instruction: Create a Dockerfile for fundamentals
output: ```dockerfile
  from an
  Alpine Linux base image.Develop with ComposeDocker Compose is a tool for defining and running multi-container Docker
  applications. With Compose, you use a YAML file to configure your application's
  services, networks, and volumes. In this case, the application isn't a
  multi-container application, but Docker Compose has other useful features for
  development, like
  Compose Watch.The sample application doesn't have a Compose file yet. To create a Compose
  file, in the TensorJS-Face-Detection directory, create a text file named
  compose.yaml and then add the following contents.
  
  services:
   server:
   build:
   context: .
   ports:
   - 80:80
   develop:
   watch:
   - action: sync
   path: .
   target: /usr/share/nginx/htmlThis Compose file defines a service that is built using the Dockerfile in the
  same directory. It maps port 80 on the host to port 80 in the container. It also
  has a develop subsection with the watch attribute that defines a list of
  rules that control automatic service updates based on local file changes. For
  more details about the Compose instructions, see the
  Compose file reference.Save the changes to your compose.yaml file and then run the following command to run the application.
  
  $ docker compose watch
  Once the application is running, open a web browser and access the application
  at http://localhost:80. You may need to grant access to
  your webcam for the application.Now you can make changes to the source code and see the changes automatically
  reflected in the container without having to rebuild and rerun the container.Open the index.js file and update the landmark points to be green instead of
  blue on line 83.
  
  - ctx.fillStyle = "blue";
  + ctx.fillStyle = "green";
  Save the changes to the index.js file and then refresh the browser page. The
  landmark points should now appear green.To stop the application, press ctrl+c in the terminal.Share your imagePublishing your Docker image on Docker Hub streamlines deployment processes for
  others, enabling seamless integration into diverse projects. It also promotes
  the adoption of your containerized solutions, broadening their impact across the
  developer ecosystem. To share your image:Sign up or sign in to Docker Hub.Rebuild your image to include the changes to your application. This time,
  prefix the image name with your Docker ID. Docker uses the name to determine
  which repository to push it to. Open a terminal and run the following
  command in the TensorJS-Face-Detection directory. Replace YOUR-USER-NAME
  with your Docker ID.
  
  $ docker build -t YOUR-USER-NAME/face-detection-tensorjs .
  Run the following docker push command to push the image to Docker Hub.
  Replace YOUR-USER-NAME with your Docker ID.
  
  $ docker push YOUR-USER-NAME/face-detection-tensorjs
  Verify that you pushed the image to Docker Hub.Go to Docker Hub.Select My Hub > Repositories.View the Last pushed time for your repository.Other users can now download and run your image using the docker run command. They need to replace YOUR-USER-NAME with your Docker ID.
  
  $ docker run -p 80:80 YOUR-USER-NAME/face-detection-tensorjs
  SummaryThis guide demonstrated leveraging TensorFlow.js and Docker for face detection
  in web applications. It highlighted the ease of running containerized
  TensorFlow.js applications, and developing with Docker Compose for real-time
  code changes. Additionally, it covered how sharing your Docker image on Docker
  Hub can streamline deployment for others, enhancing the application's reach
  within the developer community.Related information:TensorFlow.js websiteMediaPipe websiteDockerfile referenceCompose file referenceDocker CLI referenceDocker Blog: Accelerating Machine Learning with TensorFlow.js
  Request changesTable of contentsPrerequisitesWhat is TensorFlow.js?Why Use TensorFlow.js and Docker together?Get and run the sample applicationAbout the applicationWASMWebGLCPUExplore the application's codeThe index.html fileThe index.js fileThe tf-backend-wasm.js fileThe tfjs-backend-wasm-simd.wasm fileExplore the DockerfileDevelop with ComposeShare your imageSummary
  
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