# gem install multipart-post
require 'net/http/post/multipart'

url = URI.parse('https://api.platerecognizer.com/v1/plate-reader/')
path = '/path/to/car.jpg'
File.open(path) do |jpg|
  req = Net::HTTP::Post::Multipart.new url.path,
    "upload" => UploadIO.new(jpg, "image/jpeg", path)
  req['Authorization'] = 'Token my-token******'
  res = Net::HTTP.start(url.host, url.port, use_ssl: true) do |http|
    http.request(req)
  end
end

<?php
// CREATE FILE READY TO UPLOAD WITH CURL
$file = realpath('example.jpg');
if (function_exists('curl_file_create')) { // php 5.5+
  $cFile = curl_file_create($file);
} else {
  $cFile = '@' . realpath($file);
}

//ADD PARAMETER IN REQUEST LIKE regions
$data = array(
    'upload' => $cFile,
    'regions' => 'us-ca' // Optional
);

// Prepare new cURL resource
$ch = curl_init('https://api.platerecognizer.com/v1/plate-reader/');
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLINFO_HEADER_OUT, true);
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_POSTFIELDS, $data);
curl_setopt($ch, CURLOPT_HTTP_VERSION, CURL_HTTP_VERSION_2TLS);

// Set HTTP Header for POST request
curl_setopt($ch, CURLOPT_HTTPHEADER, array(
    "Authorization: Token my-token******"  //API KEY
    )
);

// Submit the POST request and close cURL session handle
$result = curl_exec($ch);
print_r($result);exit;
curl_close($ch);
?>

# pip install requests
import requests
from pprint import pprint
regions = ['mx', 'us-ca'] # Change to your country
with open('/path/to/car.jpg', 'rb') as fp:
    response = requests.post(
        'https://api.platerecognizer.com/v1/plate-reader/',
        data=dict(regions=regions),  # Optional
        files=dict(upload=fp),
        headers={'Authorization': 'Token my-token******'})
pprint(response.json())

# Calling with a custom engine configuration
import json
with open('/path/to/car.jpg', 'rb') as fp:
    response = requests.post(
        'https://api.platerecognizer.com/v1/plate-reader/',
        data=dict(regions=['us-ca'], config=json.dumps(dict(region="strict"))),  # Optional
        files=dict(upload=fp),
        headers={'Authorization': 'Token my-token******'})

# Calling the API with 2 regions (Mexico and California). On Windows, use curl -F "upload=@C:\images\car.jpg".
curl -F 'upload=@/path/to/car.jpg' \
  -F regions=mx \
  -F regions=us-ca \
  -H 'Authorization: Token my-token******' \
  https://api.platerecognizer.com/v1/plate-reader/

# Calling the API with a custom engine configuration and region California. On Windows, use curl -F "upload=@C:\images\car.jpg".
curl -F 'upload=@/path/to/car.jpg' \
  -F regions=us-ca -F config='{"region":"strict"}' \
  -H 'Authorization: Token my-token******' \
  https://api.platerecognizer.com/v1/plate-reader/

// Using Node-RED?
// Check https://github.com/parkpow/node-red-contrib-plate-recognizer

const fetch = require('node-fetch');
const FormData = require('form-data');
const fs = require('fs');

let image_path = '/path/to/car.jpg'
let body = new FormData();
body.append('upload', fs.createReadStream(image_path));
// Or body.append('upload', base64Image);
body.append('regions', 'us-ca'); // Change to your country
fetch("https://api.platerecognizer.com/v1/plate-reader/", {
        method: 'POST',
        headers: {
            "Authorization": "Token my-token******"
        },
        body: body
    }).then(res => res.json())
    .then(json => console.log(json))
    .catch((err) => {
        console.log(err);
    });

// Complete Example:

// https://github.com/marcbelmont/deep-license-plate-recognition/tree/master/csharp/PlateRecognizer

// Function calling the API:

// https://github.com/marcbelmont/deep-license-plate-recognition/blob/master/csharp/PlateRecognizer/PlateReader.cs#L23

// Complete Example:

// https://github.com/marcbelmont/deep-license-plate-recognition/tree/master/java/PlateRecognizer

// Function calling the API:

// https://github.com/marcbelmont/deep-license-plate-recognition/blob/master/java/PlateRecognizer/src/main/java/com/mycompany/numberplate/recognize.java#L17    

// Complete Android App Example:

// https://github.com/parkpow/alpr-anpr-android/

// Complete Example (Windows or Linux):

// https://github.com/marcbelmont/deep-license-plate-recognition/tree/master/java/PlateRecognizer

// Function calling the API:

// https://github.com/marcbelmont/deep-license-plate-recognition/blob/master/cpp/linux/numberPlate.cpp#L25
// https://github.com/marcbelmont/deep-license-plate-recognition/blob/master/cpp/windows/ConsoleApplication2/ConsoleApplication2.cpp#L29

