{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 点云数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of points: (678418, 3)\n",
      "Elevation range: [1753.949951171875, 1786.7099609375]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"100%\"\n",
       "            height=\"650\"\n",
       "            src=\"http://127.0.0.1:8050/\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "            \n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x1630d16a250>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import dash\n",
    "import dash_vtk\n",
    "from dash import html, dcc\n",
    "from dash.dependencies import Input, Output, State\n",
    "\n",
    "import numpy as np\n",
    "from pyvista import examples\n",
    "\n",
    "np.random.seed(42)\n",
    "\n",
    "# Get point cloud data from PyVista\n",
    "dataset = examples.download_lidar()\n",
    "subset = 0.2\n",
    "selection = np.random.randint(\n",
    "    low=0, high=dataset.n_points - 1, size=int(dataset.n_points * subset)\n",
    ")\n",
    "points = dataset.points[selection]\n",
    "xyz = points.ravel()\n",
    "elevation = points[:, -1].ravel()\n",
    "min_elevation = np.amin(elevation)\n",
    "max_elevation = np.amax(elevation)\n",
    "print(f\"Number of points: {points.shape}\")\n",
    "print(f\"Elevation range: [{min_elevation}, {max_elevation}]\")\n",
    "\n",
    "# Setup VTK rendering of PointCloud\n",
    "app = dash.Dash(__name__)\n",
    "server = app.server\n",
    "\n",
    "vtk_view = dash_vtk.View(\n",
    "    [\n",
    "        dash_vtk.PointCloudRepresentation(\n",
    "            xyz=xyz,\n",
    "            scalars=elevation,\n",
    "            colorDataRange=[min_elevation, max_elevation],\n",
    "            property={\"pointSize\": 2},\n",
    "        )\n",
    "    ]\n",
    ")\n",
    "\n",
    "app.layout = html.Div(\n",
    "    style={\"height\": \"calc(100vh - 16px)\"},\n",
    "    children=[html.Div(vtk_view, style={\"height\": \"100%\", \"width\": \"100%\"})],\n",
    ")\n",
    "\n",
    "if __name__ == \"__main__\":\n",
    "    app.run_server(debug=True, port=8891)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "也可以直接使用 `open3d` 加载 `.ply` 文件："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of points: (8192, 3)\n",
      "Elevation range: [-0.340668, 0.300229]\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import open3d\n",
    "\n",
    "pcd = open3d.io.read_point_cloud(\"test.ply\")\n",
    "points = np.asarray(pcd.points)\n",
    "xyz = points.ravel()\n",
    "elevation = points[:, -1].ravel()\n",
    "min_elevation = np.amin(elevation)\n",
    "max_elevation = np.amax(elevation)\n",
    "print(f\"Number of points: {points.shape}\")\n",
    "print(f\"Elevation range: [{min_elevation}, {max_elevation}]\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "codemirror_mode": {
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