diff --git a/Docker Setup/Dockerfile b/Docker Setup/Dockerfile
new file mode 100644
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--- /dev/null
+++ b/Docker Setup/Dockerfile	
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+FROM pytorch/pytorch:1.13.1-cuda11.6-cudnn8-devel
+
+RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub \
+    && apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/7fa2af80.pub \
+    && apt-get update \
+    && apt-get install -y ffmpeg libsm6 libxext6 git ninja-build libglib2.0-0 libsm6 libxrender-dev libxext6
+
+# Install MinkowskiEngine
+# Feel free to skip nvidia-cuda-dev if minkowski installation is fine
+RUN apt-get update \
+    && apt-get -y install libopenblas-dev nvidia-cuda-dev
+
+
+# Install torch-scatter 
+RUN pip install torch-scatter==2.1.2 -f https://data.pyg.org/whl/torch-1.13.0+cu116.html --no-deps
+
+# Install remaining python packages
+RUN pip install --no-deps \
+    munch \
+    pyyaml \
+    six \
+    tensorboard \
+    tensorboardX \
+    tqdm \
+    imageio \
+    setuptools \
+    protobuf \
+    spconv-cu116==2.3.6 \
+    addict==2.4.0 \
+    yapf==0.33.0 \
+    termcolor==2.3.0 \
+    packaging==23.1 \
+    numpy==1.24.1 \
+    rich==13.3.5 \
+    opencv-python==4.7.0.72 \
+    pycocotools==2.0.6 \
+    Shapely==1.8.5 \
+    scipy==1.10.1 \
+    terminaltables==3.1.10 \
+    numba==0.57.0 \
+    llvmlite==0.40.0 \
+    pccm==0.4.7 \
+    ccimport==0.4.2 \
+    pybind11==2.10.4 \
+    ninja==1.11.1 \
+    lark==1.1.5 \
+    cumm-cu116==0.4.9 \
+    pyquaternion==0.9.9 \
+    lyft-dataset-sdk==0.0.8 \
+    pandas==2.0.1 \
+    python-dateutil==2.8.2 \
+    matplotlib==3.5.2 \
+    pyparsing==3.0.9 \
+    cycler==0.11.0 \
+    kiwisolver==1.4.4 \
+    scikit-learn==1.2.2 \
+    joblib==1.2.0 \
+    threadpoolctl==3.1.0 \
+    cachetools==5.3.0 \
+    nuscenes-devkit==1.1.10 \
+    trimesh==3.21.6 \
+    open3d==0.17.0 \
+    plotly==5.18.0 \
+    dash==2.14.2 \
+    plyfile==1.0.2 \
+    flask==3.0.0 \
+    werkzeug==3.0.1 \
+    click==8.1.7 \
+    blinker==1.7.0 \
+    itsdangerous==2.1.2 \
+    importlib_metadata==2.1.2 \
+    zipp==3.17.0
diff --git a/Docker Setup/README.md b/Docker Setup/README.md
new file mode 100644
index 0000000..d9515c3
--- /dev/null
+++ b/Docker Setup/README.md	
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+# ISBNet Setup Using Docker
+
+Follow the steps below to set up ISBNet with Docker, including pulling the necessary Docker image, cloning the repository, and installing required dependencies.
+
+## 1. Pull the Docker Image
+
+First, pull the Docker image `rayyoh/oneformer3d`:
+
+```bash
+
+docker pull rayyoh/oneformer3d
+```
+
+## 2. Clone ISBNet Repository
+
+```bash
+git clone https://github.com/VinAIResearch/ISBNet/tree/master
+```
+
+## 3. Run Docker Container
+
+```bash
+docker run --gpus all -it --shm-size=8g --cpus=4 -e PYTORCH_CUDA_ALLOC_CONF=max_split_size_mb:128 -v C:\Users\Perception-Team\ISBNet:/workspace -p 6008:6008 --name isnbet check
+```
+
+## 4. Install Python Requirements Inside the container:
+
+```bash
+pip3 install -r requirements.txt
+```
+## 5. Build Segmentator Again Inside Docker
+
+```bash
+git clone https://github.com/Karbo123/segmentator.git
+cd segmentator/csrc
+mkdir build && cd build
+cmake .. \
+-DCMAKE_PREFIX_PATH=`python -c 'import torch; print(torch.utils.cmake_prefix_path)'` \
+-DPYTHON_INCLUDE_DIR=$(python -c "from distutils.sysconfig import get_python_inc; print(get_python_inc())") \
+-DPYTHON_LIBRARY=$(python -c "import distutils.sysconfig as sysconfig; print(sysconfig.get_config_var('LIBDIR'))") \
+-DCMAKE_INSTALL_PREFIX=`python -c 'from distutils.sysconfig import get_python_lib; print(get_python_lib())'`
+make && make install
+ ```
+
+## 6. Install libsparsehash-dev
+
+```bash
+apt-get install libsparsehash-dev
+```
+## 7. Setup PointNet2
+
+```bash
+
+cd isbnet/pointnet2
+python3 setup.py bdist_wheel
+cd ./dist
+pip3 install pointnet2-0.0.0-cp310-cp310-linux_x86_64.whl
+```
+## 8. Final Build
+
+```bash
+cd ../../..
+python3 setup.py build_ext develop
+```
+
+## Todo
+### Explanation:
+- The **Alternative Method** section provides the user an option to directly download the Dockerfile and skip the manual image pull process. 
+- You can link to the Dockerfile in your GitHub repository [link](https://github.com/Smith-S-S/ISBNet/blob/master/Docker%20Setup/Dockerfile) and indicate to the user that they can skip the manual `docker pull` command if they choose this method.
+
+
+
+