点云转灰度图+点云转RGB图的python实现

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于 2024-08-09 11:44:18 发布 · 797 阅读

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#python #numpy #开发语言

点云转灰度图脚本

import numpy as np
import pcl
import cv2


def test_cloud2gray():
    # 点云转灰度图
    xy_ratio = 100
    z_ratio = 100
    # path = r"D:\Downloads\rule_pointcloud\two_tree.pcd"
    path = r"D:\code\script\3d_detect\data\BGA_3D\yishi_2710\bga_speed-12_expose-120us-frequecy-1000.pcd"
    cloud = pcl.load(path)
    points = cloud.to_array()
    point_x = points[:, 0]
    point_y = points[:, 1]
    point_z = points[:, 2]

    min_x = min(point_x)
    offset_x = 0
    if min_x < 0:
        offset_x = abs(min_x)
    point_x = point_x + offset_x
    point_x = point_x * xy_ratio

    min_y = min(point_y)
    offset_y = 0
    if min_y < 0:
        offset_y = abs(min_y)
    point_y = point_y + offset_y
    point_y = point_y * xy_ratio

    min_z = min(point_z)
    offset_z = 0
    if min_z < 0:
        offset_z = abs(min_z)
    point_z = point_z + offset_z
    point_z = point_z * z_ratio
    # 归一化
    max_z = max(point_z)
    point_z = point_z / max_z * 255  #将取值范围划分到0~255
    print(point_z)

    # 创建画布
    max_x = int(max(point_x)) + 100
    max_y = int(max(point_y)) + 100
    print(f"create template size: x: {max_x}, y:{max_y}")
    background_img = np.zeros((max_y, max_x), np.uint8)
    # cv2.imwrite("background.jpg", background_img)

    # 将点位画上
    n_point_x = np.expand_dims(point_x, axis=1)
    n_point_y = np.expand_dims(point_y, axis=1)
    point_xy = np.array(np.concatenate((n_point_x, n_point_y), axis=1), dtype=np.uint32)
    for index, point in enumerate(point_xy):
        y, x = point[0], point[1]
        background_img[x, y] = int(point_z[index])
    cv2.imwrite("background_bga-1.jpg", backgroun