JSON camera settings file on Windows. This is recommended for using the sensor's STC.

```bash
metavision_generic_tracking.exe -j path\to\my_settings.json

```

--------------------------------

### Start Master Camera (Windows)

Source: https://docs.prophesee.ai/stable/samples/modules/hal/hal_sync.html

Command to start the master camera on a Windows system after the slave has been started. Replace SERIAL_NUMBER with the actual camera's serial number.

```bash
metavision_hal_sync.exe --master -s SERIAL_NUMBER

```

--------------------------------

### Run Simple Motion Capture with Live Cameras (Windows)

Source: https://docs.prophesee.ai/stable/samples/modules/cv3d/simple_motion_capture_cpp.html

Execute the sample on Windows with multiple live cameras. Ensure the master camera is listed first in all configuration files.

```bash
metavision_simple_motion_capture.exe -s 00051299 00050697 00051165 \
  --camera-settings-paths master-camera-settings.json slave-camera-settings.json slave-camera-settings.json \
  --calibration-paths master-camera-geometry.json slave-left-camera-geometry.json slave-right-camera-geometry.json \
  --ext-calibration-paths extrinsics-master-slave-left.json extrinsics-master-slave-right.json \
  --3d-scene-path skeleton-scene.scene \
  --adj-path adjacency-graph.json

```

--------------------------------

### Start Master Camera (Linux)

Source: https://docs.prophesee.ai/stable/samples/modules/hal/hal_sync.html

Command to start the master camera on a Linux system after the slave has been started. Replace SERIAL_NUMBER with the actual camera's serial number.

```bash
./metavision_hal_sync --master -s SERIAL_NUMBER

```

--------------------------------

### Load Camera Settings for Live Stream (Linux)

Source: https://docs.prophesee.ai/stable/samples/modules/cv/sparse_flow_cpp.html

Start the sample on a live stream, loading camera settings (biases, ROI, etc.) from a JSON file using the '--input-camera-config' option.

```bash
./metavision_sparse_optical_flow -j path/to/my_settings.json

```

--------------------------------

### Install Python Dependencies

Source: https://docs.prophesee.ai/stable/installation/windows_sdk_from_sources.html

Upgrade pip and install SDK-related Python packages using the virtual environment's Python interpreter. This command installs packages from multiple requirement files.

```bash
C:\tmp\prophesee\py3venv\Scripts\python -m pip install pip --upgrade
C:\tmp\prophesee\py3venv\Scripts\python -m pip install -r MV_SDK_SRC_DIR\utils\python\requirements_openeb.txt -r MV_SDK_SRC_DIR\utils\python\requirements_sdk_advanced.txt -r MV_SDK_SRC_DIR\utils\python\requirements_pytorch_cpu.txt
```

--------------------------------

### Run XYT Tool with Camera Configuration (Linux)

Source: https://docs.prophesee.ai/stable/samples/modules/cv/xyt.html

Start the XYT tool on a live stream with camera settings loaded from a JSON file using the `--input-camera-config` option on Linux. This allows pre-configuring biases, ROI, Anti-Flicker, STC, etc.

```bash
./metavision_yxt -j path/to/my_settings.json
```

--------------------------------

### Install Python Bindings for Specific Python Version (Linux)

Source: https://docs.prophesee.ai/stable/faq.html

Use this command to install Metavision SDK Python bindings for a specific Python version if the default installation does not match your environment.

```bash
sudo apt -y install metavision-sdk-python3.11
```

--------------------------------

### Display PSM Sample Help (Windows)

Source: https://docs.prophesee.ai/stable/samples/modules/analytics/psm_cpp.html

Display the available command-line options for the particle size measurement sample on Windows.

```bash
metavision_psm.exe -h

