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Copy file name to clipboardExpand all lines: README.md
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@@ -10,9 +10,9 @@ PyQt5 app for viewing SMAL meshes
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cd SMALViewer
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```
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2. Clone the [SMAL-ST](http://smal.is.tue.mpg.de/) project website, and access the latest version of the SMAL deformable animal model. You should copy all of [these files](https://github.com/silviazuffi/smalst/tree/master/smpl_models) underneath the ./data directory.
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2. Clone the [SMAL-ST](http://smal.is.tue.mpg.de/) project website in order to access the latest version of the SMAL deformable animal model. You should copy all of [these files](https://github.com/silviazuffi/smalst/tree/master/smpl_models) underneath a SMALViewer/data directory.
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Pro-tip: If you are a Windows user, you can still use these files but you'll need to edit the line endings. Try the following Powershell commands, shown here on one example:
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Windows tip: If you are a Windows user, you can use these files but you'll need to edit the line endings. Try the following Powershell commands, shown here on one example:
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os.environ['PYOPENGL_PLATFORM'] = 'osmesa'.
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```
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If you are a Windows user and you experience issues here, you can fix by following the advice [here](https://github.com/mmatl/pyrender/issues/117). A quick fix is to edit the function "make_current" in pyrender/platforms/pyglet_platform.py, L53 (wherever it's installed for you) to:
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If you are a Windows user and you experience issues with OffscreenRenderer, you can fix by following the advice [here](https://github.com/mmatl/pyrender/issues/117). A quick fix is to edit the function "make_current" in pyrender/platforms/pyglet_platform.py, L53 (wherever it's installed for you) to:
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```
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def make_uncurrent(self):
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```
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python smal_viewer.py
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```
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## Differentiable Rendering (Sample)
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## Differentiable Rendering
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For many research applications, it is useful to be able to propagate gradients from 2D losses (e.g. silhouette/perceptual) back through the rendering process. For this, one should use a differentiable render such as [PyTorch3D](https://github.com/facebookresearch/pytorch3d) or [Neural Mesh Renderer](https://github.com/daniilidis-group/neural_renderer). Although not usful for this simple demo app, I have included a script p3d_renderer.py which shows how one can achieve differentiable rendering of the SMAL mesh with PyTorch3D. You can flip between the two rendering methods by selecting between the two imports at the top of pyqt_viewer.py:
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