pytorch3d/tutorials/render_textured_meshes.html
2020-08-26 22:27:07 -07:00

520 lines
44 KiB
HTML
Raw Blame History

This file contains invisible Unicode characters

This file contains invisible Unicode characters that are indistinguishable to humans but may be processed differently by a computer. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.

This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.

<!DOCTYPE html><html lang=""><head><meta charSet="utf-8"/><meta http-equiv="X-UA-Compatible" content="IE=edge"/><title>PyTorch3D · A library for deep learning with 3D data</title><meta name="viewport" content="width=device-width"/><meta name="generator" content="Docusaurus"/><meta name="description" content="A library for deep learning with 3D data"/><meta property="og:title" content="PyTorch3D · A library for deep learning with 3D data"/><meta property="og:type" content="website"/><meta property="og:url" content="https://pytorch3d.org/"/><meta property="og:description" content="A library for deep learning with 3D data"/><meta property="og:image" content="https://pytorch3d.org/img/pytorch3dlogoicon.svg"/><meta name="twitter:card" content="summary"/><meta name="twitter:image" content="https://pytorch3d.org/img/pytorch3dlogoicon.svg"/><link rel="shortcut icon" href="/img/pytorch3dfavicon.png"/><link rel="stylesheet" href="//cdnjs.cloudflare.com/ajax/libs/highlight.js/9.12.0/styles/default.min.css"/><script>
(function(i,s,o,g,r,a,m){i['GoogleAnalyticsObject']=r;i[r]=i[r]||function(){
(i[r].q=i[r].q||[]).push(arguments)},i[r].l=1*new Date();a=s.createElement(o),
m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m)
})(window,document,'script','https://www.google-analytics.com/analytics.js','ga');
ga('create', 'UA-157376881-1', 'auto');
ga('send', 'pageview');
</script><script type="text/javascript" src="https://buttons.github.io/buttons.js"></script><script src="/js/scrollSpy.js"></script><link rel="stylesheet" href="/css/main.css"/><script src="/js/codetabs.js"></script></head><body><div class="fixedHeaderContainer"><div class="headerWrapper wrapper"><header><a href="/"><img class="logo" src="/img/pytorch3dfavicon.png" alt="PyTorch3D"/><h2 class="headerTitleWithLogo">PyTorch3D</h2></a><div class="navigationWrapper navigationSlider"><nav class="slidingNav"><ul class="nav-site nav-site-internal"><li class=""><a href="/docs/why_pytorch3d" target="_self">Docs</a></li><li class=""><a href="/tutorials" target="_self">Tutorials</a></li><li class=""><a href="https://pytorch3d.readthedocs.io/" target="_self">API</a></li><li class=""><a href="https://github.com/facebookresearch/pytorch3d" target="_self">GitHub</a></li></ul></nav></div></header></div></div><div class="navPusher"><div class="docMainWrapper wrapper"><div class="container docsNavContainer" id="docsNav"><nav class="toc"><div class="toggleNav"><section class="navWrapper wrapper"><div class="navBreadcrumb wrapper"><div class="navToggle" id="navToggler"><div class="hamburger-menu"><div class="line1"></div><div class="line2"></div><div class="line3"></div></div></div><h2><i></i><span></span></h2><div class="tocToggler" id="tocToggler"><i class="icon-toc"></i></div></div><div class="navGroups"><div class="navGroup"><h3 class="navGroupCategoryTitle">Tutorials</h3><ul class=""><li class="navListItem"><a class="navItem" href="/tutorials/">Overview</a></li></ul></div><div class="navGroup"><h3 class="navGroupCategoryTitle">3D operators</h3><ul class=""><li class="navListItem"><a class="navItem" href="/tutorials/deform_source_mesh_to_target_mesh">Fit Mesh</a></li><li class="navListItem"><a class="navItem" href="/tutorials/bundle_adjustment">Bundle Adjustment</a></li></ul></div><div class="navGroup"><h3 class="navGroupCategoryTitle">Rendering</h3><ul class=""><li class="navListItem navListItemActive"><a class="navItem" href="/tutorials/render_textured_meshes">Render Textured Meshes</a></li><li class="navListItem"><a class="navItem" href="/tutorials/fit_textured_mesh">Fit a mesh with texture via rendering</a></li><li class="navListItem"><a class="navItem" href="/tutorials/camera_position_optimization_with_differentiable_rendering">Camera Position Optimization</a></li></ul></div><div class="navGroup"><h3 class="navGroupCategoryTitle">Dataloaders</h3><ul class=""><li class="navListItem"><a class="navItem" href="/tutorials/dataloaders_ShapeNetCore_R2N2">Data loaders for ShapeNetCore and R2N2</a></li></ul></div></div></section></div><script>
