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TOM-Server-Python

A Python implementation of the server that handles the client data and application logic

  • A backend server to handle data processing and running of various services.
  • It takes input from a variety of sources, including video streams and the WebSocket Server.
  • Designed to be easy for developers to implement new services and to be able to support real-time data processing.

Requirements

  • Make sure python3 is installed

Installation

  • Install conda (Miniconda). Note that some packages may not work with Anaconda.
    • Upgrade pip, using pip install --upgrade pip setuptools wheel
  • Create new conda environment tom using conda env create -f environment-cpu.yml
    • If you have a previous environment, then update it, conda env update --file environment-cpu.yml --prune.
    • To completely remove previous env run, conda remove -n tom --all, then recreate the environment.
    • For ARM Mac (M1-Mn chip),
      • If the installation fails due to pyaudio, please follow this
      • If the installation fails due to egg_info, change the dependency psycopg2 to psycopg2-binary in environment-cpu.yml
      • If the installation fails due to googlemaps, either remove it from environment-cpu.yml or install it separately using pip install --use-pep517 googlemaps after activating the tom environment.
  • Activate tom environment, conda activate tom
  • Download the pretrained weights for YOLOv8 from Ultralytics (e.g., yolov8n.pt).
    • Copy the downloaded file to the Processors/Yolov8/weights directory and rename it as model.pt (i.e., Processors/Yolov8/weights/model.pt).
  • Create the environment files:
    • For development environment: Copy .sample_env to .env.dev and [optional] update the values if needed.
      • e.g., CAMERA_VIDEO_SOURCE = 0 uses the default camera and can be changed to any video stream/URL/file source.
        • [Optional] To use the HoloLens camera, uncomment the following lines in main.py and update the IP address in credential/hololens_credential.json: 
          # from APIs.hololens import hololens_portal
# hololens_portal.set_api_credentials()
# hololens_portal.set_hololens_as_camera()
    • For testing environment: Copy .sample_env to .env.test and [optional] update the values if needed.
  • [Optional] Create the required credential files inside the newly created credential folder, ONLY for third-party libraries you use. Please refer to the Third-party libraries section to obtain credentials. (Note: JSON format must be correct.)
    • Create a file credential/hololens_credential.json with Hololens credentials such as {"ip": "IP","username": "USERNAME","password": "PASSWORD"}
    • Create a file credential/google_cloud_credentials.json with Google Cloud API credentials.
      • Follow authentication to get json key file and rename it to google_cloud_credentials.json
    • Create a file credential/openai_credential.json with OpenAI credentials such as {"openai_api_key": "KEY"}
    • Create a file credential/gemini_credential.json with Gemini credentials such as {"gemini_api_key": "KEY"}
    • Create a file credential/anthropic_credential.json with Anthropic credentials such as {"anthropic_api_key": "KEY"}
    • Create a file credential/google_maps_credential.json with Google Maps credentials such as {"map_api_key": "KEY"}
      • Current Google Maps APIs used:
      • To use Google Maps API, you need to have a Google Cloud Platform (GCP) account to get an API key and enable the APIs shown above.
    • Create a file credential/ors_credential.json with Openrouteservice credentials such as {"map_api_key": "KEY"}
    • Create a file credential/geoapify_credential.json with Geoapify credentials such as {"map_api_key": "KEY"}
    • Create a file credential/fitbit_credential.json with Fitbit credentials such as {"client_id": "ID","client_secret": "SECRET"}
  • [Optional] If you want to simulate running assistance on a treadmill, follow the steps in Running Demo Service
  • [Optional] To use APIs/local_yyy (e.g., local_vector_db), please follow the README.md inside those local APIs.

Setup the clients

  • Makesure the clients (e.g., HoloLens, Xreal, WearOS Watch) are connected to the same Wi-Fi network of the Sever. Use a private network, as public networks may block certain ports used by websocket communication (e.g., 8090). Note: Campus network may not work.
  • Use ipconfig / ifconfig in your terminal to get the Server IP address. Look for the IPv4 address under the Wi-Fi section. image
  • Set up TOM-Client-Unity on the HoloLens/Xreal and make sure to update the IP address in Videos/TOM/tom_config.json.
  • [Optional] Set up TOM-Client-WearOS on the Android smartwatch and make sure to update the IP address in app/src/main/java/com/hci/tom/android/network/Credentials.kt.
  • [Optional] Set up TOM-Client-Web on a computer and make sure to update the IP address in src/constant/config.ts.
  • [Troubleshooting] If clients cannot connect to the server via websocket, try the following steps:
    • Ensure that all clients are on the same network as the server. For devices running Windows OS, such as PCs or HoloLens, set the network connection to private.
    • Check the firewall settings on the server machine and allow the server application to communicate through the firewall.
    • To test if the server is reachable, use another computer on the same network to run WebSocketClientTester.html. This test will attempt to open port 8090 on the server, confirming if it's accessible from another device.

Application execution

  1. Use the tom environment:
    • Activate it via the command line: conda activate tom (for Conda users) or through your IDE.
  2. Export the environment variable ENV:
    • For Windows Command Prompt: 
      set ENV=dev
    • For Windows PowerShell: 
      $env:ENV = "dev"
    • For Linux/Mac: 
      export ENV=dev
  3. Run the application:
    • Execute main.py using: 
      python main.py
      (Avoid using py main.py.)
  4. [Optional] Configure your IDE (e.g., VSCode, PyCharm) to run the server with the environment variable ENV=dev.
  5. [Optional] Run the clients after the server has started.

Running tests

  • Run pytest via python -m pytest (or python -m pytest Tests\...\yy.py or python -m pytest Tests\...\yy.py::test_xx to run specific tests)

Demos

Configuring First-Person Video for Running Service

  • Download the first person video here (you can download fpv_short.mp4 or fpv.mp4).
    • Copy the video/s to Tests/RunningFpv/.
    • Configure which video to be used (short/full) in the .env file (FPV_OPTION).
  • Set up the Unity and WearOS clients as mentioned in the Setup the Clients section.
  • Ensure that DemoRunningCoach.yaml is set in /Config, and RunningCoach.yaml is in /Config/Ignore on the python server.

Development

  • See DeveloperGuide.md for more details on development guidelines and adding new services/components.

References

Third-party libraries