```

--------------------------------

### Start and Check Running Status

Source: https://docs.prophesee.ai/stable/api/cpp/stream/camera.html

Starts the camera and checks if it is currently running.

```APIDOC
## bool start()

### Description
Starts the camera from the given input source. It will start polling events from the source and calling specified events callbacks. It has no effect if the start function has been already called and not the stop function.

### Method
start()

### Throws
CameraException – if the camera has not been initialized.

### Returns
true if the camera started successfully, false otherwise. Also returns false, if the camera is already started.
```

```APIDOC
## bool is_running() const

### Description
Checks if the camera is running or there are data remaining from an offline source.

### Method
is_running() const

### Parameters
None

### Returns
true if the camera is running or has remaining data, false otherwise.
```

--------------------------------

### Run Time Surface Sample (Windows)

Source: https://docs.prophesee.ai/stable/samples/modules/core/time_surface_cpp.html

Execute the C++ sample on Windows to process live camera input. No additional arguments are needed for live mode.

```bash
metavision_time_surface.exe

```

--------------------------------

### Start Camera Stream in C++

Source: https://docs.prophesee.ai/stable/get_started/get_started_cpp.html

Starts the event streaming from the initialized camera object.

```cpp
    cam.start();

```

--------------------------------

### Display Help and Options (Windows)

Source: https://docs.prophesee.ai/stable/samples/modules/analytics/tracking_spatter_cpp.html

View all available command-line options for the spatter tracking sample on Windows. This helps in understanding and customizing the sample's behavior.

```bash
metavision_spatter_tracking.exe -h

```

--------------------------------

### Run Spatter Tracking Sample (Live)

Source: https://docs.prophesee.ai/stable/samples/modules/analytics/tracking_spatter_py.html

Execute the spatter tracking sample using the live stream from your camera.

```bash
python metavision_spatter_tracking.py

```

--------------------------------

### Install Python Dependencies

Source: https://docs.prophesee.ai/stable/installation/windows_openeb.html

Upgrade pip and install OpenEB and PyTorch requirements into the virtual environment.

```bash
C:\tmp\prophesee\py3venv\Scripts\python -m pip install pip --upgrade
C:\tmp\prophesee\py3venv\Scripts\python -m pip install -r OPENEB_SRC_DIR\utils\python\requirements_openeb.txt -r OPENEB_SRC_DIR\utils\python\requirements_pytorch_cpu.txt
```

--------------------------------

### Update APT and Install OpenEB

Source: https://docs.prophesee.ai/stable/installation/linux_openeb_with_packages.html

Refresh the package list and install the main OpenEB package.

```bash
sudo apt update
sudo apt -y install metavision-openeb
```

--------------------------------

### Display Help for Synced Camera Streams Slicer (Linux)

Source: https://docs.prophesee.ai/stable/samples/modules/stream/synced_camera_slicer_cpp.html

View available command-line options for the sample on Linux.

```bash
./metavision_synced_camera_streams_slicer -h

```

--------------------------------

### Remove Previous OpenEB Installations

Source: https://docs.prophesee.ai/stable/installation/linux_openeb_with_packages.html

Before upgrading, remove any existing Prophesee software installations to avoid conflicts.

```bash
sudo apt remove '~nprophesee-.*' '~nmetavision-.*' '~nhdf5-ecf-*' '~nhdf5-plugin-ecf-*' --purge
```

--------------------------------

### Run PSM Sample with Camera Configuration (Linux)

Source: https://docs.prophesee.ai/stable/samples/modules/analytics/psm_cpp.html

Execute the particle size measurement sample with a live camera stream and load camera settings from a JSON file on Linux.

```bash
./metavision_psm -j path/to/my_settings.json

```

--------------------------------

### Start Camera and Viewer

Source: https://docs.prophesee.ai/stable/samples/modules/cv3d/active_marker_3d_tracking_cpp.html

Starts the camera stream and the 3D viewer, then stops the camera after the viewer is closed.

```cpp
camera.start();
viewer.run();
camera.stop();

