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arash committed May 20, 2024
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## Getting Started
## Installation

0. You can install the Minkowski Engine with `pip`, with anaconda, or on the system directly.
- [PIP](https://github.com/NVIDIA/MinkowskiEngine#pip) installation
- [Conda](https://github.com/NVIDIA/MinkowskiEngine#anaconda) installation
- [Python](https://github.com/NVIDIA/MinkowskiEngine#system-python) installation
- [Docker](https://github.com/NVIDIA/MinkowskiEngine#docker) installation

1. Create and activate a conda environment:
```sh
conda create --name mink python=3.8
conda activate mink

2. Install Poetry:
1. Install Poetry:
```sh
curl -sSL https://install.python-poetry.org | python3 -

3. Install project dependencies:
poetry install
2. Install project dependencies:
poetry install

4. Set config parameters in config/config.yaml file
3. Set config parameters in config/config.yaml

5. poetry run python src/main.py
4. poetry run python src/main.py

6. python main.py

## Features

### Dependencies
- Unlimited high-dimensional sparse tensor support
- All standard neural network layers (Convolution, Pooling, Broadcast, etc.)
- Dynamic computation graph
- Custom kernel shapes
- Multi-GPU training
- Multi-threaded kernel map
- Multi-threaded compilation
- Highly-optimized GPU kernels

MinkowskiEngine: calculation of sparse tensors

Open3d: manipulation of points (coords), colors and normals
## Requirements

- Ubuntu >= 14.04
- CUDA >= 10.1.243 and **the same CUDA version used for pytorch** (e.g. if you use conda cudatoolkit=11.1, use CUDA=11.1 for MinkowskiEngine compilation)
- pytorch >= 1.7 To specify CUDA version, please use conda for installation. You must match the CUDA version pytorch uses and CUDA version used for Minkowski Engine installation. `conda install -y -c nvidia -c pytorch pytorch=1.8.1 cudatoolkit=10.2`)
- python >= 3.6
- ninja (for installation)
- GCC >= 7.4.0


# Program structure
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<!-- ACKNOWLEDGMENTS -->
## Useful links
## Useful links and other projects using Minkowski Engine

* [Point clouds][Point-clouds]
* [Open3d][open3d-url]
* [Minkowski Engine][MinkowskiEngine-url]
- Segmentation: [3D and 4D Spatio-Temporal Semantic Segmentation, CVPR'19](https://github.com/chrischoy/SpatioTemporalSegmentation)
- Representation Learning: [Fully Convolutional Geometric Features, ICCV'19](https://github.com/chrischoy/FCGF)
- 3D Registration: [Learning multiview 3D point cloud registration, CVPR'20](https://arxiv.org/abs/2001.05119)
- 3D Registration: [Deep Global Registration, CVPR'20](https://arxiv.org/abs/2004.11540)
- Pattern Recognition: [High-Dimensional Convolutional Networks for Geometric Pattern Recognition, CVPR'20](https://arxiv.org/abs/2005.08144)
- Detection: [Generative Sparse Detection Networks for 3D Single-shot Object Detection, ECCV'20](https://arxiv.org/abs/2006.12356)
- Image matching: [Sparse Neighbourhood Consensus Networks, ECCV'20](https://www.di.ens.fr/willow/research/sparse-ncnet/)
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