{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Exploration of 3D Indoor Scenes Datasets"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Install useful dependencies for data exploration"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"hideCode": false,
"hideOutput": true,
"hidePrompt": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Collecting xmltodict\n",
" Downloading xmltodict-0.12.0-py2.py3-none-any.whl (9.2 kB)\n",
"Installing collected packages: xmltodict\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"WARNING: pip is being invoked by an old script wrapper. This will fail in a future version of pip.\n",
"Please see https://github.com/pypa/pip/issues/5599 for advice on fixing the underlying issue.\n",
"To avoid this problem you can invoke Python with '-m pip' instead of running pip directly.\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Successfully installed xmltodict-0.12.0\n"
]
}
],
"source": [
"import pip\n",
"\n",
"def install(package):\n",
" if hasattr(pip, 'main'):\n",
" pip.main(['install', package])\n",
" else:\n",
" pip._internal.main(['install', package])\n",
"\n",
"# install('panda3d')\n",
"# install('ursina')\n",
"# install('ipyvolume')\n",
"# install('plotly')\n",
"# install('pyquaternion')\n",
"# install('xmltodict')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Explore SceneNN scene"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Copy minimalist scene data as string \"sample_scene_data\""
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"hideCode": true,
"hideOutput": true,
"hidePrompt": false
},
"outputs": [],
"source": [
"sample_scene_data = \"\"\"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
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"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"\"\"\""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Load scene data as xml tree element"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"OrderedDict([('@id', '716508'),\n",
" ('@color', '21 156 162'),\n",
" ('@text', ''),\n",
" ('@nyu_class', 'wall'),\n",
" ('@note', ''),\n",
" ('@area', '492477'),\n",
" ('@obbox',\n",
" '-1.2153 -2.52873 -1.90061 4.76056 2.89713 3.58827 0.999386 0.0115122 0.0173149 0.02819'),\n",
" ('@aabbox',\n",
" '-1.19997 -0.368718 -1.66073 3.51822 2.43698 1.86119'),\n",
" ('@local_pose', '1 0 0 0')])"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import xmltodict\n",
"labels = xmltodict.parse(sample_scene_data)['annotation']['label']\n",
"sample_label = labels[0]\n",
"# sample_label"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [],
"source": [
"import pyquaternion\n",
"\n",
"def obbox_properties_to_vertices(obbox_properties):\n",
" \"\"\"\n",
" Convert 3D box properties (center, dimensions, and quaternion)\n",
" \"\"\"\n",
" if isinstance(obbox_properties, str):\n",
" obbox_properties = list(map(float, obbox_properties.split()))\n",
" \n",
"# TODO ADD EXTRA CHECKS\n",
"# if isinstance(obbox_properties, iterable) and len(obbox_properties == 10) and \n",
" \n",
" # Extract properties\n",
" cx, cy, cz = obbox_properties[0:3]\n",
" dx, dy, dz = obbox_properties[3:6]\n",
" qx, qy, qz, qw = obbox_properties[6:10]\n",
"\n",
" # Constants for converting properties to vertices\n",
" X = [0, 0, 1, 1, 0, 0, 1, 1]\n",
" Y = [0, 1, 1, 0, 0, 1, 1, 0]\n",
" Z = [0, 0, 0, 0, 1, 1, 1, 1]\n",
"\n",
" # Properties to unrotated vertices\n",
" x = [cx + (-0.5 * dx if v == 0 else 0.5 * dx) for v in X]\n",
" y = [cy + (-0.5 * dy if v == 0 else 0.5 * dy) for v in Y]\n",
" z = [cz + (-0.5 * dz if v == 0 else 0.5 * dz) for v in Z]\n",
" unrotated_vertices = zip(x, y, z)\n",
" \n",
" # Apply quaternion\n",
" quaternion = pyquaternion.Quaternion(qw, qx, qy, qz)\n",
" unrotated_vectors = [(v[0] - cx, v[1] - cy, v[2] - cz) for v in unrotated_vertices]\n",
" vectors = [quaternion.rotate(v) for v in unrotated_vectors]\n",
" vertices = [(v[0] + cx, v[1] + cy, v[2] + cz) for v in vectors]\n",
" \n",
" x, y, z = zip(*vertices)\n",
" \n",
" return x, y, z"
]
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {},
"outputs": [],
"source": [
"import plotly.graph_objects as go\n",
"import numpy as np\n",
"\n",
"def label_to_mesh_3d(label, color='magenta'):\n",
" x, y, z = obbox_properties_to_vertices(label['@obbox'])\n",
" mesh_3d = go.Mesh3d(\n",
" x=x, y=y, z=z,\n",
" color=color,\n",
" opacity=0.5,\n",
" # i, j and k give the vertices of triangles\n",
" i = [7, 0, 0, 0, 4, 4, 6, 6, 4, 0, 3, 2],\n",
" j = [3, 4, 1, 2, 5, 6, 5, 2, 0, 1, 6, 3],\n",
" k = [0, 7, 2, 3, 6, 7, 1, 1, 5, 5, 7, 6],\n",
" name=label['@nyu_class'],\n",
" showscale=True\n",
" )\n",
" return mesh_3d\n",
"\n",
"def plot_obbox(obbox):\n",
" x, y, z = obbox_properties_to_vertices(obbox)\n",
" fig = go.Figure(data=[\n",
" go.Mesh3d(\n",
" x=x, y=y, z=z,\n",
" color='magenta',\n",
" opacity=0.5,\n",
" # i, j and k give the vertices of triangles\n",
" i = [7, 0, 0, 0, 4, 4, 6, 6, 4, 0, 3, 2],\n",
" j = [3, 4, 1, 2, 5, 6, 5, 2, 0, 1, 6, 3],\n",
" k = [0, 7, 2, 3, 6, 7, 1, 1, 5, 5, 7, 6],\n",
" name='y',\n",
" showscale=True\n",
" )\n",
" ])\n",
" return fig\n",
"\n",
"# fig.show()"
]
},
{
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"execution_count": 52,
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