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SAM 2 Demo

Welcome to the SAM 2 Demo! This project consists of a frontend built with React TypeScript and Vite and a backend service using Python Flask and Strawberry GraphQL. Both components can be run in Docker containers or locally on MPS (Metal Performance Shaders) or CPU. However, running the backend service on MPS or CPU devices may result in significantly slower performance (FPS).

Prerequisites

Before you begin, ensure you have the following installed on your system:

  • Docker and Docker Compose
  • [OPTIONAL] Node.js and Yarn for running frontend locally
  • [OPTIONAL] Anaconda for running backend locally

Installing Docker

To install Docker, follow these steps:

  1. Go to the Docker website
  2. Follow the installation instructions for your operating system.

[OPTIONAL] Installing Node.js and Yarn

To install Node.js and Yarn, follow these steps:

  1. Go to the Node.js website.
  2. Follow the installation instructions for your operating system.
  3. Once Node.js is installed, open a terminal or command prompt and run the following command to install Yarn:
npm install -g yarn

[OPTIONAL] Installing Anaconda

To install Anaconda, follow these steps:

  1. Go to the Anaconda website.
  2. Follow the installation instructions for your operating system.

Quick Start

To get both the frontend and backend running quickly using Docker, you can use the following command:

docker compose up --build

Warning

On macOS, Docker containers only support running on CPU. MPS is not supported through Docker. If you want to run the demo backend service on MPS, you will need to run it locally (see "Running the Backend Locally" below).

This will build and start both services. You can access them at:

Running Backend with MPS Support

MPS (Metal Performance Shaders) is not supported with Docker. To use MPS, you need to run the backend on your local machine.

Setting Up Your Environment

  1. Create Conda environment

    Create a new Conda environment for this project by running the following command or use your existing conda environment for SAM 2:

    conda create --name sam2-demo python=3.10 --yes

    This will create a new environment named sam2-demo with Python 3.10 as the interpreter.

  2. Activate the Conda environment:

    conda activate sam2-demo

  3. Install ffmpeg

    conda install -c conda-forge ffmpeg

  4. Install SAM 2 demo dependencies:

Install project dependencies by running the following command in the SAM 2 checkout root directory:

pip install -e '.[interactive-demo]'

Running the Backend Locally

Download the SAM 2 checkpoints:

(cd ./checkpoints && ./download_ckpts.sh)

Use the following command to start the backend with MPS support:

cd demo/backend/server/
PYTORCH_ENABLE_MPS_FALLBACK=1 \
APP_ROOT="$(pwd)/../../../" \
API_URL=http://localhost:7263 \
MODEL_SIZE=base_plus \
DATA_PATH="$(pwd)/../../data" \
DEFAULT_VIDEO_PATH=gallery/05_default_juggle.mp4 \
gunicorn \
    --worker-class gthread app:app \
    --workers 1 \
    --threads 2 \
    --bind 0.0.0.0:7263 \
    --timeout 60

Options for the MODEL_SIZE argument are "tiny", "small", "base_plus" (default), and "large".

Warning

Running the backend service on MPS devices can cause fatal crashes with the Gunicorn worker due to insufficient MPS memory. Try switching to CPU devices by setting the SAM2_DEMO_FORCE_CPU_DEVICE=1 environment variable.

Starting the Frontend

If you wish to run the frontend separately (useful for development), follow these steps:

  1. Navigate to demo frontend directory:

    cd demo/frontend

  2. Install dependencies:

    yarn install

  3. Start the development server:

    yarn dev --port 7262

This will start the frontend development server on http://localhost:7262.

Docker Tips

  • To rebuild the Docker containers (useful if you've made changes to the Dockerfile or dependencies):

    docker compose up --build

  • To stop the Docker containers:

    docker compose down

Contributing

Contributions are welcome! Please read our contributing guidelines to get started.

License

See the LICENSE file for details.

By following these instructions, you should have a fully functional development environment for both the frontend and backend of the SAM 2 Demo. Happy coding!