Metadata-Version: 2.1
Name: sdfest
Version: 0.1.1
Summary: 6-DoF pose, scale, and shape estimation architecture
Home-page: https://github.com/roym899/sdfest
Author: Leonard Bruns
Author-email: roym899@gmail.com
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: cpas_toolbox
Requires-Dist: ffmpeg-python
Requires-Dist: healpy
Requires-Dist: joblib
Requires-Dist: matplotlib
Requires-Dist: ninja
Requires-Dist: numpy
Requires-Dist: open3d
Requires-Dist: pandas
Requires-Dist: pynput
Requires-Dist: pyrender
Requires-Dist: PySide2
Requires-Dist: tensorboard
Requires-Dist: trimesh
Requires-Dist: scipy
Requires-Dist: scikit-image
Requires-Dist: tabulate
Requires-Dist: tqdm
Requires-Dist: torch
Requires-Dist: torchinfo
Requires-Dist: torchvision
Requires-Dist: wandb
Requires-Dist: yoco

# SDFEst
SDFEst is a package for pose, scale, and shape estimation using discretized signed distance fields. It includes and combines three main components (generative model, discriminative initialization, and differentiable renderer) to enable pose and shape estimation in an analysis-by-synthesis framework.

Check the [GitHub page](https://github.com/roym899/sdfest#sdfest) for usage instructions.
