### Install pyrealsense2 for Live Demo

Source: https://github.com/muskie82/monogs/blob/main/README.md

Installs the pyrealsense2 library within the active Conda environment, which is a prerequisite for running the live Realsense camera demo.

```bash
pip install pyrealsense2
```

--------------------------------

### Run Live Demo with Realsense Camera

Source: https://github.com/muskie82/monogs/blob/main/README.md

Starts the live SLAM demo using a Realsense camera. Ensure the camera is connected via USB-3 and the appropriate configuration file is used. A global shutter camera is recommended.

```bash
python slam.py --config configs/live/realsense.yaml
```

--------------------------------

### Clone and Install MonoGS Repository

Source: https://github.com/muskie82/monogs/blob/main/README.md

Clones the MonoGS GitHub repository and its submodules, then navigates into the project directory.

```bash
git clone https://github.com/muskie82/MonoGS.git --recursive
cd MonoGS
```

--------------------------------

### Run RGB-D SLAM Demo (Replica)

Source: https://github.com/muskie82/monogs/blob/main/README.md

Executes the RGB-D SLAM system using the Replica dataset configuration. This allows testing on a different dataset.

```bash
python slam.py --config configs/rgbd/replica/office0.yaml
```

--------------------------------

### Run Single-Process RGB-D SLAM Demo (Replica)

Source: https://github.com/muskie82/monogs/blob/main/README.md

Runs a single-process version of the RGB-D SLAM system for the Replica dataset. This may offer different performance characteristics.

```bash
python slam.py --config configs/rgbd/replica/office0_sp.yaml
```

--------------------------------

### Run Monocular SLAM Demo

Source: https://github.com/muskie82/monogs/blob/main/README.md

Executes the monocular SLAM system using a specified configuration file for the TUM dataset. A GUI window will appear upon successful execution.

```bash
python slam.py --config configs/mono/tum/fr3_office.yaml
```

--------------------------------

### Download Replica Dataset

Source: https://github.com/muskie82/monogs/blob/main/README.md

Downloads the Replica dataset, used for RGB-D SLAM experiments. The dataset is placed in the './datasets' directory.

```bash
bash scripts/download_replica.sh
```

--------------------------------

### Run Experimental Stereo SLAM Demo

Source: https://github.com/muskie82/monogs/blob/main/README.md

Initiates the stereo SLAM system, currently marked as experimental, using the EuRoC MAV dataset configuration.

```bash
python slam.py --config configs/stereo/euroc/mh02.yaml
```

--------------------------------

### Run SLAM Evaluation Script

Source: https://github.com/muskie82/monogs/blob/main/README.md

This command executes the SLAM system with evaluation enabled. It requires specifying the configuration file and passing the `--eval` argument. This will run the system in headless mode and log detailed results, including rendering metrics.

```bash
python slam.py --config configs/mono/tum/fr3_office.yaml --eval

```

--------------------------------

### Run RGB-D SLAM Demo (TUM)

Source: https://github.com/muskie82/monogs/blob/main/README.md

Launches the RGB-D SLAM system with the TUM dataset configuration. This demonstrates the system's capability with depth information.

```bash
python slam.py --config configs/rgbd/tum/fr3_office.yaml
```

--------------------------------

### Download TUM-RGBD Dataset

Source: https://github.com/muskie82/monogs/blob/main/README.md

Downloads the TUM-RGBD dataset, which is required for certain SLAM demonstrations. The dataset will be saved in the './datasets' folder.

```bash
bash scripts/download_tum.sh
```

--------------------------------

### Set Up Conda Environment for MonoGS

Source: https://github.com/muskie82/monogs/blob/main/README.md

Creates and activates a Conda environment using the provided 'environment.yml' file. Users may need to adjust PyTorch and CUDA toolkit versions based on their system.

```bash
conda env create -f environment.yml
conda activate MonoGS
```

--------------------------------

### Download EuRoC MAV Dataset

Source: https://github.com/muskie82/monogs/blob/main/README.md

Downloads the EuRoC MAV dataset, necessary for stereo SLAM configuration. The datasets are stored under the './datasets' folder.

```bash
bash scripts/download_euroc.sh
```

--------------------------------

### Citation for Gaussian Splatting SLAM

Source: https://github.com/muskie82/monogs/blob/main/README.md

BibTeX entry for citing the Gaussian Splatting SLAM work, as presented in CVPR 2024. This should be used when referencing the project in academic publications.

```bibtex
@inproceedings{Matsuki:Murai:etal:CVPR2024,
  title={{G}aussian {S}platting {SLAM}},
  author={Hidenobu Matsuki and Riku Murai and Paul H. J. Kelly and Andrew J. Davison},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year={2024}
}

```

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