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<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># Copyright (c) Meta Platforms, Inc. and affiliates. All rights reserved.</span>
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<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>
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<h2 id="0.-Install-and-Import-modules">0. Install and Import modules<a class="anchor-link" href="#0.-Install-and-Import-modules"></a></h2>
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<p>Ensure <code>torch</code> and <code>torchvision</code> are installed. If <code>pytorch3d</code> is not installed, install it using the following cell:</p>
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<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">sys</span>
<span class="kn">import</span> <span class="nn">torch</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="ne">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="k">if</span> <span class="n">torch</span><span class="o">.</span><span class="n">__version__</span><span class="o">.</span><span class="n">startswith</span><span class="p">(</span><span class="s2">"2.1."</span><span class="p">)</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="s2">"linux"</span><span class="p">):</span>
<span class="c1"># We try to install PyTorch3D via a released wheel.</span>
<span class="n">pyt_version_str</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">__version__</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s2">"+"</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s2">"."</span><span class="p">,</span> <span class="s2">""</span><span class="p">)</span>
<span class="n">version_str</span><span class="o">=</span><span class="s2">""</span><span class="o">.</span><span class="n">join</span><span class="p">([</span>
<span class="sa">f</span><span class="s2">"py3</span><span class="si">{</span><span class="n">sys</span><span class="o">.</span><span class="n">version_info</span><span class="o">.</span><span class="n">minor</span><span class="si">}</span><span class="s2">_cu"</span><span class="p">,</span>
<span class="n">torch</span><span class="o">.</span><span class="n">version</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s2">"."</span><span class="p">,</span><span class="s2">""</span><span class="p">),</span>
<span class="sa">f</span><span class="s2">"_pyt</span><span class="si">{</span><span class="n">pyt_version_str</span><span class="si">}</span><span class="s2">"</span>
<span class="p">])</span>
<span class="o">!</span>pip<span class="w"> </span>install<span class="w"> </span>fvcore<span class="w"> </span>iopath
<span class="o">!</span>pip<span class="w"> </span>install<span class="w"> </span>--no-index<span class="w"> </span>--no-cache-dir<span class="w"> </span>pytorch3d<span class="w"> </span>-f<span class="w"> </span>https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/<span class="o">{</span>version_str<span class="o">}</span>/download.html
<span class="k">else</span><span class="p">:</span>
<span class="c1"># We try to install PyTorch3D from source.</span>
<span class="o">!</span>pip<span class="w"> </span>install<span class="w"> </span><span class="s1">'git+https://github.com/facebookresearch/pytorch3d.git@stable'</span>
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<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="c1"># Util function for loading meshes</span>
<span class="kn">from</span> <span class="nn">pytorch3d.io</span> <span class="kn">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="kn">import</span> <span class="n">Meshes</span>
<span class="kn">from</span> <span class="nn">pytorch3d.vis.plotly_vis</span> <span class="kn">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="kn">import</span> <span class="n">texturesuv_image_matplotlib</span>
<span class="kn">from</span> <span class="nn">pytorch3d.renderer</span> <span class="kn">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="n">TexturesVertex</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>
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<p>If using <strong>Google Colab</strong>, fetch the utils file for plotting image grids:</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="o">!</span>wget<span class="w"> </span>https://raw.githubusercontent.com/facebookresearch/pytorch3d/main/docs/tutorials/utils/plot_image_grid.py
<span class="kn">from</span> <span class="nn">plot_image_grid</span> <span class="kn">import</span> <span class="n">image_grid</span>
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<p>OR if running <strong>locally</strong> uncomment and run the following cell:</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># from utils import image_grid</span>
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<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 its 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 auxiliary 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>
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<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>
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<div class="highlight hl-ipython3"><pre><span></span><span class="o">!</span>mkdir<span class="w"> </span>-p<span class="w"> </span>data/cow_mesh
<span class="o">!</span>wget<span class="w"> </span>-P<span class="w"> </span>data/cow_mesh<span class="w"> </span>https://dl.fbaipublicfiles.com/pytorch3d/data/cow_mesh/cow.obj
<span class="o">!</span>wget<span class="w"> </span>-P<span class="w"> </span>data/cow_mesh<span class="w"> </span>https://dl.fbaipublicfiles.com/pytorch3d/data/cow_mesh/cow.mtl
<span class="o">!</span>wget<span class="w"> </span>-P<span class="w"> </span>data/cow_mesh<span class="w"> </span>https://dl.fbaipublicfiles.com/pytorch3d/data/cow_mesh/cow_texture.png
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<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>
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<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>
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<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">axis</span><span class="p">(</span><span class="s2">"off"</span><span class="p">);</span>
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<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>
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<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">axis</span><span class="p">(</span><span class="s2">"off"</span><span class="p">);</span>
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<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>
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<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>
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<h2 id="3.-Render-the-mesh">3. Render the mesh<a class="anchor-link" href="#3.-Render-the-mesh"></a></h2>
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<p>The light is in front of the object so it is bright and the image has specular highlights.</p>
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<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">axis</span><span class="p">(</span><span class="s2">"off"</span><span class="p">);</span>
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<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 arbitrary 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>
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<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>
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<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">axis</span><span class="p">(</span><span class="s2">"off"</span><span class="p">);</span>
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<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>
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<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>
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<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>
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<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">axis</span><span class="p">(</span><span class="s2">"off"</span><span class="p">);</span>
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<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>
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<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>
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<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># We can pass arbitrary 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>
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<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>
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<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>
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<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>
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<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>
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<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>
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<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>
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<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>
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<p>For batches, we can also use <code>plot_batch_individually</code> to avoid constructing the scene dictionary ourselves.</p>
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<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>
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<p>We can also modify the axis arguments and axis backgrounds in both functions.</p>
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<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>
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<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>
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<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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