Update latest version of site

2025-12-21 23:00:34 +08:00 · 2020-11-11 10:05:01 -08:00
parent 4277d6a2b5
commit 13e2fd2b5b
57 changed files with 4901 additions and 101 deletions
--- a/tutorials/render_textured_meshes/index.html
+++ b/tutorials/render_textured_meshes/index.html
@@ -6,7 +6,7 @@

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-            </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>
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@@ -115,12 +115,22 @@
 <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">os</span>
 <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>
+    <span class="n">need_pytorch3d</span><span class="o">=</span><span class="kc">False</span>
+    <span class="k">try</span><span class="p">:</span>
+        <span class="kn">import</span> <span class="nn">pytorch3d</span>
+    <span class="k">except</span> <span class="n">ModuleNotFoundError</span><span class="p">:</span>
+        <span class="n">need_pytorch3d</span><span class="o">=</span><span class="kc">True</span>
+    <span class="k">if</span> <span class="n">need_pytorch3d</span><span class="p">:</span>
+        <span class="o">!</span>curl -LO https://github.com/NVIDIA/cub/archive/1.10.0.tar.gz
+        <span class="o">!</span>tar xzf <span class="m">1</span>.10.0.tar.gz
+        <span class="n">os</span><span class="o">.</span><span class="n">environ</span><span class="p">[</span><span class="s2">"CUB_HOME"</span><span class="p">]</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">getcwd</span><span class="p">()</span> <span class="o">+</span> <span class="s2">"/cub-1.10.0"</span>
+        <span class="o">!</span>pip install <span class="s1">'git+https://github.com/facebookresearch/pytorch3d.git@stable'</span>
 </pre></div>
 </div>
 </div>
@@ -141,6 +151,8 @@

 <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.vis.plotly_vis</span> <span class="k">import</span> <span class="n">AxisArgs</span><span class="p">,</span> <span class="n">plot_batch_individually</span><span class="p">,</span> <span class="n">plot_scene</span>
+<span class="kn">from</span> <span class="nn">pytorch3d.vis.texture_vis</span> <span class="k">import</span> <span class="n">texturesuv_image_matplotlib</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> 
@@ -151,7 +163,8 @@
    <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="n">TexturesUV</span><span class="p">,</span>
+    <span class="n">TexturesVertex</span>
 <span class="p">)</span>

 <span class="c1"># add path for demo utils functions </span>
@@ -250,7 +263,6 @@ If running locally, the data is already available at the correct path.</p>