var coll = document.getElementsByClassName('collapsible');
var checkActiveCategory = true;
for (var i = 0; i < coll.length; i++) {
var links = coll[i].nextElementSibling.getElementsByTagName('*');
if (checkActiveCategory){
for (var j = 0; j < links.length; j++) {
if (links[j].classList.contains('navListItemActive')){
coll[i].nextElementSibling.classList.toggle('hide');
coll[i].childNodes[1].classList.toggle('rotate');
checkActiveCategory = false;
break;
}
}
}
coll[i].addEventListener('click', function() {
var arrow = this.childNodes[1];
arrow.classList.toggle('rotate');
var content = this.nextElementSibling;
content.classList.toggle('hide');
});
}
document.addEventListener('DOMContentLoaded', function() {
createToggler('#navToggler', '#docsNav', 'docsSliderActive');
createToggler('#tocToggler', 'body', 'tocActive');
var headings = document.querySelector('.toc-headings');
headings && headings.addEventListener('click', function(event) {
var el = event.target;
while(el !== headings){
if (el.tagName === 'A') {
document.body.classList.remove('tocActive');
break;
} else{
el = el.parentNode;
}
}
}, false);
function createToggler(togglerSelector, targetSelector, className) {
var toggler = document.querySelector(togglerSelector);
var target = document.querySelector(targetSelector);
if (!toggler) {
return;
}
toggler.onclick = function(event) {
event.preventDefault();
target.classList.toggle(className);
};
}
});
</script></nav></div><div class="container mainContainer"><div class="wrapper"><div class="tutorialButtonsWrapper"><div class="tutorialButtonWrapper buttonWrapper"><a class="tutorialButton button" download="" href="https://colab.research.google.com/github/facebookresearch/pytorch3d/blob/stable/docs/tutorials/render_textured_meshes.ipynb" target="_blank"><img class="colabButton" align="left" src="/img/colab_icon.png"/>Run in Google Colab</a></div><div class="tutorialButtonWrapper buttonWrapper"><a class="tutorialButton button" download="" href="/files/render_textured_meshes.ipynb" target="_blank"><svg aria-hidden="true" focusable="false" data-prefix="fas" data-icon="file-download" class="svg-inline--fa fa-file-download fa-w-12" role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 384 512"><path fill="currentColor" d="M224 136V0H24C10.7 0 0 10.7 0 24v464c0 13.3 10.7 24 24 24h336c13.3 0 24-10.7 24-24V160H248c-13.2 0-24-10.8-24-24zm76.45 211.36l-96.42 95.7c-6.65 6.61-17.39 6.61-24.04 0l-96.42-95.7C73.42 337.29 80.54 320 94.82 320H160v-80c0-8.84 7.16-16 16-16h32c8.84 0 16 7.16 16 16v80h65.18c14.28 0 21.4 17.29 11.27 27.36zM377 105L279.1 7c-4.5-4.5-10.6-7-17-7H256v128h128v-6.1c0-6.3-2.5-12.4-7-16.9z"></path></svg>Download Tutorial Jupyter Notebook</a></div><div class="tutorialButtonWrapper buttonWrapper"><a class="tutorialButton button" download="" href="/files/render_textured_meshes.py" target="_blank"><svg aria-hidden="true" focusable="false" data-prefix="fas" data-icon="file-download" class="svg-inline--fa fa-file-download fa-w-12" role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 384 512"><path fill="currentColor" d="M224 136V0H24C10.7 0 0 10.7 0 24v464c0 13.3 10.7 24 24 24h336c13.3 0 24-10.7 24-24V160H248c-13.2 0-24-10.8-24-24zm76.45 211.36l-96.42 95.7c-6.65 6.61-17.39 6.61-24.04 0l-96.42-95.7C73.42 337.29 80.54 320 94.82 320H160v-80c0-8.84 7.16-16 16-16h32c8.84 0 16 7.16 16 16v80h65.18c14.28 0 21.4 17.29 11.27 27.36zM377 105L279.1 7c-4.5-4.5-10.6-7-17-7H256v128h128v-6.1c0-6.3-2.5-12.4-7-16.9z"></path></svg>Download Tutorial Source Code</a></div></div><div class="tutorialBody">
<script
src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.1.10/require.min.js">
</script>
<script
src="https://cdnjs.cloudflare.com/ajax/libs/jquery/2.0.3/jquery.min.js">
</script>
<div class="notebook">
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In [ ]:</div>
<div class="inner_cell">
<div class="input_area">
<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.</span>
</pre></div>
</div>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h1 id="Render-a-textured-mesh">Render a textured mesh<a class="anchor-link" href="#Render-a-textured-mesh"></a></h1><p>This tutorial shows how to:</p>
<ul>
<li>load a mesh and textures from an <code>.obj</code> file. </li>
<li>set up a renderer </li>
<li>render the mesh </li>
<li>vary the rendering settings such as lighting and camera position</li>
