GetConfidenceMap

设置置信度去噪阈值，采集并保存点云与 2D 图，在图像中选取一点，打印此点的置信度值。

# 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 Camera devices.
    ret, devices = RVC.SystemListDevices(opt)
    print("RVC X Camera devices number:%d" % len(devices))

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

    # 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() == True:
        print("RVC X Camera is valid!")
    else:
        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 ret1 and x.IsOpen() == True:
        print("RVC X Camera is opened!")
    else:
        print("RVC X Camera is not opened!")
        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))

    cap_opts = RVC.X1_CaptureOptions()
    cap_opts.confidence_threshold = 0.6

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

    # 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()
        width = img.GetSize().cols
        height = img.GetSize().rows

        # Check the camera color information.
        print("width=%d, height=%d" % (width, height))
        if img.GetType() == RVC.ImageTypeEnum.Mono8:
            print("This is mono camera")
        else:
            print("This is color camera")

        # 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!")

        # get confidence map
        confidence_map = np.array(x.GetConfidenceMap(), copy=False)
        select_x = width // 2
        select_y = height // 2
        corr_confidence = confidence_map[select_y, select_x]
        print(
            f"the confidence in xy: ({select_x}, {select_y}) is {corr_confidence}")
    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()