HappyPose

Toolbox and trackers for object pose-estimation. Based on the work CosyPose and MegaPose. This directory is currently under development. Please refer to the documentation for more details.

Installation

To install happypose, you can use pip or poetry.

We strongly suggest to install it in either a venv or a conda environment.

Example with conda

git clone --branch dev --recurse-submodules https://github.com/agimus-project/happypose.git
cd happypose
conda env create -f environment.yml
conda activate happypose
pip install .

Example with venv

git clone --branch dev --recurse-submodules https://github.com/agimus-project/happypose.git
cd happypose
python -m venv .venv
source .venv/bin/activate
pip install .[pypi,cpu] --extra-index-url https://download.pytorch.org/whl/cpu

Install extras:

• cpu: required to get pytorch CPU from PyPI (don't use this for GPU or with conda)
• gpu: required to get pytorch GPU from PyPI (don't use this for CPU or with conda)
• multiview: installs cosypose c++ extension
• pypi: install pinocchio & opencv from PyPI (don't use this with conda)

Create data directory

Create data dir /somewhere/convenient. The dataset to store are quite large.
export HAPPYPOSE_DATA_DIR=/somewhere/convenient