<li>use the batching features of the pytorch3d API to render the mesh from different viewpoints</li>
</ul>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h2 id="0.-Install-and-Import-modules">0. Install and Import modules<a class="anchor-link" href="#0.-Install-and-Import-modules"></a></h2>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>If <code>torch</code>, <code>torchvision</code> and <code>pytorch3d</code> are not installed, run the following cell:</p>
</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In [ ]:</div>
<div class="inner_cell">
<div class="input_area">
<div class="highlight hl-ipython3"><pre><span></span><span class="o">!</span>pip install torch torchvision
<span class="kn">import</span> <span class="nn">sys</span>
<span class="kn">import</span> <span class="nn">torch</span>
<span class="k">if</span> <span class="n">torch</span><span class="o">.</span><span class="n">__version__</span><span class="o">==</span><span class="s1">'1.6.0+cu101'</span> <span class="ow">and</span> <span class="n">sys</span><span class="o">.</span><span class="n">platform</span><span class="o">.</span><span class="n">startswith</span><span class="p">(</span><span class="s1">'linux'</span><span class="p">):</span>
<span class="o">!</span>pip install pytorch3d
<span class="k">else</span><span class="p">:</span>
<span class="o">!</span>pip install <span class="s1">'git+https://github.com/facebookresearch/pytorch3d.git@stable'</span>
</pre></div>
</div>
</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In [ ]:</div>
<div class="inner_cell">
<div class="input_area">
<div class="highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">os</span>
<span class="kn">import</span> <span class="nn">torch</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">from</span> <span class="nn">skimage.io</span> <span class="k">import</span> <span class="n">imread</span>
<span class="c1"># Util function for loading meshes</span>
<span class="kn">from</span> <span class="nn">pytorch3d.io</span> <span class="k">import</span> <span class="n">load_objs_as_meshes</span><span class="p">,</span> <span class="n">load_obj</span>
<span class="c1"># Data structures and functions for rendering</span>
<span class="kn">from</span> <span class="nn">pytorch3d.structures</span> <span class="k">import</span> <span class="n">Meshes</span>
<span class="kn">from</span> <span class="nn">pytorch3d.renderer</span> <span class="k">import</span> <span class="p">(</span>
<span class="n">look_at_view_transform</span><span class="p">,</span>
<span class="n">FoVPerspectiveCameras</span><span class="p">,</span>
<span class="n">PointLights</span><span class="p">,</span>
<span class="n">DirectionalLights</span><span class="p">,</span>
<span class="n">Materials</span><span class="p">,</span>
<span class="n">RasterizationSettings</span><span class="p">,</span>
<span class="n">MeshRenderer</span><span class="p">,</span>
<span class="n">MeshRasterizer</span><span class="p">,</span>
<span class="n">SoftPhongShader</span><span class="p">,</span>
<span class="n">TexturesUV</span>
<span class="p">)</span>
<span class="c1"># add path for demo utils functions </span>
<span class="kn">import</span> <span class="nn">sys</span>
<span class="kn">import</span> <span class="nn">os</span>
<span class="n">sys</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">abspath</span><span class="p">(</span><span class="s1">''</span><span class="p">))</span>
</pre></div>
</div>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>If using <strong>Google Colab</strong>, fetch the utils file for plotting image grids:</p>
</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In [ ]:</div>
<div class="inner_cell">
<div class="input_area">
<div class="highlight hl-ipython3"><pre><span></span><span class="o">!</span>wget https://raw.githubusercontent.com/facebookresearch/pytorch3d/master/docs/tutorials/utils/plot_image_grid.py
<span class="kn">from</span> <span class="nn">plot_image_grid</span> <span class="k">import</span> <span class="n">image_grid</span>
</pre></div>
</div>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>OR if running <strong>locally</strong> uncomment and run the following cell:</p>
</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In [ ]:</div>
<div class="inner_cell">
<div class="input_area">
<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># from utils import image_grid</span>
</pre></div>
