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Jeremy Reizenstein 6c4151a820 Remove _read_image from densepose example 
Summary:
As noted in #601, the example notebook was using an internal function _read_image from PyTorch3D, which has changed signature recently. It is not meant to be used externally. Switch to using PIL directly.

Other changes: (1) removed unused skimage import. (2) some small tidyups. We now don't have places where cells modify values set by other cells. (3) removed bad calls to `plt.grid` which have no effect.

Reviewed By: theschnitz, nikhilaravi

Differential Revision: D27080372

fbshipit-source-id: 2fce651b3e5d7a4619f0a2b298c5db18c8fa1e2c
2021-03-17 16:13:36 -07:00
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data
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utils
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bundle_adjustment.ipynb
update notebooks for s3 wheels
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camera_position_optimization_with_differentiable_rendering.ipynb
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dataloaders_ShapeNetCore_R2N2.ipynb
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deform_source_mesh_to_target_mesh.ipynb
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fit_simple_neural_radiance_field.ipynb
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fit_textured_mesh.ipynb
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fit_textured_volume.ipynb
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README.md
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render_colored_points.ipynb
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render_densepose.ipynb
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render_textured_meshes.ipynb
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README.md

Tutorial notebooks

For current versions of the tutorials, which correspond to the latest release, please look at this directory at the stable tag, namely at https://github.com/facebookresearch/pytorch3d/tree/stable/docs/tutorials .

There are links at the project homepage for opening these directly in colab.

They install PyTorch3D from pip, which should work inside a GPU colab notebook. If you need to install PyTorch3D from source inside colab, you can use

import os
!curl -LO https://github.com/NVIDIA/cub/archive/1.10.0.tar.gz
!tar xzf 1.10.0.tar.gz
os.environ["CUB_HOME"] = os.getcwd() + "/cub-1.10.0"
!pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'`

instead.

The versions of these tutorials on the main branch may need to use the latest PyTorch3D from the main branch. You may be able to install this from source with the same commands as above, but replacing the last line with !pip install 'git+https://github.com/facebookresearch/pytorch3d.git'.