```

--------------------------------

### Run Generic Tracking Sample with Camera Configuration (Linux)

Source: https://docs.prophesee.ai/stable/samples/modules/analytics/tracking_generic_cpp.html

Launch the generic tracking sample with a JSON camera settings file on Linux. This is recommended for using the sensor's STC.

```bash
./metavision_generic_tracking -j path/to/my_settings.json

```

--------------------------------

### Run Simple Motion Capture with Live Cameras (Linux)

Source: https://docs.prophesee.ai/stable/samples/modules/cv3d/simple_motion_capture_cpp.html

Execute the sample on Linux with multiple live cameras. Ensure the master camera is listed first in all configuration files.

```bash
./metavision_simple_motion_capture -s 00051299 00050697 00051165 \
    --camera-settings-paths master-camera-settings.json slave-camera-settings.json slave-camera-settings.json \
    --calibration-paths master-camera-geometry.json slave-left-camera-geometry.json slave-right-camera-geometry.json \
    --ext-calibration-paths extrinsics-master-slave-left.json extrinsics-master-slave-right.json \
    --3d-scene-path skeleton-scene.scene \
    --adj-path adjacency-graph.json

```

--------------------------------

### Install Camera Drivers

Source: https://docs.prophesee.ai/stable/installation/windows_openeb.html

Installs drivers for the EVK camera using wdi-simple.exe. Run this command prompt as an administrator.

```bash
wdi-simple.exe -n "EVK" -m "Prophesee" -v 0x04b4 -p 0x00f4
```

```bash
wdi-simple.exe -n "EVK" -m "Prophesee" -v 0x04b4 -p 0x00f5
```

```bash
wdi-simple.exe -n "EVK" -m "Prophesee" -v 0x04b4 -p 0x00f3
```

--------------------------------

### Install Core System Dependencies

Source: https://docs.prophesee.ai/stable/installation/linux_openeb.html

Installs essential development tools and libraries required for OpenEB compilation and functionality.

```bash
sudo apt update
sudo apt -y install apt-utils build-essential software-properties-common wget unzip curl git cmake
sudo apt -y install libopencv-dev libboost-all-dev libusb-1.0-0-dev libprotobuf-dev protobuf-compiler
sudo apt -y install libhdf5-dev hdf5-tools libglew-dev libglfw3-dev libcanberra-gtk-module ffmpeg
```

--------------------------------

### Run Active Marker Tracking Sample (Windows)

Source: https://docs.prophesee.ai/stable/samples/modules/cv3d/active_marker_3d_tracking_cpp.html

Launches the active marker tracking sample on Windows using a RAW recording, active marker description, camera calibration, and a scene file.

```bash
metavision_active_marker_3d_tracking.exe -i active_marker_dataset/active_marker.raw -a active_marker_dataset/rectangular_active_marker.json -c active_marker_dataset/calibration.json -s active_marker_dataset/handle_scene/handle_scene.scene

```

--------------------------------

### Display Help for Event Frame Generation Sample (Windows)

Source: https://docs.prophesee.ai/stable/samples/modules/core/event_frame_generation.html

Display all available command-line options for the event frame generation sample on Windows.

```bash
metavision_event_frame_generation.exe -h

```

--------------------------------

### Install Video and OpenGL Diagnostic Tools

Source: https://docs.prophesee.ai/stable/installation/linux_openeb_with_packages.html

Install essential packages for video management and diagnosing OpenGL driver issues.

```bash
sudo apt -y install libcanberra-gtk-module mesa-utils ffmpeg
```

--------------------------------

### Display PSM Sample Help (Linux)

Source: https://docs.prophesee.ai/stable/samples/modules/analytics/psm_cpp.html

Display the available command-line options for the particle size measurement sample on Linux.

```bash
./metavision_psm -h

