Overview

This node uses a cloud based service to read license plates from vehicles that are detected using the Vehicle & License Plate models.

This node requires AI Model Node (Vehicle Detection model) -> Model Inference Node (License Plate model) -> Track Objects Node prior to it in order to function properly using the "LPR & Make/Model/Color" recognition mode.

Inputs & Outputs

Inputs : 1, Media Format : Raw Video
Outputs : 1, Media Format: Raw Video
Output Metadata : None

Properties

Property	Value
`geographies`	Geographies that the license plates may belong to. Use this to optimize license plate recognition. ex. `us, us_ca`
`objects_to_track`	Objects on which to perform License plate recognition. Unset means all. ex. `car`, `vehicle`, `truck` Accepted formats: `object_label`: any object of this type, with or without a classifier attribute. Example: `car` `object_label.class_type`: any object of this type that has a specific classifier attribute. Example: `car.red` `object_label.`: any object of this type that has at least one classifier attribute. Example: `car.` (this will match `car.red`, `car.yellow`, etc)
`display_info`	Display License plate (+ MMC) information on the video stream itself. ex. `true` / `false`
`recognition_mode`	Recognition mode "LPR & Make/Model/Color" (`lpr_mmc`) => Requires a Model Inference Node for `Vehicle Detection` and another one for `License Plate Detection`. We will only perform recognition once we find a valid association between a Vehicle and a License Plate. "LPR Only" (`lpr_only`) => Requires a Model Inference Node for `License Plate Detection`. Will perform recognition attempts using the detected License Plate image crop. "Make/Model/Color Only" (`mmc_only`) => Requires a Model Inference Node for `Vehicle Detection` Performs recognition attempts using the detected Vehicle image crop.
`requests_buffer`	The interval (in seconds) before perform the initial LPR request and between subsequent retries ex. 1.0

Metadata

Metadata Property	Description
`nodes.<node_id>`	License plate information as described in the JSON below. `<node_id>` for License Plate Detection Nodes is of the form `annotate_lprX` (ex. `annotate_lpr1`)

"nodes":{
    "annotate_lpr*":{
        "type":"annotate_lpr",
        "license_plates_entered_delta":"<int>",
        "license_plates_exited_delta":"<int>",
        "license_plates_count":"<int>",
        "license_plates":{
            "<object_tracking_id>": {
                "plate":{
                    "type":"Plate",
                    "score":<float>,
                    "props":{
                        "plate":[
                            {
                            "value":"<license_plate_number>",
                            "score":<float>
                            }
                        ],
                        "region":[
                            {
                            "value":"<region>",
                            "score":<float>
                            }
                        ]
                    }
                },
                "vehicle":{
                    "type":"<vehicle_type>",
                    "score":<float>,
                    "props":{
                        "make_model":[
                            {
                            "make":"<make>",
                            "model":"<model>",
                            "score":<float>
                            }
                        ],
                        "orientation":[
                            {
                            "value":"<orientation>",
                            "score":<float>
                            }
                        ],
                        "color":[
                            {
                            "value":"<color>",
                            "score":<float>
                            }
                        ]
                    }
                }
            }
        }
    }
}

Format

Key	Type	Description
`license_plates_entered_delta`	Integer	Number of new license plates detected since last frame
`license_plates_exited_delta`	Integer	Number of license plates that left since last frame
`license_plates_count`	Integer	Total number of license plates in the view right now
`license_plates`	List of object IDs	Information about the license plate, make, model & color of each vehicle. \n \n`object_tracking_id` : Unique identifier for a specific object, as specified by `object.id` property (see Model Inference Node ) \n \nThe `\"plate\"` and "recognition"`fields contents may not be present depending on the current recognition results.\n\nPlease check the`json\` example for more details.

Objects metadata augmentation

The following information is added to the detected object's "attributes" array:

"class_id" field	"label" field	"probability" field
10500	The recognized license plate (string)	LP recognition confidence
10501	Vehicle's make	LP recognition confidence
10502	Vehicle's model	LP recognition confidence
10503	Vehicle's color	LP recognition confidence

"objects": [{
    "id": 5750484150146564100,
    "label": "car",
    "class_id": 0,
    "probability": 0.98,
    "rect": {
        "width": 47,
        "top": 201,
        "left": 656,
        "height": 25.
    },
    "attributes": [{
        "label": "ABC1234",
        "class_id": 10500,
        "probability": 1.0,
    },
    {
        "label": "Tesla",
        "class_id": 10501,
        "probability": 1.0,
    },
    {
        "label": "Model S",
        "class_id": 10502,
        "probability": 1.0,
    },
    {
        "label": "Red",
        "class_id": 10503,
        "probability": 1.0,
    }]
}]