License Plate and MMC Recognition (Platerecognizer)
Recognize license plate numbers and make/model/color using Platerecognizer's Snapshot API for the license plates detected using the License Plate model.
Overview
This node uses Platerecognizer's Snapshot API 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 |
---|---|
pr_api_key | Your Platerecognizer Snapshot API key from https://platerecognizer.com/snapshot/ |
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.object_tracking_id : Unique identifier for a specific object, as specified by object.id property (see Model Inference Node )The "plate" and "recognition"fields contents may not be present depending on the current recognition results. Please 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 |
---|---|---|
10300 | The recognized license plate (string) | LP recognition confidence |
10301 | Vehicle's make | LP recognition confidence |
10302 | Vehicle's model | LP recognition confidence |
10303 | 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": 10300,
"probability": 1.0,
},
{
"label": "Tesla",
"class_id": 10301,
"probability": 1.0,
},
{
"label": "Model S",
"class_id": 10302,
"probability": 1.0,
},
{
"label": "Red",
"class_id": 10303,
"probability": 1.0,
}]
}]
Updated 4 days ago