Python

示例列表

示例主要分为两类：相机 和 应用。 相机 类别中的示例侧重于如何使用相机。 应用 类别中的示例则侧重于使用相机生成的输出，例如3D点云、2D图像或来自相机的其它数据。这些示例展示了可以如何使用来自相机的数据。

• camera

  • basic

    • capture - Capture colored point cloud, save 2D image, save 3D ZDF, and export PLY, using the Zivid camera.

    • capture_from_file_camera - Capture point clouds, with color, with the Zivid file camera.

    • capture_hdr_complete_settings - Capture point clouds, with color, from the Zivid camera with fully configured settings.

    • capture_with_settings_from_yml - Capture images and point clouds, with and without color, from the Zivid camera with settings from YML file.

  • advanced

    • capture_2d_and_3d - Capture 2D and 3D with the Zivid camera.

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

  • info_util_other

    • adapt_settings_for_flickering_ambient_light - Adapt camera acquisition settings based on known ambient light conditions.

    • automatic_network_configuration_for_cameras - Automatically configure the IP addresses of connected cameras to match the network of the user's PC.

    • 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 default settings and diagnostics enabled.

    • context_manager_with_zivid - Sample showing how to use a context manager with Zivid Application and safely return processed data.

    • firmware_updater - Update firmware on the Zivid camera.

    • frame_info - Read frame info from the Zivid camera.

    • get_camera_intrinsics - Read intrinsic parameters from the Zivid camera (OpenCV model) or estimate them from the point cloud.

    • measure_scene_conditions - Measure ambient light conditions in the scene and output the measured flickering frequency of the ambient light if flickering is detected.

    • network_configuration - Uses Zivid API to change the IP address of the Zivid camera.

    • warmup - Short example of a basic way to warm up the 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_and_visualize_normals - Capture Zivid point clouds, compute normals and convert to color map and display.

      • capture_from_file_camera_vis_3d - Capture point clouds, with color, with the Zivid file camera.

      • 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_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

      • 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.

    • barcode_detector - Detect and decode linear and matrix barcodes from a 2D capture.

    • 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).

    • read_project_and_capture_image - Read a 2D image from file and project it using the camera projector.

    • reproject_points - Illuminate checkerboard (Zivid Calibration Board) centers by getting the checkerboard feature points

    • roi_box_via_aruco_marker - Filter the point cloud based on a ROI box given relative to the ArUco marker on a Zivid Calibration Board.

    • roi_box_via_checkerboard - Filter the point cloud based on a ROI box given relative to the Zivid Calibration Board.

    • stitch_continuously_rotating_object - Stitch point clouds from a continuously rotating object without pre-alignment using Local Point Cloud Registration and apply Voxel Downsample.

    • stitch_using_robot_mounted_camera - Stitch multiple point clouds captured with a robot mounted camera.

    • stitch_via_local_point_cloud_registration - Stitch two point clouds using a transformation estimated by Local Point Cloud Registration and apply Voxel Downsample.

    • transform_point_cloud_from_millimeters_to_meters - Transform point cloud data from millimeters to meters.

    • transform_point_cloud_via_aruco_marker - Transform a point cloud from camera to ArUco marker coordinate frame by estimating the marker's pose from the point cloud.

    • transform_point_cloud_via_checkerboard - Transform a point cloud from camera to checkerboard (Zivid Calibration Board) coordinate frame by getting checkerboard pose from the API.

    • hand_eye_calibration

      • hand_eye_gui - Hand-Eye Calibration GUI

      • pose_conversion_gui - Convert between different rotation formats with a GUI:

      • 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.

      • robodk_hand_eye_calibration

        • robodk_verify_hand_eye_calibration - Perform a touch test with a robot to verify Hand-Eye Calibration using the RoboDK interface.

    • multi_camera

      • multi_camera_calibration - Use captures of a calibration object to generate transformation matrices to a single coordinate frame, from connected cameras.

      • multi_camera_calibration_from_zdf - Use captures of a calibration object to generate transformation matrices to a single coordinate frame, from ZDF files.

      • stitch_by_transformation - Use transformation matrices from Multi-Camera calibration to transform point clouds into a single coordinate frame, from connected cameras.

      • stitch_by_transformation_from_zdf - Use transformation matrices from Multi-Camera calibration to transform point clouds into single coordinate frame, from a ZDF files.

    • robot_guidance

      • robodk_robot_guidance - Guide the robot to follow a path on the Zivid Calibration Board.

• modules

  • zividsamples

    • calibration_board_utils - Utility functions for the Zivid calibration board.

    • camera_verification - def capture_and_measure_from_frame(frame: zivid.Frame) -> VerificationAndState:

    • color_to_grayscale - if rgba_image.ndim != 3 or rgba_image.shape[2] != 4:

    • display - Display relevant data for Zivid Samples.

    • paths - Get relevant paths for Zivid Samples.

    • robodk_tools - Robot Control Module

    • save_load_matrix - Save and load Zivid 4x4 transformation matrices from and to YAML files.

    • save_load_transformation_matrix - assert_affine_matrix_and_save(transformation_matrix.as_matrix(), yaml_path)

    • settings_utils - categories = zivid.presets.categories2d(camera.info.model)

    • transformation_matrix - Convenience functions and a class for 4x4 transformation matrices.

    • white_balance_calibration - Balance color for 2D capture using white surface as reference.

操作指南

备注

这些示例的推荐 Python 版本是 3.7 - 3.9 。

请注意，Open3D 不适用于 Python 3.13 及更高版本。

1. 安装Zivid软件。

2. 下载Zivid Sample Data。

3. 查看 Zivid Python 示例存储库：

   git clone http://github.com/zivid/zivid-python-samples.git
   

4. 使用IDE或命令行安装runtime requirements：

cd zivid-python-samples
pip install -r requirements.txt

备注

如果 Open3D 安装失败，请确保您使用的是 Open3D 支持的 Python 版本。或者，您也可以运行以下命令，仅安装非 Open3D 示例所需的依赖项：

pip install ./modules

5. 打开并运行其中一个示例。

   备注

   在 Windows 上运行 GUI 示例应该通过 pythonw 完成。

• 使用Spyder IDE创建Python "Hello World"应用程序