{
    "processing_time": 288.758,
    "results": [
        {
            "box": {
                "xmin": 143,
                "ymin": 481,
                "xmax": 282,
                "ymax": 575
            },
            "plate": "nhk552",
            "region": {
                "code": "gb",
                "score": 0.747
            },
            "vehicle": {
                "score": 0.798,
                "type": "Sedan",
                "box": {
                    "xmin": 67,
                    "ymin": 113,
                    "xmax": 908,
                    "ymax": 653
                }
            },
            "score": 0.904,
            "candidates": [
                {
                    "score": 0.904,
                    "plate": "nhk552"
                }
            ],
            "dscore": 0.99,
            // Make Model, Orientation and Color are only available if you set mmc=true
            "model_make": [
                {
                    "make": "Riley",
                    "model": "RMF",
                    "score": 0.306
                }
            ],
            "color": [
                {
                    "color": "black",
                    "score": 0.937
                }
            ],
            "orientation": [
                {
                    "orientation": "Front",
                    "score": 0.937
                }
            ]
        }
    ],
    "filename": "1617_7M83K_car.jpg",
    "version": 1,
    "camera_id": null,
    "timestamp": "2020-10-12T16:17:27.574008Z"
}

# Custom threshold and fast mode:
curl -F 'upload=@/path/to/car.jpg' \
-F config='{"mode":"fast", "threshold_d":0.2, "threshold_o":0.6}' \
-H 'Authorization: Token my-token******' \
https://api.platerecognizer.com/v1/plate-reader/

# Strict region matching:
curl -F 'upload=@/path/to/car.jpg' \
-F config='{"region":"strict"}' \
-F region=us-ca \
-H 'Authorization: Token my-token******' \
https://api.platerecognizer.com/v1/plate-reader/

# Prediction must include a vehicle:
curl -F 'upload=@/path/to/car.jpg' \
-F config='{"detection_rule":"strict"}' \
-H 'Authorization: Token my-token******' \
https://api.platerecognizer.com/v1/plate-reader/

import json
with open('/path/to/car.jpg', 'rb') as fp:
    response = requests.post(
        'https://api.platerecognizer.com/v1/plate-reader/',
        data=dict(config=json.dumps(dict(region="strict"))),
        files=dict(upload=fp),
        headers={'Authorization': 'Token my-token******'})

{
    "filename": "car.jpg",
    "timestamp": "2021-11-23 17:56:47.896406",
    "camera_id": "my-camera",
    "processing_time": 58.184,
    "results": [
        {
            "plate": {
                "type": "Plate",
                "score": 0.925,
                "box": {
                    "xmin": 146,
                    "ymin": 481,
                    "xmax": 276,
                    "ymax": 576
                },
                "props": {
                    "plate": [
                        {
                            "value": "nhk552",
                            "score": 0.838
                        }
                    ],
                    "region": [
                        {
                            "value": "gb",
                            "score": 0.931
                        }
                    ]
                }
            },
            "vehicle": {
                "type": "Sedan",
                "score": 0.834,
                "box": {
                    "xmin": 68,
                    "ymin": 103,
                    "xmax": 914,
                    "ymax": 643
                },
                "props": {
                    "make_model": [
                        {
                            "make": "Riley",
                            "model": "RMF",
                            "score": 0.339
                        }
                    ],
                    "orientation": [
                        {
                            "value": "Front",
                            "score": 0.939
                        }
                    ],
                    "color": [
                        {
                            "value": "black",
                            "score": 0.846
                        }
                    ]
                }
            }
        }
    ]
}

# Calling the API with just the image
curl -F 'upload=@/path/to/car.jpg' \
  http://localhost:8080/v1/plate-reader/

# Calling with API with optional parameters config and mmc
# The region is set to Mexico and California
curl -F 'upload=@/path/to/car.jpg' \
  -F regions=mx \
  -F regions=us-ca \
  -F mmc=true \
  -F config='{"mode":"fast"}' \
  http://localhost:8080/v1/plate-reader/

{
  "usage":{
    "max_calls":1000,
    "calls":44
  },
  "results":[
    // Same as cloud API example above.
  ],
  "camera_id": "null",
  "timestamp": "2020-01-16 17:00:00",
  "filename":"car.jpg"
}

{
    "version": "1.3.8",
    "license_key": "XXX",
    "webhooks": []
}

{
  "hook": {
    "target": "http://localhost:8081/",
    "id": 2,
    "event": "image.done"
  },
  "data": {
    "processing_time": 0.186,
    "timestamp": "2019-08-31T14:22:06.983Z",
    "results": [
      {
        "box": {
          "xmin": 563,
          "ymin": 530,
          "ymax": 579,
          "xmax": 702
        },
        "plate": "765410",
        "score": 0.9131534678711563,
        "dscore": 0.4084282568529709
      },
      {
        "box": {
          "xmin": 563,
          "ymin": 530,
          "ymax": 579,
          "xmax": 702
        },
        "plate": "830265",
        "score": 0.7700640306685624,
        "dscore": 0.8493143507578083
      }
    ],
    "filename": "14_22_test.jpeg",
    "version": 1,
    "camera_id": null
  }
}

curl -H 'Authorization: Token my-token******' \
  https://api.platerecognizer.com/v1/statistics/

{
  "usage": {
    "month": 1,
    "calls": 128,
    "year": 2019,
    "resets_on": "2019-01-14T00:00:00Z"
  },
  "total_calls": 2500
}