</div>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="1.-Load-a-mesh-and-texture-file">1. Load a mesh and texture file<a class="anchor-link" href="#1.-Load-a-mesh-and-texture-file"></a></h3><p>Load an <code>.obj</code> file and it's associated <code>.mtl</code> file and create a <strong>Textures</strong> and <strong>Meshes</strong> object.</p>
<p><strong>Meshes</strong> is a unique datastructure provided in PyTorch3D for working with batches of meshes of different sizes.</p>
<p><strong>TexturesUV</strong> is an auxillary datastructure for storing vertex uv and texture maps for meshes.</p>
<p><strong>Meshes</strong> has several class methods which are used throughout the rendering pipeline.</p>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>If running this notebook using <strong>Google Colab</strong>, run the following cell to fetch the mesh obj and texture files and save it at the path <code>data/cow_mesh</code>:
If running locally, the data is already available at the correct path.</p>
</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In [ ]:</div>
<div class="inner_cell">
<div class="input_area">
<div class="highlight hl-ipython3"><pre><span></span><span class="o">!</span>mkdir -p data/cow_mesh
<span class="o">!</span>wget -P data/cow_mesh https://dl.fbaipublicfiles.com/pytorch3d/data/cow_mesh/cow.obj
<span class="o">!</span>wget -P data/cow_mesh https://dl.fbaipublicfiles.com/pytorch3d/data/cow_mesh/cow.mtl
<span class="o">!</span>wget -P data/cow_mesh https://dl.fbaipublicfiles.com/pytorch3d/data/cow_mesh/cow_texture.png
</pre></div>
</div>
</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In [ ]:</div>
<div class="inner_cell">
<div class="input_area">
<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># Setup</span>
<span class="k">if</span> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">is_available</span><span class="p">():</span>
<span class="n">device</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">device</span><span class="p">(</span><span class="s2">"cuda:0"</span><span class="p">)</span>
<span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">set_device</span><span class="p">(</span><span class="n">device</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">device</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">device</span><span class="p">(</span><span class="s2">"cpu"</span><span class="p">)</span>
<span class="c1"># Set paths</span>
<span class="n">DATA_DIR</span> <span class="o">=</span> <span class="s2">"./data"</span>
<span class="n">obj_filename</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">DATA_DIR</span><span class="p">,</span> <span class="s2">"cow_mesh/cow.obj"</span><span class="p">)</span>
<span class="c1"># Load obj file</span>
<span class="n">mesh</span> <span class="o">=</span> <span class="n">load_objs_as_meshes</span><span class="p">([</span><span class="n">obj_filename</span><span class="p">],</span> <span class="n">device</span><span class="o">=</span><span class="n">device</span><span class="p">)</span>
<span class="n">texture_image</span><span class="o">=</span><span class="n">mesh</span><span class="o">.</span><span class="n">textures</span><span class="o">.</span><span class="n">maps_padded</span><span class="p">()</span>
</pre></div>
</div>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h4 id="Let's-visualize-the-texture-map">Let's visualize the texture map<a class="anchor-link" href="#Let's-visualize-the-texture-map"></a></h4>
</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In [ ]:</div>
<div class="inner_cell">
<div class="input_area">
<div class="highlight hl-ipython3"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">7</span><span class="p">,</span><span class="mi">7</span><span class="p">))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">texture_image</span><span class="o">.</span><span class="n">squeeze</span><span class="p">()</span><span class="o">.</span><span class="n">cpu</span><span class="p">()</span><span class="o">.</span><span class="n">numpy</span><span class="p">())</span>
<span class="n">plt</span><span class="o">.</span><span class="n">grid</span><span class="p">(</span><span class="s2">"off"</span><span class="p">);</span>
<span class="n">plt</span><span class="o">.</span><span class="n">axis</span><span class="p">(</span><span class="s1">'off'</span><span class="p">);</span>
</pre></div>