```

--------------------------------

### EventTrailFilterModule - Get Threshold Limits

Source: https://docs.prophesee.ai/stable/api/python/hal/bindings.html

Gets the minimum and maximum supported threshold values for event trail filtering delay.

```APIDOC
## get_max_supported_threshold(_self : metavision_hal.I_EventTrailFilterModule_) -> int

### Description
Gets the maximum supported value for event trail filtering threshold delay (in microseconds).

### Parameters
#### Path Parameters
- **_self** (metavision_hal.I_EventTrailFilterModule_) - Required - The module instance.

### Return Value
- int - The maximum supported threshold value.

## get_min_supported_threshold(_self : metavision_hal.I_EventTrailFilterModule_) -> int

### Description
Gets the minimum supported value for event trail filtering threshold delay (in microseconds).

### Parameters
#### Path Parameters
- **_self** (metavision_hal.I_EventTrailFilterModule_) - Required - The module instance.

### Return Value
- int - The minimum supported threshold value.
```

--------------------------------

### Install aedat Library

Source: https://docs.prophesee.ai/stable/samples/modules/core/interop.html

Install the Python library required for reading aedat4 files. This is essential for processing data in the aedat4 format.

```bash
python -m pip install aedat
```

--------------------------------

### Run Event Frame Viewer Sample

Source: https://docs.prophesee.ai/stable/samples/modules/core/event_frame_viewer.html

To start the sample on an Event Frame file, provide the RAW file path as an argument. This command displays the event frames.

```bash
python metavision_event_frame_viewer.py recording_histo.raw

```

--------------------------------

### Install Node.js for Metavision Studio

Source: https://docs.prophesee.ai/stable/installation/linux_sdk_from_sources.html

Installs Node.js on a Debian-based system using NodeSource repositories. This is a prerequisite for compiling Metavision Studio.

```bash
sudo apt-get update
sudo apt-get install -y ca-certificates gnupg
sudo mkdir -p /etc/apt/keyrings
curl -fsSL https://deb.nodesource.com/gpgkey/nodesource-repo.gpg.key | sudo gpg --dearmor -o /etc/apt/keyrings/nodesource.gpg
echo "deb [signed-by=/etc/apt/keyrings/nodesource.gpg] https://deb.nodesource.com/node_16.x nodistro main" | sudo tee /etc/apt/sources.list.d/nodesource.list
sudo apt-get update
sudo apt-get install nodejs -y
```

--------------------------------

### Run Time Surface Sample (Linux)

Source: https://docs.prophesee.ai/stable/samples/modules/core/time_surface_cpp.html

Execute the C++ sample on Linux to process live camera input. No additional arguments are needed for live mode.

```bash
./metavision_time_surface

```

--------------------------------

### Uninstall Previous OpenEB Installation

Source: https://docs.prophesee.ai/stable/installation/linux_openeb.html

Run this command from the build folder to remove previously installed Prophesee software if upgrading OpenEB.

```bash
sudo make uninstall

```

--------------------------------

### Display Help for 3D Tracking Sample

Source: https://docs.prophesee.ai/stable/samples/modules/cv3d/model_3d_tracking_python.html

View all available command-line options and parameters for the 3D tracking sample.

```bash
python metavision_model_3d_tracking.py -h

```

--------------------------------

### Install Specific Python Version Bindings

Source: https://docs.prophesee.ai/stable/installation/linux_openeb_with_packages.html

Install Python bindings for a specific Python version if it differs from the system's default.

```bash
sudo apt -y install metavision-openeb-python3.9
```

--------------------------------

### Display Help for Event Frame Generation Sample (Linux)

Source: https://docs.prophesee.ai/stable/samples/modules/core/event_frame_generation.html

Display all available command-line options for the event frame generation sample on Linux.

```bash
./metavision_event_frame_generation -h

```

--------------------------------

### Start Slave Camera

Source: https://docs.prophesee.ai/stable/samples/modules/core/synchronization.html

Run this command to start the slave camera. Replace `SERIAL_NUMBER` with the actual serial number of your slave camera.

```python
python metavision_sync.py -s SERIAL_NUMBER -m slave

