CodeProject.AI Home Assistant License Plate Reader custom component

This component is a direct port of the HASS-plate-recognizer component by Robin Cole. This component provides AI-based Object Detection capabilities using CodeProject.AI Server.

CodeProject.AI Server is a service which runs either in a Docker container or as a Windows Service and exposes various an API for many AI inferencing operations via a REST API. The Object Detection capabilities use the YOLO algorithm as implemented by Ultralytics and others. It can identify 80 different kinds of objects by default, but custom models are also available that focus on specific objects such as animals, license plates or objects typically encountered by home webcams. CodeProject.AI Server is free, locally installed, and can run without an external internet connection, is is comatible with Windows, Linux, macOS. It can run on Raspberry Pi, and supports CUDA and embedded Intel GPUs.

On the machine in which you are running CodeProject.AI server, either ensure the service is running, or if using Docker, start a Docker container.

This integration adds an image processing entity where the state of the entity is the number of license plates found in a processed image. Information about the vehicle which has the license plate is provided in the entity attributes, and includes the license plate number, and confidence (in a scale 0 to 1) in this prediction. For each vehicle an codeproject_ai_alpr.vehicle_detected event is fired, containing the same information just listed.

Note this integration does NOT automatically process images, it is necessary to call the image_processing.scan service to trigger processing.

Home Assistant setup

Place the custom_components folder in your configuration directory (or add its contents to an existing custom_components folder). Then configure as below:

image_processing:
  - platform: codeproject_ai_alpr
    server: http://yoururl:8080/v1/vision/alpr/
    watched_plates:
      - kbw46ba
      - kfab726
    save_file_folder: /config/images/codeproject_ai_alpr/
    save_timestamped_file: True
    always_save_latest_file: True
    source:
      - entity_id: camera.yours

Then, restart your Home Assistant

Configuration variables:

• server: (CodeProject.AI ALPS instance URL)
• watched_plates: (Optional) A list of number plates to watch for, which will identify a plate even if a couple of digits are incorrect in the prediction (fuzzy matching). If configured this adds an attribute to the entity with a boolean for each watched plate to indicate if it is detected.
• save_file_folder: (Optional) The folder to save processed images to. Note that folder path should be added to whitelist_external_dirs
• save_timestamped_file: (Optional, default False, requires save_file_folder to be configured) Save the processed image with the time of detection in the filename.
• always_save_latest_file: (Optional, default False, requires save_file_folder to be configured) Always save the last processed image, no matter there were detections or not.
• source: Must be a camera.
• unique_id: Unique id of the entity.

Making a sensor for individual plates

If you have configured watched_plates you can create a binary sensor for each watched plate, using a template sensor as below, which is an example for plate kbw46ba:

sensor:
  - platform: template
    sensors:
      my_plate:
        friendly_name: "kbw46ba"
        value_template: "{{ state_attr("image_processing.codeproject_ai_alpr_1", "watched_plates")["kbw46ba"] }}"