</div>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h2 id="2.-Create-a-renderer">2. Create a renderer<a class="anchor-link" href="#2.-Create-a-renderer"></a></h2><p>A renderer in PyTorch3D is composed of a <strong>rasterizer</strong> and a <strong>shader</strong> which each have a number of subcomponents such as a <strong>camera</strong> (orthographic/perspective). Here we initialize some of these components and use default values for the rest.</p>
<p>In this example we will first create a <strong>renderer</strong> which uses a <strong>perspective camera</strong>, a <strong>point light</strong> and applies <strong>phong shading</strong>. Then we learn how to vary different components using the modular API.</p>
</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In [ ]:</div>
<div class="inner_cell">
<div class="input_area">
<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># Initialize a camera.</span>
<span class="c1"># With world coordinates +Y up, +X left and +Z in, the front of the cow is facing the -Z direction. </span>
<span class="c1"># So we move the camera by 180 in the azimuth direction so it is facing the front of the cow. </span>
<span class="n">R</span><span class="p">,</span> <span class="n">T</span> <span class="o">=</span> <span class="n">look_at_view_transform</span><span class="p">(</span><span class="mf">2.7</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">180</span><span class="p">)</span>
<span class="n">cameras</span> <span class="o">=</span> <span class="n">FoVPerspectiveCameras</span><span class="p">(</span><span class="n">device</span><span class="o">=</span><span class="n">device</span><span class="p">,</span> <span class="n">R</span><span class="o">=</span><span class="n">R</span><span class="p">,</span> <span class="n">T</span><span class="o">=</span><span class="n">T</span><span class="p">)</span>
<span class="c1"># Define the settings for rasterization and shading. Here we set the output image to be of size</span>
<span class="c1"># 512x512. As we are rendering images for visualization purposes only we will set faces_per_pixel=1</span>
<span class="c1"># and blur_radius=0.0. We also set bin_size and max_faces_per_bin to None which ensure that </span>
<span class="c1"># the faster coarse-to-fine rasterization method is used. Refer to rasterize_meshes.py for </span>
<span class="c1"># explanations of these parameters. Refer to docs/notes/renderer.md for an explanation of </span>
<span class="c1"># the difference between naive and coarse-to-fine rasterization. </span>
<span class="n">raster_settings</span> <span class="o">=</span> <span class="n">RasterizationSettings</span><span class="p">(</span>
<span class="n">image_size</span><span class="o">=</span><span class="mi">512</span><span class="p">,</span>
<span class="n">blur_radius</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span>
<span class="n">faces_per_pixel</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span>
<span class="p">)</span>
<span class="c1"># Place a point light in front of the object. As mentioned above, the front of the cow is facing the </span>
<span class="c1"># -z direction. </span>
<span class="n">lights</span> <span class="o">=</span> <span class="n">PointLights</span><span class="p">(</span><span class="n">device</span><span class="o">=</span><span class="n">device</span><span class="p">,</span> <span class="n">location</span><span class="o">=</span><span class="p">[[</span><span class="mf">0.0</span><span class="p">,</span> <span class="mf">0.0</span><span class="p">,</span> <span class="o">-</span><span class="mf">3.0</span><span class="p">]])</span>
<span class="c1"># Create a phong renderer by composing a rasterizer and a shader. The textured phong shader will </span>
<span class="c1"># interpolate the texture uv coordinates for each vertex, sample from a texture image and </span>
<span class="c1"># apply the Phong lighting model</span>
<span class="n">renderer</span> <span class="o">=</span> <span class="n">MeshRenderer</span><span class="p">(</span>
<span class="n">rasterizer</span><span class="o">=</span><span class="n">MeshRasterizer</span><span class="p">(</span>
<span class="n">cameras</span><span class="o">=</span><span class="n">cameras</span><span class="p">,</span>
<span class="n">raster_settings</span><span class="o">=</span><span class="n">raster_settings</span>
<span class="p">),</span>
<span class="n">shader</span><span class="o">=</span><span class="n">SoftPhongShader</span><span class="p">(</span>
