HASS-plate-recognizer

This is a fork of robmarkcole/HASS-plate-recognizer which utlizes the codeproject.ai local plate recognizer instead of ALPR at platerecognizer.com

Read vehicle license plates with codeproject.ai (get it from https://www.codeproject.com/)

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 platerecognizer.vehicle_detected event is fired, containing the same information just listed. Additionally, statistics about your account usage are given in the Statistics attribute, including the number of calls_remaining out of your 2500 monthly available.

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: platerecognizer_local
    api_token: your_token (For now, any value)
    regions: (Not used, just to not ruin the config flow until cleaned)
      - gb
      - ie
    watched_plates:
      - kbw46ba
      - kfab726
    save_file_folder: /config/images/platerecognizer/
    save_timestamped_file: True
    always_save_latest_file: True
    mmc: True (For now, any value)
    detection_rule: strict (For now, any value)
    region: strict (For now, any value)
    server: http://yoururl:8080/v1/plate-reader/ (URL To your local Codeproject site)

    source:
      - entity_id: camera.yours

Then, restart your Home Assistant

Configuration variables:

• api_key: Not needed.

• regions: Not needed.

• 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.

• mmc: Not needed.

• detection_rule: Not needed.

• region: Not needed.

• server: (Required - if vision is enabled in codeproject, use http://codeproject local url:port/v1/vision/alpr)

• source: Must be a camera.

• Pictures below doesn't really match the forked component.

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:
      plate_recognizer:
        friendly_name: "kbw46ba"
        value_template: "{{ state_attr('image_processing.platerecognizer_1', 'watched_plates').kbw46ba }}"

Depending on your license plate, you may recieve an template error due to variables not being able to start with a number. if so, here is another method to create the template sensor:

sensor:
  - platform: template
    sensors:
      plate_recognizer:
        friendly_name: "kbw46ba"
        value_template: "{{ state_attr("image_processing.platerecognizer_1", "watched_plates")["kbw46ba"] }}"

Video of usage

Checkout this excellent video of usage from Everything Smart Home