<h1 align="center">
<br>
pmeshlab
<br>
<br>
<img src="https://drive.google.com/uc?id=1adCikDmjjDULmn-3R7_wpyyJX-nzKlHb">
</h1>
<p align="center">
<a href="#modules">Modules</a> •
<a href="#installing-the-application">Installing the application</a> •
<a href="#makefile-commands">Makefile commands</a> •
<a href="#environments">Environments</a> •
<a href="#running-the-application">Running the application</a>
<a href="#ressources">Ressources</a>
</p>
pmeshlab is a Python package that provides two high-level features:
- A simple Mesh processor
- A list of tool to convert mesh files into point cloud
You can reuse your favorite Python packages such as NumPy, SciPy and Cython to extend ZakuroCache integration.
# Modules
At a granular level, pmeshlab is a library that consists of the following components:
| Component | Description |
| ---- | --- |
| **pmeshlab** | Contains the implementation of pmeshlab |
# Installing the application
To clone and run this application, you'll need the following installed on your computer:
- [Git](https://git-scm.com)
- Docker Desktop
- [Install Docker Desktop on Mac](https://docs.docker.com/docker-for-mac/install/)
- [Install Docker Desktop on Windows](https://docs.docker.com/desktop/install/windows-install/)
- [Install Docker Desktop on Linux](https://docs.docker.com/desktop/install/linux-install/)
- [Python](https://www.python.org/downloads/)
Install the package:
```bash
# Clone this repository and install the code
git clone https://github.com/JeanMaximilienCadic/pmeshlab
# Go into the repository
cd pmeshlab
```
# Makefile commands
Exhaustive list of make commands:
```
install_wheels
sandbox_cpu
sandbox_gpu
build_sandbox
push_environment
push_container_sandbox
push_container_vanilla
pull_container_vanilla
pull_container_sandbox
build_vanilla
build_wheels
auto_branch
```
# Environments
## Docker
> **Note**
>
> Running this application by using Docker is recommended.
To build and run the docker image
```
make build
make sandbox
```
## PythonEnv
> **Warning**
>
> Running this application by using PythonEnv is possible but *not* recommended.
```
make install_wheels
```
## Ressources
* Vanilla: https://en.wikipedia.org/wiki/Vanilla_software
* Sandbox: https://en.wikipedia.org/wiki/Sandbox_(software_development)
* All you need is docker: https://www.theregister.com/2014/05/23/google_containerization_two_billion/
* Dev in containers : https://code.visualstudio.com/docs/remote/containers
* Delta lake partitions: https://k21academy.com/microsoft-azure/data-engineer/delta-lake/
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"description": "<h1 align=\"center\">\n <br>\n pmeshlab\n <br>\n <br>\n <img src=\"https://drive.google.com/uc?id=1adCikDmjjDULmn-3R7_wpyyJX-nzKlHb\">\n</h1>\n\n<p align=\"center\">\n <a href=\"#modules\">Modules</a> \u2022\n <a href=\"#installing-the-application\">Installing the application</a> \u2022\n <a href=\"#makefile-commands\">Makefile commands</a> \u2022\n <a href=\"#environments\">Environments</a> \u2022\n <a href=\"#running-the-application\">Running the application</a>\n <a href=\"#ressources\">Ressources</a>\n</p>\n\n\npmeshlab is a Python package that provides two high-level features:\n- A simple Mesh processor\n- A list of tool to convert mesh files into point cloud\n\nYou can reuse your favorite Python packages such as NumPy, SciPy and Cython to extend ZakuroCache integration.\n\n\n# Modules\n\nAt a granular level, pmeshlab is a library that consists of the following components:\n\n| Component | Description |\n| ---- | --- |\n| **pmeshlab** | Contains the implementation of pmeshlab |\n\n# Installing the application\nTo clone and run this application, you'll need the following installed on your computer:\n- [Git](https://git-scm.com)\n- Docker Desktop\n - [Install Docker Desktop on Mac](https://docs.docker.com/docker-for-mac/install/)\n - [Install Docker Desktop on Windows](https://docs.docker.com/desktop/install/windows-install/)\n - [Install Docker Desktop on Linux](https://docs.docker.com/desktop/install/linux-install/)\n- [Python](https://www.python.org/downloads/)\n\nInstall the package:\n```bash\n# Clone this repository and install the code\ngit clone https://github.com/JeanMaximilienCadic/pmeshlab\n\n# Go into the repository\ncd pmeshlab\n```\n\n# Makefile commands\nExhaustive list of make commands:\n```\ninstall_wheels\nsandbox_cpu\nsandbox_gpu\nbuild_sandbox\npush_environment\npush_container_sandbox\npush_container_vanilla\npull_container_vanilla\npull_container_sandbox\nbuild_vanilla\nbuild_wheels\nauto_branch \n```\n# Environments\n\n## Docker\n\n> **Note**\n> \n> Running this application by using Docker is recommended.\n\nTo build and run the docker image\n```\nmake build\nmake sandbox\n```\n\n## PythonEnv\n\n> **Warning**\n> \n> Running this application by using PythonEnv is possible but *not* recommended.\n```\nmake install_wheels\n```\n\n## Ressources\n* Vanilla: https://en.wikipedia.org/wiki/Vanilla_software\n* Sandbox: https://en.wikipedia.org/wiki/Sandbox_(software_development)\n* All you need is docker: https://www.theregister.com/2014/05/23/google_containerization_two_billion/\n* Dev in containers : https://code.visualstudio.com/docs/remote/containers\n* Delta lake partitions: https://k21academy.com/microsoft-azure/data-engineer/delta-lake/\n\n\n\n\n",
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