GetAutoNoiseRemovalSetting

Automatically adjust clustering denoising parameters (Cluster Denoising Distance Threshold, Cluster Denoising Effective Points).

# Copyright (c) RVBUST, Inc - All rights reserved.
import PyRVC as RVC
import os
import numpy as np
import cv2
from Utils.Tools import *


def App():

    # Initialize RVC X system.
    RVC.SystemInit()

    # Choose RVC X Camera type (USB, GigE or All)
    opt = RVC.SystemListDeviceTypeEnum.All

    # Scan all RVC X GigE Camera devices.
    ret, devices = RVC.SystemListDevices(opt)

    #  Find whether any RVC X GigE Camera is connected or not.
    if len(devices) == 0:
        print("Can not find any RVC X Camera!")
        RVC.SystemShutdown()
        return 1

    # Create a RVC X Camera and choose use left side camera.
    x = RVC.X1.Create(devices[0], RVC.CameraID_Left)

    # Test RVC X Camera is valid or not.
    if x.IsValid() is not True:
        print("RVC X Camera is not valid!")
        RVC.X1.Destroy(x)
        RVC.SystemShutdown()
        return 1
    #PrintCaptureMode(devices[0])

    # Open RVC X Camera.
    ret1 = x.Open()

    # Test RVC X Camera is opened or not.
    if not ret1:
        print("open camera failed!")
        RVC.X1.Destroy(x)
        RVC.SystemShutdown()
        return 1

    # Print ExposureTime Range
    _, exp_range_min, exp_range_max = x.GetExposureTimeRange()
    print("ExposureTime Range:[{}, {}]".format(exp_range_min, exp_range_max))

    # Set capture parameters
    cap_opt = RVC.X1_CaptureOptions()

    '''
     We can use GetAutoNoiseRemovalSetting() function to automatically set noise_removal_distance and
     noise_removal_point_number.
     However, the recommended practice is to use the auto noise removal function on the RVCManager.exe
     to automatically obtain the parameters, then adjust them on the RVCManager.exe, and then set them
     here directly by number like the above.
     '''
    x.GetAutoNoiseRemovalSetting(cap_opt)

    # Capture a point map and a image.
    ret2 = x.Capture(cap_opt)

    # Create saving address of image and point map.
    save_address = "Data"
    TryCreateDir(save_address)

    if ret2 == True:
        print("RVC X Camera capture successed!")

        # Get image data and image size.
        img = x.GetImage()

        # Convert image to array and save it.
        img = np.array(img, copy=False)
        cv2.imwrite("Data/test.png", img)
        print("Save image successed!")

        # Save point map (m) to file.
        if x.GetPointMap().Save("Data/test.ply", RVC.PointMapUnitEnum.Meter):
            print("Save point map successed!")
        else:
            print("Save point map failed!")
    else:
        print("RVC X Camera capture failed!")
        print(RVC.GetLastErrorMessage())
        x.Close()
        RVC.X1.Destroy(x)
        RVC.SystemShutdown()
        return 1

    # Close RVC X Camera.
    x.Close()

    # Destroy RVC X Camera.
    RVC.X1.Destroy(x)

    # Shutdown RVC X System.
    RVC.SystemShutdown()

    return 0


if __name__ == "__main__":
    App()