 <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>
@@ -269,9 +281,31 @@ If running locally, the data is already available at the correct path.</p>
 <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">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>
 <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>
+<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">
+<p>PyTorch3D has a built-in way to view the texture map with matplotlib along with the points on the map corresponding to vertices. There is also a method, texturesuv_image_PIL, to get a similar image which can be saved to a file.</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">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">texturesuv_image_matplotlib</span><span class="p">(</span><span class="n">mesh</span><span class="o">.</span><span class="n">textures</span><span class="p">,</span> <span class="n">subsample</span><span class="o">=</span><span class="kc">None</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>
@@ -513,7 +547,201 @@ The renderer and associated components can take batched inputs and <strong>rende
 <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>
+<h2 id="7.-Plotly-visualization">7. Plotly visualization<a class="anchor-link" href="#7.-Plotly-visualization">¶</a></h2><p>If you only want to visualize a mesh, you don't really need to use a differentiable renderer - instead we support plotting of Meshes with plotly. For these Meshes, we use TexturesVertex to define a texture for the rendering.
+<code>plot_meshes</code> creates a Plotly figure with a trace for each Meshes object.</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">verts</span><span class="p">,</span> <span class="n">faces_idx</span><span class="p">,</span> <span class="n">_</span> <span class="o">=</span> <span class="n">load_obj</span><span class="p">(</span><span class="n">obj_filename</span><span class="p">)</span>
+<span class="n">faces</span> <span class="o">=</span> <span class="n">faces_idx</span><span class="o">.</span><span class="n">verts_idx</span>
+
+<span class="c1"># Initialize each vertex to be white in color.</span>
+<span class="n">verts_rgb</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">ones_like</span><span class="p">(</span><span class="n">verts</span><span class="p">)[</span><span class="kc">None</span><span class="p">]</span>  <span class="c1"># (1, V, 3)</span>
+<span class="n">textures</span> <span class="o">=</span> <span class="n">TexturesVertex</span><span class="p">(</span><span class="n">verts_features</span><span class="o">=</span><span class="n">verts_rgb</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">))</span>
+
+<span class="c1"># Create a Meshes object</span>
+<span class="n">mesh</span> <span class="o">=</span> <span class="n">Meshes</span><span class="p">(</span>
+    <span class="n">verts</span><span class="o">=</span><span class="p">[</span><span class="n">verts</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">)],</span>   
+    <span class="n">faces</span><span class="o">=</span><span class="p">[</span><span class="n">faces</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">)],</span>
+    <span class="n">textures</span><span class="o">=</span><span class="n">textures</span>
+<span class="p">)</span>
+
+<span class="c1"># Render the plotly figure</span>
+<span class="n">fig</span> <span class="o">=</span> <span class="n">plot_scene</span><span class="p">({</span>
+    <span class="s2">"subplot1"</span><span class="p">:</span> <span class="p">{</span>
+        <span class="s2">"cow_mesh"</span><span class="p">:</span> <span class="n">mesh</span>
+    <span class="p">}</span>
+<span class="p">})</span>
+<span class="n">fig</span><span class="o">.</span><span class="n">show</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"># use Plotly's default colors (no texture)</span>
+<span class="n">mesh</span> <span class="o">=</span> <span class="n">Meshes</span><span class="p">(</span>
+    <span class="n">verts</span><span class="o">=</span><span class="p">[</span><span class="n">verts</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">)],</span>   
+    <span class="n">faces</span><span class="o">=</span><span class="p">[</span><span class="n">faces</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">)]</span>
+<span class="p">)</span>
+
+<span class="c1"># Render the plotly figure</span>
+<span class="n">fig</span> <span class="o">=</span> <span class="n">plot_scene</span><span class="p">({</span>
+    <span class="s2">"subplot1"</span><span class="p">:</span> <span class="p">{</span>
+        <span class="s2">"cow_mesh"</span><span class="p">:</span> <span class="n">mesh</span>
+    <span class="p">}</span>
+<span class="p">})</span>
+<span class="n">fig</span><span class="o">.</span><span class="n">show</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"># create a batch of meshes, and offset one to prevent overlap</span>
+<span class="n">mesh_batch</span> <span class="o">=</span> <span class="n">Meshes</span><span class="p">(</span>
+    <span class="n">verts</span><span class="o">=</span><span class="p">[</span><span class="n">verts</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">),</span> <span class="p">(</span><span class="n">verts</span> <span class="o">+</span> <span class="mi">2</span><span class="p">)</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">)],</span>   
+    <span class="n">faces</span><span class="o">=</span><span class="p">[</span><span class="n">faces</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">),</span> <span class="n">faces</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">)]</span>
+<span class="p">)</span>
+
+<span class="c1"># plot mesh batch in the same trace</span>
+<span class="n">fig</span> <span class="o">=</span> <span class="n">plot_scene</span><span class="p">({</span>
+    <span class="s2">"subplot1"</span><span class="p">:</span> <span class="p">{</span>
+        <span class="s2">"cow_mesh_batch"</span><span class="p">:</span> <span class="n">mesh_batch</span>
+    <span class="p">}</span>
+<span class="p">})</span>
