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
capture - Capture point clouds, with color, from the Zivid camera.
capture_2d - Capture 2D images from the Zivid camera.
capture_2d_with_settings_from_yml - Capture 2D images from the Zivid camera, with settings from YML file.
capture_assistant - Use Capture Assistant to capture point clouds, with color, from the Zivid camera.
capture_from_file_camera - Capture point clouds, with color, with the Zivid file camera.
capture_hdr - Capture point clouds, with color, from the Zivid camera.
capture_hdr_complete_settings - Capture point clouds, with color, from the Zivid camera with fully configured settings.
capture_with_settings_from_yml - Capture point clouds, with color, from the Zivid camera, with settings from YML file.
advanced
capture_2d_and_3d - Capture 2D and 3D separately with the Zivid camera.
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
camera_info - Print version information for Python, zivid-python and Zivid SDK, then list cameras and print camera info and state for each connected camera.
camera_user_data - Store user data on the Zivid camera.
capture_with_diagnostics - Capture point clouds, with color, from the Zivid camera, with settings from YML file and diagnostics enabled.
firmware_updater - Update firmware on the Zivid camera.
get_camera_intrinsics - Read intrinsic parameters from the Zivid camera (OpenCV model) or estimate them from the point cloud.
warmup - A basic warm-up method for a Zivid camera with specified time and capture cycle.
maintenance
correct_camera_in_field - Correct the dimension trueness of a Zivid camera.
reset_camera_in_field - Reset infield correction on a camera.
verify_camera_in_field - Check the dimension trueness of a Zivid camera.
verify_camera_in_field_from_zdf - Check the dimension trueness of a Zivid camera from a ZDF file.
applications
basic
visualization
capture_from_file_camera_vis_3d - Capture point clouds, with color, with the Zivid file camera.
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.
project_image_start_and_stop - Start the Image Projection and Stop it.
read_and_project_image - Read a 2D image from file and project it using the camera projector.
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
auto_2d_settings - Automatically find 2D settings for a 2D capture by using a Zivid calibration board.
color_balance - Balance color of a 2D image by using a Zivid calibration board.
create_depth_map - Read point cloud data from a ZDF file, convert it to OpenCV format, then extract and visualize depth map.
downsample - Downsample point cloud from a ZDF file.
gamma_correction - Capture 2D image with gamma correction.
get_checkerboard_pose_from_zdf - Read point cloud data of a Zivid calibration board from a ZDF file, estimate the
hand_eye_calibration - Perform Hand-Eye calibration.
mask_point_cloud - Read point cloud data from a ZDF file, apply a binary mask, and visualize it.
project_and_find_marker - Show a marker using the projector, capture a set of 2D images to find the marker coordinates (2D and 3D).
reproject_points - Illuminate checkerboard (Zivid Calibration Board) corners by getting checkerboard pose
roi_box_via_checkerboard - Filter the point cloud based on a ROI box given relative to the Zivid Calibration Board.
hand_eye_calibration
pose_conversions - Convert to/from Transformation Matrix (Rotation Matrix + Translation Vector).
robodk_hand_eye_calibration - Generate a dataset and perform hand-eye calibration using the Robodk interface.
utilize_hand_eye_calibration - Transform single data point or entire point cloud from camera to robot base reference frame using Hand-Eye calibration
verify_hand_eye_with_visualization - Verify hand-eye calibration by transforming all dataset point clouds and
ur_hand_eye_calibration
universal_robots_perform_hand_eye_calibration - Script to generate a dataset and perform hand-eye calibration using a Universal Robot UR5e robot.
robot_guidance
robodk_robot_guidance - Guide the robot to follow a path on the Zivid Calibration Board.
verify_hand_eye_calibration
robodk_verify_hand_eye_calibration - Perform a touch test with a robot to verify Hand-Eye Calibration using the RoboDK interface.
sample_utils
calibration_board_utils - Utility functions for the Zivid calibration board.
display - Display relevant data for Zivid Samples.
paths - Get relevant paths for Zivid Samples.
robodk_tools - Robot Control Module
save_load_matrix - try:
white_balance_calibration - Balance color for 2D capture using white surface as reference.
Instructions
Note
The recommended Python version for these samples is 3.7 - 3.9.
Install the runtime requirements using IDE or command line:
pip install -r requirements.txt
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"
Open and run one of the samples.