<span class="n">device</span><span class="o">=</span><span class="n">device</span><span class="p">,</span>
<span class="n">cameras</span><span class="o">=</span><span class="n">cameras</span><span class="p">,</span>
<span class="n">lights</span><span class="o">=</span><span class="n">lights</span>
<span class="p">)</span>
<span class="p">)</span>
</pre></div>
</div>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h2 id="3.-Render-the-mesh">3. Render the mesh<a class="anchor-link" href="#3.-Render-the-mesh"></a></h2>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>The light is in front of the object so it is bright and the image has specular highlights.</p>
</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In [ ]:</div>
<div class="inner_cell">
<div class="input_area">
<div class="highlight hl-ipython3"><pre><span></span><span class="n">images</span> <span class="o">=</span> <span class="n">renderer</span><span class="p">(</span><span class="n">mesh</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">images</span><span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="p">:</span><span class="mi">3</span><span class="p">]</span><span class="o">.</span><span class="n">cpu</span><span class="p">()</span><span class="o">.</span><span class="n">numpy</span><span class="p">())</span>
<span class="n">plt</span><span class="o">.</span><span class="n">grid</span><span class="p">(</span><span class="s2">"off"</span><span class="p">);</span>
<span class="n">plt</span><span class="o">.</span><span class="n">axis</span><span class="p">(</span><span class="s2">"off"</span><span class="p">);</span>
</pre></div>
</div>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h2 id="4.-Move-the-light-behind-the-object-and-re-render">4. Move the light behind the object and re-render<a class="anchor-link" href="#4.-Move-the-light-behind-the-object-and-re-render"></a></h2><p>We can pass arbirary keyword arguments to the <code>rasterizer</code>/<code>shader</code> via the call to the <code>renderer</code> so the renderer does not need to be reinitialized if any of the settings change/</p>
<p>In this case, we can simply update the location of the lights and pass them into the call to the renderer.</p>
<p>The image is now dark as there is only ambient lighting, and there are no specular highlights.</p>
</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In [ ]:</div>
<div class="inner_cell">
<div class="input_area">
<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># Now move the light so it is on the +Z axis which will be behind the cow. </span>
<span class="n">lights</span><span class="o">.</span><span class="n">location</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">([</span><span class="mf">0.0</span><span class="p">,</span> <span class="mf">0.0</span><span class="p">,</span> <span class="o">+</span><span class="mf">1.0</span><span class="p">],</span> <span class="n">device</span><span class="o">=</span><span class="n">device</span><span class="p">)[</span><span class="kc">None</span><span class="p">]</span>
<span class="n">images</span> <span class="o">=</span> <span class="n">renderer</span><span class="p">(</span><span class="n">mesh</span><span class="p">,</span> <span class="n">lights</span><span class="o">=</span><span class="n">lights</span><span class="p">)</span>
</pre></div>
</div>
</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In [ ]:</div>
<div class="inner_cell">
<div class="input_area">
<div class="highlight hl-ipython3"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">images</span><span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="p">:</span><span class="mi">3</span><span class="p">]</span><span class="o">.</span><span class="n">cpu</span><span class="p">()</span><span class="o">.</span><span class="n">numpy</span><span class="p">())</span>
<span class="n">plt</span><span class="o">.</span><span class="n">grid</span><span class="p">(</span><span class="s2">"off"</span><span class="p">);</span>
<span class="n">plt</span><span class="o">.</span><span class="n">axis</span><span class="p">(</span><span class="s2">"off"</span><span class="p">);</span>
</pre></div>