```

--------------------------------

### Display Help and Options (Linux)

Source: https://docs.prophesee.ai/stable/samples/modules/analytics/tracking_spatter_cpp.html

View all available command-line options for the spatter tracking sample on Linux. This helps in understanding and customizing the sample's behavior.

```bash
./metavision_spatter_tracking -h

```

--------------------------------

### Example DAT File Header

Source: https://docs.prophesee.ai/stable/data/file_formats/dat.html

This is an example of the ASCII text header found at the beginning of a DAT file. It contains metadata about the recording.

```text
% Data file containing CD events
% Date 2020-09-14 14:18:29
% Version 2
% Width 640
% Height 480


```

--------------------------------

### Run HAL Showcase with Recorded Data (Windows)

Source: https://docs.prophesee.ai/stable/samples/modules/hal/hal_showcase.html

Run the HAL showcase sample on Windows using a recorded RAW file as input.

```bash
metavision_hal_showcase.exe -i spinner.raw

```

--------------------------------

### Install rospy and rosbag Libraries

Source: https://docs.prophesee.ai/stable/samples/modules/core/interop.html

Install the necessary Python libraries to read rosbag files. This is a prerequisite for handling rosbag format data.

```bash
python -m pip install --extra-index-url https://rospypi.github.io/simple/ rospy rosbag
```

--------------------------------

### Run HAL Showcase with Recorded Data (Linux)

Source: https://docs.prophesee.ai/stable/samples/modules/hal/hal_showcase.html

Run the HAL showcase sample on Linux using a recorded RAW file as input.

```bash
./metavision_hal_showcase -i spinner.raw

```

--------------------------------

### C++: Register Callback and Start Camera

Source: https://docs.prophesee.ai/stable/guides/events_streaming.html

Associate the defined callback function with the camera's CD events and start the camera stream.

```cpp
// add a callback that will be called periodically to give access to the latest events
cam.cd().add_callback(my_function);
// start the camera
cam.start();

```

--------------------------------

### Display Generic Tracking Sample Help (Windows)

Source: https://docs.prophesee.ai/stable/samples/modules/analytics/tracking_generic_cpp.html

View available command-line options for the generic tracking sample on Windows.

```bash
metavision_generic_tracking.exe -h

```

--------------------------------

### Generic Configuration Get

Source: https://docs.prophesee.ai/stable/api/cpp/stream/features.html

Get the typed value for a named key from the configuration dictionary. Returns a default value if the key is not found or cannot be extracted.

```APIDOC
## get

### Description
Gets the (typed) value for a named key in the config dictionary if it exists and can be extracted from the corresponding value safely or the provided default value.

### Method
`template<typename T> T get(const std::string &key, const T &def = T()) const`

### Template Parameters
* **T** - Type of the value to return as.

### Parameters
* **key** (const std::string&) - Required - Name of the config key.
* **def** (const T&, optional) - Default value if the config key is not found. Defaults to T().

### Returns
`T` - Value of the config.
```

--------------------------------

### Run 3D Tracking Sample (Live Mode)

Source: https://docs.prophesee.ai/stable/samples/modules/cv3d/model_3d_tracking_cpp.html

Execute the 3D tracking sample in live mode using your camera stream. Provide the base path to a folder containing calibration, initial pose, and object description files.

```bash
./metavision_model_3d_tracking -i <base_path>/object

```

```bash
metavision_model_3d_tracking.exe -i <base_path>/object

```

--------------------------------

### YAML/CSV Hyperparameter File Example

Source: https://docs.prophesee.ai/stable/api/python/core_ml/corner_detection.html

Example structure for a hyperparameter file used with `_load_from_checkpoint`. This file can define hierarchical configurations for training parameters.

```yaml
drop_prob: 0.2
data
    batch_size: 32
```
Tokens:
Raw