Python

Sample list

There are two main categories of samples: Camera and Applications. The samples in the Camera category focus only on how to use the camera. The samples in the Applications category use the output generated by the camera, such as the 3D point cloud, a 2D image or other data from the camera. These samples shows how the data from the camera can be used.

  • camera

    • basic

    • advanced

      • capture_hdr_loop - Cover the same dynamic range in a scene with different acquisition settings to optimize for quality, speed, or to find a compromise.

      • capture_hdr_print_normals - Capture Zivid point clouds, compute normals and print a subset.

    • info_util_other

      • capture_with_diagnostics - Capture point clouds, with color, from the Zivid camera, with settings from YML file and diagnostics enabled.

      • print_version_info - Print version information for Python, zivid-python and Zivid SDK, then list cameras and print camera info for each connected camera.

      • warmup - A basic warm-up method for a Zivid camera with specified time and capture cycle.

  • applications

    • basic

      • visualization

        • capture_hdr_vis_normals - Capture Zivid point clouds, compute normals and convert to color map and display.

        • capture_vis_3d - Capture point clouds, with color, from the Zivid camera, and visualize it.

        • read_zdf_vis_3d - Read point cloud data from a ZDF file and visualize it.

      • file_formats

        • convert_zdf - Convert point cloud data from a ZDF file to your preferred format (.ply, .csv, .txt, .png, .jpg, .bmp, .tiff).

        • read_iterate_zdf - Read point cloud data from a ZDF file, iterate through it, and extract individual points.

    • advanced

  • sample_utils

    • display - Display relevant data for Zivid Samples.

    • paths - Get relevant paths for Zivid Samples.

Instructions

  1. Install Zivid Software

  2. Install Zivid Python. Note: The recommended Python version for these samples is 3.8.

  3. Download Zivid Sample Data

  4. [Optional] Launch the Python IDE of your choice. Read our instructions on setting up Python.

  5. Install the runtime requirements using IDE or command line:

    pip install -r requirements.txt
    
  6. Add the directory source to PYTHONPATH. Navigate to the root of the repository and run:

  • PowerShell: $env:PYTHONPATH=$env:PYTHONPATH + ";$PWD\source"

  • cmd: set PYTHONPATH="$PYTHONPATH;$PWD\source"

  • bash: export PYTHONPATH="$PYTHONPATH:$PWD/source"

  1. Open and run one of the samples.