</div>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h2 id="5.-Rotate-the-object,-modify-the-material-properties-or-light-properties">5. Rotate the object, modify the material properties or light properties<a class="anchor-link" href="#5.-Rotate-the-object,-modify-the-material-properties-or-light-properties"></a></h2><p>We can also change many other settings in the rendering pipeline. Here we:</p>
<ul>
<li>change the <strong>viewing angle</strong> of the camera</li>
<li>change the <strong>position</strong> of the point light</li>
<li>change the <strong>material reflectance</strong> properties of the mesh</li>
</ul>
</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In [ ]:</div>
<div class="inner_cell">
<div class="input_area">
<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># Rotate the object by increasing the elevation and azimuth angles</span>
<span class="n">R</span><span class="p">,</span> <span class="n">T</span> <span class="o">=</span> <span class="n">look_at_view_transform</span><span class="p">(</span><span class="n">dist</span><span class="o">=</span><span class="mf">2.7</span><span class="p">,</span> <span class="n">elev</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">azim</span><span class="o">=-</span><span class="mi">150</span><span class="p">)</span>
<span class="n">cameras</span> <span class="o">=</span> <span class="n">FoVPerspectiveCameras</span><span class="p">(</span><span class="n">device</span><span class="o">=</span><span class="n">device</span><span class="p">,</span> <span class="n">R</span><span class="o">=</span><span class="n">R</span><span class="p">,</span> <span class="n">T</span><span class="o">=</span><span class="n">T</span><span class="p">)</span>
<span class="c1"># Move the light location so the light is shining on the cow's face. </span>
<span class="n">lights</span><span class="o">.</span><span class="n">location</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">([[</span><span class="mf">2.0</span><span class="p">,</span> <span class="mf">2.0</span><span class="p">,</span> <span class="o">-</span><span class="mf">2.0</span><span class="p">]],</span> <span class="n">device</span><span class="o">=</span><span class="n">device</span><span class="p">)</span>
<span class="c1"># Change specular color to green and change material shininess </span>
<span class="n">materials</span> <span class="o">=</span> <span class="n">Materials</span><span class="p">(</span>
<span class="n">device</span><span class="o">=</span><span class="n">device</span><span class="p">,</span>
<span class="n">specular_color</span><span class="o">=</span><span class="p">[[</span><span class="mf">0.0</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">,</span> <span class="mf">0.0</span><span class="p">]],</span>
<span class="n">shininess</span><span class="o">=</span><span class="mf">10.0</span>
<span class="p">)</span>
<span class="c1"># Re render the mesh, passing in keyword arguments for the modified components.</span>
<span class="n">images</span> <span class="o">=</span> <span class="n">renderer</span><span class="p">(</span><span class="n">mesh</span><span class="p">,</span> <span class="n">lights</span><span class="o">=</span><span class="n">lights</span><span class="p">,</span> <span class="n">materials</span><span class="o">=</span><span class="n">materials</span><span class="p">,</span> <span class="n">cameras</span><span class="o">=</span><span class="n">cameras</span><span class="p">)</span>
</pre></div>
</div>
</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In [ ]:</div>
<div class="inner_cell">
<div class="input_area">
<div class="highlight hl-ipython3"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">images</span><span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="p">:</span><span class="mi">3</span><span class="p">]</span><span class="o">.</span><span class="n">cpu</span><span class="p">()</span><span class="o">.</span><span class="n">numpy</span><span class="p">())</span>
<span class="n">plt</span><span class="o">.</span><span class="n">grid</span><span class="p">(</span><span class="s2">"off"</span><span class="p">);</span>
<span class="n">plt</span><span class="o">.</span><span class="n">axis</span><span class="p">(</span><span class="s2">"off"</span><span class="p">);</span>
</pre></div>
</div>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h2 id="6.-Batched-Rendering">6. Batched Rendering<a class="anchor-link" href="#6.-Batched-Rendering"></a></h2><p>One of the core design choices of the PyTorch3D API is to support <strong>batched inputs for all components</strong>.
