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feat: moar README.md

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Laurent Fainsin 2022-09-12 14:52:28 +02:00
parent 8ca80e200e
commit 23295957e6
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3
.vscode/extensions.json vendored
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@ -4,6 +4,7 @@
"ms-azuretools.vscode-docker",
"editorconfig.editorconfig",
"njpwerner.autodocstring",
"ms-python.python"
"ms-python.python",
"ms-toolsai.jupyter"
]
}

49
README.md
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@ -11,8 +11,8 @@ sphereDetect is a simple neural network, based on a Mask R-CNN, to detect spheri
- [PyTorch](https://pytorch.org/)
- [TorchVision](https://pytorch.org/vision/stable/index.html)
- [PyTorch Lightning](https://www.pytorchlightning.ai/)
- [PyTorch Metrics](https://torchmetrics.readthedocs.io/en/stable/)
- [PyTorch Lightning Bolts](https://www.pytorchlightning.ai/bolts)
- [PyTorch Metrics](https://torchmetrics.readthedocs.io/en/stable/)
- [ONNXRuntime](https://onnxruntime.ai/)
### Tools
@ -26,13 +26,50 @@ sphereDetect is a simple neural network, based on a Mask R-CNN, to detect spheri
- [Remote container](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.remote-containers)
- [EditorConfig](https://marketplace.visualstudio.com/items?itemName=EditorConfig.EditorConfig)
- [Docker](https://marketplace.visualstudio.com/items?itemName=ms-azuretools.vscode-docker)
- [Jupyter](https://marketplace.visualstudio.com/items?itemName=ms-toolsai.jupyter)
## Getting started (with docker)
## Getting started (with docker and vscode)
TODO
### Requirements
- [Git](https://git-scm.com/)
- [Docker](https://www.docker.com/)
- [NVIDIA-Docker](https://github.com/NVIDIA/nvidia-docker)
### Installation
Clone the repository:
```bash
git clone git@git.inpt.fr:fainsil/pytorch-reva.git
```
Start VS Code:
```bash
vscode pytorch-reva
```
Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). \
Reopen the workspace in [devcontainer mode](https://code.visualstudio.com/docs/remote/containers).
### Usage
Configure [Weights & Biases (local) server](https://docs.wandb.ai/guides/self-hosted/local) at <http://localhost:8080>, and login:
```bash
wandb login --host http://localhost:8080
```
Press `F5` to launch `src/train.py` in debug mode (with breakpoints, slower) \
or press `Ctrl+F5` to launch `src/train.py` in release mode.
## Getting started (without docker)
### Requirements
- [Git](https://git-scm.com/)
- [Poetry](https://python-poetry.org/)
- [Python](https://www.python.org/)
- [Docker](https://www.docker.com/) (if local wandb server used)
### Installation
Clone the repository:
@ -53,10 +90,10 @@ Activate python environment:
poetry shell
```
Start and configure Weights & Biases local server:
Configure [Weights & Biases (local) server](https://docs.wandb.ai/guides/self-hosted/local), and login:
```bash
wandb server start
wandb login
wandb login --host http://localhost:8080
```
Start a training:
@ -71,5 +108,5 @@ See [`LICENSE`](https://git.inpt.fr/fainsil/pytorch-reva/-/blob/master/LICENSE)
## Contact
Laurent Fainsin _[fɛ̃zɛ̃]_ \
Laurent Fainsin _[loʁɑ̃ fɛ̃zɛ̃]_ \
\<[laurent@fainsin.bzh](mailto:laurent@fainsin.bzh)\>