feat: update README.md

README.md

@@ -1,111 +1,31 @@
-# sphereDetect
+# Neural sphere detection in images for lighting calibration
 
-sphereDetect is a simple neural network, based on a Mask R-CNN, to detect spherical landmarks for image calibration.
+# Installation
-
-## Built with
-
-- [Python](https://www.python.org/)
-
-### Frameworks
-
-- [PyTorch](https://pytorch.org/)
-- [TorchVision](https://pytorch.org/vision/stable/index.html)
-- [PyTorch Lightning](https://www.pytorchlightning.ai/)
-- [PyTorch Lightning Bolts](https://www.pytorchlightning.ai/bolts)
-- [PyTorch Metrics](https://torchmetrics.readthedocs.io/en/stable/)
-- [ONNXRuntime](https://onnxruntime.ai/)
-
-### Tools
-
-- [Poetry](https://python-poetry.org/)
-- [Docker](https://www.docker.com/)
-- [VSCode](https://code.visualstudio.com/)
-    - [ms-python](https://marketplace.visualstudio.com/items?itemName=ms-python.python)
-    - [Python Docstring Generator](https://marketplace.visualstudio.com/items?itemName=njpwerner.autodocstring)
-    - [Conventional Commits](https://marketplace.visualstudio.com/items?itemName=vivaxy.vscode-conventional-commits)
-    - [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 and vscode)
-
-### 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
+git clone https://github.com/Laurent2916/REVA-DETR.git
+cd REVA-DETR/
 ```
 
-Start VS Code:
+## Usage
-```bash
-vscode pytorch-reva
-```
 
-Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). \
+Everything is managed thanks to [Lightning CLI](https://lightning.ai/docs/pytorch/latest/api/lightning.pytorch.cli.LightningCLI.html#lightning.pytorch.cli.LightningCLI) !
-Modify variables `UID` and `GID` in [`.devcontainer/Dockerfile`](https://git.inpt.fr/fainsil/pytorch-reva/-/blob/master/.devcontainer/Dockerfile#L6) if necessary.
-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:
-```bash
-git clone git@git.inpt.fr:fainsil/pytorch-reva.git
-cd pytorch-reva
-```
-
-Install the dependencies:
-```bash
-poetry install --with all
-```
-
-### Usage
-
-Activate python environment:
-```bash
-poetry shell
-```
-
-Configure [Weights & Biases (local) server](https://docs.wandb.ai/guides/self-hosted/local), and login:
-```bash
-wandb server start
-wandb login --host http://localhost:8080
-```
 
 Start a training:
 ```bash
-python src/train.py
+python src/main.py fit
+```
+
+Start inference on images:
+```bash
+python src/main predict --ckpt_path <path_to_checkpoint>
 ```
 
 ## License
 
 Distributed under the [MIT](https://choosealicense.com/licenses/mit/) license. \
-See [`LICENSE`](https://git.inpt.fr/fainsil/pytorch-reva/-/blob/master/LICENSE) for more information.
+See [`LICENSE`](https://github.com/Laurent2916/REVA-DETR/blob/master/LICENSE) for more information.
 
 ## Contact