將.pcd文件可視化爲鳥瞰圖（俯視圖）

首先，你可以用pcl庫中的 pcl_viewer 3D可視化 .pcd 文件。
在做3D檢測的時候可能需要用到鳥瞰圖來檢查效果，所以寫了這麼個功能:
這裏需要注意的 .pcd 不能爲二進制文件，否則不能直接讀取。

import numpy as np
import cv2

def lidar_to_bird_view_img(lidar, factor=4):
    # Input:
    #   lidar: (N', 4)
    #   factor: 越大清晰度越高
    # Output:
    #   birdview: (w, l, 3)
    birdview = np.zeros(
        (INPUT_HEIGHT * factor, INPUT_WIDTH * factor, 1))
    for point in lidar:
        x, y = point[0:2]
        if X_MIN < x < X_MAX and Y_MIN < y < Y_MAX:
            x, y = int((x - X_MIN) / VOXEL_X_SIZE *
                       factor), int((y - Y_MIN) / VOXEL_Y_SIZE * factor)
            birdview[y, x] += 1
    birdview = birdview - np.min(birdview)
    divisor = np.max(birdview) - np.min(birdview)
    # TODO: adjust this factor
    birdview = np.clip((birdview / divisor * 255) *
                       5 * factor, a_min=0, a_max=255)
    birdview = np.tile(birdview, 3).astype(np.uint8)

    return birdview

# 限定可視化範圍
INPUT_HEIGHT = 400
INPUT_WIDTH = 352
X_MIN = 0
X_MAX = 70.4
Y_MIN = -40
Y_MAX = 40
VOXEL_X_SIZE = 0.2
VOXEL_Y_SIZE = 0.2


lidar = []
with open('000000.pcd','r') as f:
    line = f.readline().strip()
    while line:
        linestr = line.split(" ")
        if len(linestr) == 4:
        	# 將str類型轉換爲float類型
            linestr_convert = list(map(float, linestr))
            lidar.append(linestr_convert)
        line = f.readline().strip()

bird_view  = lidar_to_bird_view_img(lidar)
bird_view_path = '000000.jpg'
cv2.imwrite( bird_view_path, bird_view )

顯示效果如下: