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updates for v0.7.0
This commit is contained in:
Jeremy Francis Reizenstein
@@ -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"><a class="navItem" href="/tutorials/render_textured_meshes">Render Textured Meshes</a></li><li class="navListItem"><a class="navItem" href="/tutorials/render_densepose">Render DensePose Meshes</a></li><li class="navListItem"><a class="navItem" href="/tutorials/render_colored_points">Render Colored Pointclouds</a></li><li class="navListItem navListItemActive"><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 with Differentiable Rendering</a></li><li class="navListItem"><a class="navItem" href="/tutorials/fit_textured_volume">Fit a volume via raymarching</a></li><li class="navListItem"><a class="navItem" href="/tutorials/fit_simple_neural_radiance_field">Fit a simplified NeRF via raymarching</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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</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"><a class="navItem" href="/tutorials/render_textured_meshes">Render Textured Meshes</a></li><li class="navListItem"><a class="navItem" href="/tutorials/render_densepose">Render DensePose Meshes</a></li><li class="navListItem"><a class="navItem" href="/tutorials/render_colored_points">Render Colored Pointclouds</a></li><li class="navListItem navListItemActive"><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 with Differentiable Rendering</a></li><li class="navListItem"><a class="navItem" href="/tutorials/fit_textured_volume">Fit a volume via raymarching</a></li><li class="navListItem"><a class="navItem" href="/tutorials/fit_simple_neural_radiance_field">Fit a simplified NeRF via raymarching</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 class="navGroup"><h3 class="navGroupCategoryTitle">Implicitron</h3><ul class=""><li class="navListItem"><a class="navItem" href="/tutorials/implicitron_volumes">Training a custom volumes function with implicitron</a></li><li class="navListItem"><a class="navItem" href="/tutorials/implicitron_config_system">Implicitron config system deep dive</a></li></ul></div></div></section></div><script>
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@@ -125,7 +125,7 @@
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<span class="k">except</span> <span class="ne">ModuleNotFoundError</span><span class="p">:</span>
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<span class="n">need_pytorch3d</span><span class="o">=</span><span class="kc">True</span>
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<span class="k">if</span> <span class="n">need_pytorch3d</span><span class="p">:</span>
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<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">"1.10."</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>
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<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">"1.12."</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>
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<span class="c1"># We try to install PyTorch3D via a released wheel.</span>
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<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>
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<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>
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@@ -173,7 +173,7 @@
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<span class="kn">from</span> <span class="nn">pytorch3d.structures</span> <span class="kn">import</span> <span class="n">Meshes</span>
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<span class="kn">from</span> <span class="nn">pytorch3d.renderer</span> <span class="kn">import</span> <span class="p">(</span>
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<span class="n">look_at_view_transform</span><span class="p">,</span>
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<span class="n">OpenGLPerspectiveCameras</span><span class="p">,</span>
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<span class="n">FoVPerspectiveCameras</span><span class="p">,</span>
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<span class="n">PointLights</span><span class="p">,</span>
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<span class="n">DirectionalLights</span><span class="p">,</span>
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<span class="n">Materials</span><span class="p">,</span>
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@@ -331,11 +331,11 @@ If running locally, the data is already available at the correct path.</p>
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<span class="c1"># broadcasting. So we can view the camera from the a distance of dist=2.7, and </span>
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<span class="c1"># then specify elevation and azimuth angles for each viewpoint as tensors. </span>
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<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>
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<span class="n">cameras</span> <span class="o">=</span> <span class="n">OpenGLPerspectiveCameras</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>
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<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>
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<span class="c1"># We arbitrarily choose one particular view that will be used to visualize </span>
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<span class="c1"># results</span>
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<span class="n">camera</span> <span class="o">=</span> <span class="n">OpenGLPerspectiveCameras</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="kc">None</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="o">...</span><span class="p">],</span>
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<span class="n">camera</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="kc">None</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="o">...</span><span class="p">],</span>
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<span class="n">T</span><span class="o">=</span><span class="n">T</span><span class="p">[</span><span class="kc">None</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="o">...</span><span class="p">])</span>
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<span class="c1"># Define the settings for rasterization and shading. Here we set the output </span>
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@@ -378,7 +378,7 @@ If running locally, the data is already available at the correct path.</p>
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<span class="c1"># Our multi-view cow dataset will be represented by these 2 lists of tensors,</span>
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<span class="c1"># each of length num_views.</span>
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<span class="n">target_rgb</span> <span class="o">=</span> <span class="p">[</span><span class="n">target_images</span><span class="p">[</span><span class="n">i</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="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">num_views</span><span class="p">)]</span>
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<span class="n">target_cameras</span> <span class="o">=</span> <span class="p">[</span><span class="n">OpenGLPerspectiveCameras</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="kc">None</span><span class="p">,</span> <span class="n">i</span><span class="p">,</span> <span class="o">...</span><span class="p">],</span>
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<span class="n">target_cameras</span> <span class="o">=</span> <span class="p">[</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="kc">None</span><span class="p">,</span> <span class="n">i</span><span class="p">,</span> <span class="o">...</span><span class="p">],</span>
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<span class="n">T</span><span class="o">=</span><span class="n">T</span><span class="p">[</span><span class="kc">None</span><span class="p">,</span> <span class="n">i</span><span class="p">,</span> <span class="o">...</span><span class="p">])</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">num_views</span><span class="p">)]</span>
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</pre></div>
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</div>
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@@ -697,6 +697,7 @@ If running locally, the data is already available at the correct path.</p>
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<span class="n">image_size</span><span class="o">=</span><span class="mi">128</span><span class="p">,</span>
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<span class="n">blur_radius</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="mf">1.</span> <span class="o">/</span> <span class="mf">1e-4</span> <span class="o">-</span> <span class="mf">1.</span><span class="p">)</span><span class="o">*</span><span class="n">sigma</span><span class="p">,</span>
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<span class="n">faces_per_pixel</span><span class="o">=</span><span class="mi">50</span><span class="p">,</span>
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<span class="n">perspective_correct</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
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<span class="p">)</span>
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<span class="c1"># Differentiable soft renderer using per vertex RGB colors for texture</span>
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