License Plate Parser (Edge)
Extracts license plate numbers locally from the license plates detected using the License Plate Detection and the Licence Plate Recognition models.
Overview
This node parses the output of "License Plate Recognition" model to extract the license plate information.
This node requires AI Model Node (Vehicle Detection model) -> Model Inference Node (License Plate model) -> Track Objects Node -> Model Inference Node (License Plate Recognition) prior to it in order to function properly.
Inputs & Outputs
- Inputs : 1, Media Format : Raw Video
- Outputs : 1, Media Format: Raw Video
- Output Metadata : None
Properties
Property | Value |
---|---|
display_info | If true, LPR info will be drawn on video. ex. true / false |
objects_to_associate | Objects classes that should be considered on the LPR and vehicle association. 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) |
detection_buffer | Time (in seconds) that the License Plate must be present before reporting results in metadata. ex. 1.0 |
rejection_buffer | Time (in seconds) during which objects that leave and re-enter the scene will be ignored. Increase to reduce duplicate alerts for a given object. ex, 5.0 |
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_lpr_edgeX (ex. annotate_lpr_edge1 ) |
"nodes":{
"annotate_lpr_edge*":{
"type":"annotate_lpr_edge",
"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>
}
]
}
}
}
}
}
}
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 each detected and recognized license plate.object_tracking_id : Unique identifier for a specific object, as specified by object.id property (see Track Objects NodePlease 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 |
---|---|---|
10400 | The recognized license plate (string) | 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": 10400,
"probability": 1.0,
}]
}]
Updated 8 months ago