+<span class="n">fig</span><span class="o">.</span><span class="n">show</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"># plot batch of meshes in different traces</span>
+<span class="n">fig</span> <span class="o">=</span> <span class="n">plot_scene</span><span class="p">({</span>
+    <span class="s2">"subplot1"</span><span class="p">:</span> <span class="p">{</span>
+        <span class="s2">"cow_mesh1"</span><span class="p">:</span> <span class="n">mesh_batch</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span>
+        <span class="s2">"cow_mesh2"</span><span class="p">:</span> <span class="n">mesh_batch</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
+    <span class="p">}</span>
+<span class="p">})</span>
+<span class="n">fig</span><span class="o">.</span><span class="n">show</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"># plot batch of meshes in different subplots</span>
+<span class="n">fig</span> <span class="o">=</span> <span class="n">plot_scene</span><span class="p">({</span>
+    <span class="s2">"subplot1"</span><span class="p">:</span> <span class="p">{</span>
+        <span class="s2">"cow_mesh1"</span><span class="p">:</span> <span class="n">mesh_batch</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
+    <span class="p">},</span>
+    <span class="s2">"subplot2"</span><span class="p">:{</span>
+        <span class="s2">"cow_mesh2"</span><span class="p">:</span> <span class="n">mesh_batch</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
+    <span class="p">}</span>
+<span class="p">})</span>
+<span class="n">fig</span><span class="o">.</span><span class="n">show</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>For batches, we can also use <code>plot_batch_individually</code> to avoid constructing the scene dictionary ourselves.</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"># extend the batch to have 4 meshes</span>
+<span class="n">mesh_4</span> <span class="o">=</span> <span class="n">mesh_batch</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span>
+
+<span class="c1"># visualize the batch in different subplots, 2 per row</span>
+<span class="n">fig</span> <span class="o">=</span> <span class="n">plot_batch_individually</span><span class="p">(</span><span class="n">mesh_4</span><span class="p">)</span>
+<span class="c1"># we can update the figure height and width</span>
+<span class="n">fig</span><span class="o">.</span><span class="n">update_layout</span><span class="p">(</span><span class="n">height</span><span class="o">=</span><span class="mi">1000</span><span class="p">,</span> <span class="n">width</span><span class="o">=</span><span class="mi">500</span><span class="p">)</span>
+<span class="n">fig</span><span class="o">.</span><span class="n">show</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>We can also modify the axis arguments and axis backgrounds in both functions.</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">fig2</span> <span class="o">=</span> <span class="n">plot_scene</span><span class="p">({</span>
+    <span class="s2">"cow_plot1"</span><span class="p">:</span> <span class="p">{</span>
+        <span class="s2">"cows"</span><span class="p">:</span> <span class="n">mesh_batch</span>
+    <span class="p">}</span>
+<span class="p">},</span>
+    <span class="n">xaxis</span><span class="o">=</span><span class="p">{</span><span class="s2">"backgroundcolor"</span><span class="p">:</span><span class="s2">"rgb(200, 200, 230)"</span><span class="p">},</span>
+    <span class="n">yaxis</span><span class="o">=</span><span class="p">{</span><span class="s2">"backgroundcolor"</span><span class="p">:</span><span class="s2">"rgb(230, 200, 200)"</span><span class="p">},</span>
+    <span class="n">zaxis</span><span class="o">=</span><span class="p">{</span><span class="s2">"backgroundcolor"</span><span class="p">:</span><span class="s2">"rgb(200, 230, 200)"</span><span class="p">},</span> 
+    <span class="n">axis_args</span><span class="o">=</span><span class="n">AxisArgs</span><span class="p">(</span><span class="n">showgrid</span><span class="o">=</span><span class="kc">True</span><span class="p">))</span>
+<span class="n">fig2</span><span class="o">.</span><span class="n">show</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">fig3</span> <span class="o">=</span> <span class="n">plot_batch_individually</span><span class="p">(</span>
+    <span class="n">mesh_4</span><span class="p">,</span> 
+    <span class="n">ncols</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span>
+    <span class="n">subplot_titles</span> <span class="o">=</span> <span class="p">[</span><span class="s2">"cow1"</span><span class="p">,</span> <span class="s2">"cow2"</span><span class="p">,</span> <span class="s2">"cow3"</span><span class="p">,</span> <span class="s2">"cow4"</span><span class="p">],</span> <span class="c1"># customize subplot titles</span>
+    <span class="n">xaxis</span><span class="o">=</span><span class="p">{</span><span class="s2">"backgroundcolor"</span><span class="p">:</span><span class="s2">"rgb(200, 200, 230)"</span><span class="p">},</span>
+    <span class="n">yaxis</span><span class="o">=</span><span class="p">{</span><span class="s2">"backgroundcolor"</span><span class="p">:</span><span class="s2">"rgb(230, 200, 200)"</span><span class="p">},</span>
+    <span class="n">zaxis</span><span class="o">=</span><span class="p">{</span><span class="s2">"backgroundcolor"</span><span class="p">:</span><span class="s2">"rgb(200, 230, 200)"</span><span class="p">},</span> 
+    <span class="n">axis_args</span><span class="o">=</span><span class="n">AxisArgs</span><span class="p">(</span><span class="n">showgrid</span><span class="o">=</span><span class="kc">True</span><span class="p">))</span>
+<span class="n">fig3</span><span class="o">.</span><span class="n">show</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="8.-Conclusion">8. Conclusion<a class="anchor-link" href="#8.-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. We also learned how to render Meshes in Plotly figures.</p>
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