This repo migrate the following work to Python3 and latest PyTorch [v1.3]:
- Learning Category-Specific Mesh Reconstruction from Image Collections (ECCV 2018)
- Neural 3D Mesh Renderer (CVPR 2018)
Special thanks to the them and neural_renderer_pytorch.
What's new here:
- update the code [Python2 -> Python3, PyTorch 0.x -> PyTorch 1.3].
- Remove Chainer/Cupy dependancy (Chainer is depreciated and it's painful to install cupy).
- Simplify the environment setup.
- Slightly reorg and simplify the code.
- Python 3 [Python2 may work as well]
- PyTorch tested on version
1.3.0
conda create -n cmr python=3
conda activate cmr
conda install pytorch torchvision -c pytorch
pip install -r requirements.txt
export CUDA_HOME=/path/to/cuda/
Install CUDA here with the same version as PyTorch python -c 'import torch;print(torch.version.cuda)'
. You may skip it if you alreadly have it in your machine.
Make sure you set the right CUDA_HOME
(e.g. ls $CUDA_HOME/bin/nvcc
works.)
and then build extension
python setup.py install # install to sys.path
python setup.py build develop # install to workspace
- From the
cmr
directory, download the trained model:
cd misc && wget https://people.eecs.berkeley.edu/~kanazawa/cachedir/cmr/model.tar.gz && tar -vzxf model.tar.gz && cd ..
You should see misc/cachedir/snapshots/bird_net/
- Run the demo:
python demo.py --name bird_net --num_train_epoch 500 --img_path misc/demo_data/img1.jpg
python demo.py --name bird_net --num_train_epoch 500 --img_path misc/demo_data/birdie.jpg
Please see train.md
If you use this code for your research, please consider citing:
@inProceedings{cmrKanazawa18,
title={Learning Category-Specific Mesh Reconstruction
from Image Collections},
author = {Angjoo Kanazawa and
Shubham Tulsiani
and Alexei A. Efros
and Jitendra Malik},
booktitle={ECCV},
year={2018}
}
@InProceedings{kato2018renderer
title={Neural 3D Mesh Renderer},
author={Kato, Hiroharu and Ushiku, Yoshitaka and Harada, Tatsuya},
booktitle={The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year={2018}
}