The renderer and associated components can take batched inputs and <strong>render a batch of output images in one forward pass</strong>. We will now use this feature to render the mesh from many different viewpoints.</p>
</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In [ ]:</div>
<div class="inner_cell">
<div class="input_area">
<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># Set batch size - this is the number of different viewpoints from which we want to render the mesh.</span>
<span class="n">batch_size</span> <span class="o">=</span> <span class="mi">20</span>
<span class="c1"># Create a batch of meshes by repeating the cow mesh and associated textures. </span>
<span class="c1"># Meshes has a useful `extend` method which allows us do this very easily. </span>
<span class="c1"># This also extends the textures. </span>
<span class="n">meshes</span> <span class="o">=</span> <span class="n">mesh</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="n">batch_size</span><span class="p">)</span>
<span class="c1"># Get a batch of viewing angles. </span>
<span class="n">elev</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">180</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">)</span>
<span class="n">azim</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="o">-</span><span class="mi">180</span><span class="p">,</span> <span class="mi">180</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">)</span>
<span class="c1"># All the cameras helper methods support mixed type inputs and broadcasting. So we can </span>
<span class="c1"># view the camera from the same distance and specify dist=2.7 as a float,</span>
<span class="c1"># and then specify elevation and azimuth angles for each viewpoint as tensors. </span>
<span class="n">R</span><span class="p">,</span> <span class="n">T</span> <span class="o">=</span> <span class="n">look_at_view_transform</span><span class="p">(</span><span class="n">dist</span><span class="o">=</span><span class="mf">2.7</span><span class="p">,</span> <span class="n">elev</span><span class="o">=</span><span class="n">elev</span><span class="p">,</span> <span class="n">azim</span><span class="o">=</span><span class="n">azim</span><span class="p">)</span>
<span class="n">cameras</span> <span class="o">=</span> <span class="n">FoVPerspectiveCameras</span><span class="p">(</span><span class="n">device</span><span class="o">=</span><span class="n">device</span><span class="p">,</span> <span class="n">R</span><span class="o">=</span><span class="n">R</span><span class="p">,</span> <span class="n">T</span><span class="o">=</span><span class="n">T</span><span class="p">)</span>
<span class="c1"># Move the light back in front of the cow which is facing the -z direction.</span>
<span class="n">lights</span><span class="o">.</span><span class="n">location</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">([[</span><span class="mf">0.0</span><span class="p">,</span> <span class="mf">0.0</span><span class="p">,</span> <span class="o">-</span><span class="mf">3.0</span><span class="p">]],</span> <span class="n">device</span><span class="o">=</span><span class="n">device</span><span class="p">)</span>
</pre></div>
</div>
</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In [ ]:</div>
<div class="inner_cell">
<div class="input_area">
<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># We can pass arbirary keyword arguments to the rasterizer/shader via the renderer</span>
<span class="c1"># so the renderer does not need to be reinitialized if any of the settings change.</span>
<span class="n">images</span> <span class="o">=</span> <span class="n">renderer</span><span class="p">(</span><span class="n">meshes</span><span class="p">,</span> <span class="n">cameras</span><span class="o">=</span><span class="n">cameras</span><span class="p">,</span> <span class="n">lights</span><span class="o">=</span><span class="n">lights</span><span class="p">)</span>
</pre></div>
</div>
</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In [ ]:</div>
<div class="inner_cell">
<div class="input_area">
<div class="highlight hl-ipython3"><pre><span></span><span class="n">image_grid</span><span class="p">(</span><span class="n">images</span><span class="o">.</span><span class="n">cpu</span><span class="p">()</span><span class="o">.</span><span class="n">numpy</span><span class="p">(),</span> <span class="n">rows</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span> <span class="n">cols</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="n">rgb</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
</pre></div>
</div>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h2 id="7.-Conclusion">7. Conclusion<a class="anchor-link" href="#7.-Conclusion"></a></h2><p>In this tutorial we learnt how to <strong>load</strong> a textured mesh from an obj file, initialize a PyTorch3D datastructure called <strong>Meshes</strong>, set up an <strong>Renderer</strong> consisting of a <strong>Rasterizer</strong> and a <strong>Shader</strong>, and modify several components of the rendering pipeline.</p>
</div>
</div>
</div>
</div></div></div></div></div><footer class="nav-footer" id="footer"><section class="sitemap"><div class="footerSection"><div class="social"><a class="github-button" href="https://github.com/facebookresearch/pytorch3d" data-count-href="https://github.com/facebookresearch/pytorch3d/stargazers" data-show-count="true" data-count-aria-label="# stargazers on GitHub" aria-label="Star PyTorch3D on GitHub">pytorch3d</a></div></div></section><a href="https://opensource.facebook.com/" target="_blank" rel="noreferrer noopener" class="fbOpenSource"><img src="/img/oss_logo.png" alt="Facebook Open Source" width="170" height="45"/></a><section class="copyright">Copyright © 2020 Facebook Inc<br/>Legal:<a href="https://opensource.facebook.com/legal/privacy/" target="_blank" rel="noreferrer noopener">Privacy</a><a href="https://opensource.facebook.com/legal/terms/" target="_blank" rel="noreferrer noopener">Terms</a></section></footer></div></body></html>