neural-mesh-model 1.0.0

Models

• Original NeMo (3D pose estimation)

• 3D aware classification NeMo (3D pose estimation and classification)

• 6D pose estimation NeMo

• (Deformable NeMo ?)

Baselines

• ResNet50

• Starmap

• Transformer

• Faster RCNN

Datasets

• OOD-CV

• Pascal3D+

• (Synthetic data ?)

• (ObjectNet ?)

Python Environment

1. Create conda environment:

conda create -n nemo python=3.9
conda activate nemo

2. Install PyTorch (see pytorch.org):

conda install pytorch==1.12.0 torchvision==0.13.0 torchaudio==0.12.0 cudatoolkit=10.2 -c pytorch

3. Install PyTorch3D (see github.com/facebookresearch/pytorch3d):

conda install -c fvcore -c iopath -c conda-forge fvcore iopath
conda install -c bottler nvidiacub
conda install pytorch3d -c pytorch3d

4. Install other dependencies:

conda install numpy matplotlib scipy scikit-image
conda install pillow
conda install -c conda-forge timm tqdm pyyaml transformers
pip install wget BboxTools opencv-python

2. Install NeMo-Extensions:

pip install -e .

Data Preparation

See data/README.