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Toolbox and trackers for object pose-estimation. Based on the work CosyPose and MegaPose

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HappyPose

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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

This installation procedure will be curated.

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

Installation of bop_toolkit :

conda activate happypose
cd happypose/pose_estimators/megapose/deps/bop_toolkit_challenge/
# Remove all versions enforcing on requirements.txt
pip install -r requirements.txt -e .

Create data directory

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

Configuration for the evaluation

If you plan on evaluating CosyPose and Megapose, you need to modify the following lines in bop_toolkit_lib/config.py, replace

######## Basic ########


# Folder with the BOP datasets.
if 'BOP_PATH' in os.environ:
  datasets_path = os.environ['BOP_PATH']
else:
  datasets_path = r'/path/to/bop/datasets'

# Folder with pose results to be evaluated.
results_path = r'/path/to/folder/with/results'

# Folder for the calculated pose errors and performance scores.
eval_path = r'/path/to/eval/folder'

with

######## Basic ########

# Folder with the BOP datasets.
datasets_path = str(os.environ['BOP_DATASETS_PATH'])
results_path = str(os.environ['BOP_RESULTS_PATH'])
eval_path = str(os.environ['BOP_EVAL_PATH'])

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Toolbox and trackers for object pose-estimation. Based on the work CosyPose and MegaPose

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