python - 使用 Laspy 模块的 Python 中的 Houdini 自定义 LiDAR 导入器

Question

我正在尝试使用 Python 为 Houdini 构建一个自定义 LiDAR 导入器。到目前为止，Laspy 模块 ( https://pypi.org/project/laspy ) 通过在 Houdini 中读取和写入 *.*las 文件以及过滤分类来完成一项快速而快速的工作。

但是我必须读取和写入 *.*las 文件并再次导入，而不是立即获取 Houdini 中的点。

现在我想知道，是否可以获取 LiDAR 点 xyz 位置，以将它们提供给 Houdini 内部的点。

我试图在 Laspy 手册中找到有用的信息，但找不到任何示例或功能。

我用 *.*csv 文件做了类似的事情，它有 xyz 位置来构建一个简单的 GPS 阅读器，以将位置输出为 Houdini 中的点（使用 csv 模块）。

我附上了原始 .las（灰色）和过滤后的 output.las（红色屋顶）的屏幕截图以及来自 Laspy 手册的脚本示例。

也许代替 Laspy 有一个更优雅的解决方案？我在 Houdini 中使用 Python 3，但 2.7 也可以。

更新，这里的答案几乎完美 https://forums.odforce.net/topic/46475-custom-lidar-importer-with-python/?tab=comments#comment-217104：

from laspy.file import File
import numpy as np

node = hou.pwd()
geo = node.geometry()

file_path = geo.attribValue("file_path")
inFile = File(file_path, mode='r')

# --- load point position
coords = np.vstack((inFile.x, inFile.y, inFile.z)).transpose()
scale = np.array(inFile.header.scale)
offset = np.array(inFile.header.offset) # there is no offset in simple.las example from laspy library
# offset = np.array([1000, 20000, 100000])  # just for testing that offset works

# geo.setPointFloatAttribValues("P", np.concatenate(coords))    # same as Lidar Import SOP - seems that it ignores scale (and offset?)
geo.setPointFloatAttribValues("P", np.concatenate(coords*scale+offset))

# --- load color
color = np.vstack((inFile.red, inFile.green, inFile.blue)).transpose()
geo.addAttrib(hou.attribType.Point, "Cd", (1.0,1.0,1.0), False, False)  # add color atttribute
geo.setPointFloatAttribValues("Cd", np.concatenate(color / 255.0)) # transform from 1-255 to 0.0-1.0 range)

唯一不起作用的是 inFile.classifications == x 这使 Houdini 崩溃。

标签： pythonclassificationlidarhoudini

Answer 1

来自 Odforce 的 Petr 完成了 LiDAR Importer。 https://forums.odforce.net/topic/46475-custom-lidar-importer-with-python/

要加载和读取点：

from laspy.file import File
node = hou.pwd()
geo = node.geometry()
geo.createPoint()   # dummy point for point generate

classification = hou.evalParm("classification")
file_path = hou.evalParm("lidar_file")
inFile = File(file_path, mode='r')
# store how many points lidar attribute has
geo.addAttrib(hou.attribType.Global, "nb_of_points", 0, False, False)
geo.setGlobalAttribValue("nb_of_points", len(inFile.points[inFile.Classification == classification]))

# store file path
geo.addAttrib(hou.attribType.Global, "file_path", "", False, False)
geo.setGlobalAttribValue("file_path", file_path)

# store classification
geo.addAttrib(hou.attribType.Global, "classification", 0, False, False)
geo.setGlobalAttribValue("classification", classification)

# find availible information
pointformat = inFile.point_format
for spec in inFile.point_format:
    print(spec.name)

并加载属性：

from laspy.file import File
import numpy as np

node = hou.pwd()
geo = node.geometry()

file_path = geo.attribValue("file_path")
inFile = File(file_path, mode='r')
classification = geo.attribValue("classification")

selection = inFile.Classification == classification
points = inFile.points[selection]



# --- load point position
coords = np.vstack((inFile.x, inFile.y, inFile.z)).transpose()
scale = np.array(inFile.header.scale)
offset = np.array(inFile.header.offset) # there is no offset in simple.las example from laspy library
# offset = np.array([1000, 20000, 100000])  # just for testing that offset works

# geo.setPointFloatAttribValues("P", np.concatenate(coords))    # same as Lidar Import SOP - seems that it ignores scale (and offset?)
geo.setPointFloatAttribValues("P", np.concatenate(coords[selection]*scale+offset))

# --- load color
missing_color = ["red", "green", "blue"]
for spec in inFile.point_format:
    if spec.name in missing_color:
        missing_color.remove(spec.name)

if not missing_color:       
    color = np.vstack((inFile.red, inFile.green, inFile.blue)).transpose()
    geo.addAttrib(hou.attribType.Point, "Cd", (1.0,1.0,1.0), False, False)  # add color atttribute
    geo.setPointFloatAttribValues("Cd", np.concatenate(color[selection] / 255.0)) # transform from 1-255 to 0.0-1.0 range)

# --- load intensity
geo.addAttrib(hou.attribType.Point, "intensity", 0.0, False, False)  # add intensity atttribute
geo.setPointFloatAttribValues("intensity", inFile.intensity[selection] / 512.0) # transform from 1-255 to 0.0-1.0 range)