Integration

Rekor CarCheck® is designed as a REST-based API, allowing you to interact with it using a variety of programming languages and operating systems. API calls can be made using different methods according to your development preferences. This flexibility ensures that you have control over how you interact with the API, enabling seamless integration into your applications.

Data Analysis and Retrieval

One of the key features of Rekor CarCheck® is its ability to analyze vehicle images from multiple sources. You can send vehicle image data from a local machine, server, or any web-based URL to Rekor CarCheck®. Upon receiving the image data, the API performs a comprehensive analysis, extracting information about the license plate and the corresponding vehicle. The results are returned in the form of JSON data, providing you with detailed insights about the recognized license plate and the associated vehicle.

API Endpoints

Rekor CarCheck® offers several endpoints that facilitate different functionalities within the API. Each endpoint serves a specific purpose, allowing you to perform various operations related to license plate recognition and vehicle identification.

Before getting started, you will want to make sure you have your secret key ready to go. Your secret key is available within the Web Dashboard. The following endpoints are available:

Send an image for Rekor to analyze and provide metadata back The image is sent as a file using a form data POST

post

/recognize

Query parameters

secret_keystringrequired

The secret key used to authenticate your account. You can view your secret key by visiting https://cloud.openalpr.com/

recognize_vehicleinteger · enum

If set to 1, the vehicle will also be recognized in the image This requires an additional credit per request

Options: 0, 1

countrystringrequired

Defines the training data used by Rekor. "us" analyzes North-American style plates. "eu" analyzes European-style plates.

This field is required if using the "plate" task

return_imageinteger · enum

If set to 1, the image you uploaded will be encoded in base64 and sent back along with the response

Options: 0, 1

topninteger · min: 1 · max: 1000 · default: 10

The number of results you would like to be returned for plate candidates and vehicle classifications

is_croppedinteger · enum

When providing a plate or vehicle that is already cropped,
this performs a recognition against the full crop and does not attempt to localize the plate/vehicle

Options: 0, 1

Body

imagestring · binaryrequired

The image file that you wish to analyze

Responses

application/json

application/json

application/json

application/json

application/json

cURL

JavaScript

Python

HTTP

cURL

curl -L \
  --request POST \
  --url 'https://api.openalpr.com/v3/recognize?secret_key=text&country=text' \
  --header 'Content-Type: multipart/form-data' \
  --data '{"image":"text"}'

200

400

401

402

403

200

{
  "img_width": 1,
  "img_height": 1,
  "credit_cost": 1,
  "credits_monthly_used": 1,
  "credits_monthly_total": 1,
  "epoch_time": 1,
  "version": 1,
  "data_type": "alpr_results",
  "results": [
    {
      "plate": "text",
      "matches_template": 1,
      "requested_topn": 1,
      "processing_time_ms": 1,
      "confidence": 1,
      "region": "text",
      "region_confidence": 1,
      "vehicle_region": {
        "x": 1,
        "y": 1,
        "width": 1,
        "height": 1
      },
      "vehicle": {
        "color": [
          {
            "name": "text",
            "confidence": 1
          }
        ],
        "make": [
          {
            "name": "text",
            "confidence": 1
          }
        ],
        "make_model": [
          {
            "name": "text",
            "confidence": 1
          }
        ],
        "body_type": [
          {
            "name": "text",
            "confidence": 1
          }
        ],
        "orientation": [
          {
            "name": "text",
            "confidence": 1
          }
        ],
        "year": [
          {
            "name": "text",
            "confidence": 1
          }
        ]
      },
      "coordinates": [
        {
          "x": 1,
          "y": 1
        }
      ],
      "candidates": [
        {
          "plate": "text",
          "confidence": 1,
          "matches_template": 1
        }
      ]
    }
  ],
  "regions_of_interest": [
    {
      "x": 1,
      "y": 1,
      "width": 1,
      "height": 1
    }
  ],
  "vehicles": [
    {
      "x": 1,
      "y": 1,
      "width": 1,
      "height": 1,
      "details": {
        "color": [
          {
            "name": "text",
            "confidence": 1
          }
        ],
        "make": [
          {
            "name": "text",
            "confidence": 1
          }
        ],
        "make_model": [
          {
            "name": "text",
            "confidence": 1
          }
        ],
        "body_type": [
          {
            "name": "text",
            "confidence": 1
          }
        ],
        "orientation": [
          {
            "name": "text",
            "confidence": 1
          }
        ],
        "year": [
          {
            "name": "text",
            "confidence": 1
          }
        ]
      }
    }
  ],
  "processing_time": {
    "total": 1,
    "plates": 1,
    "vehicles": 1
  }
}

OK

Send an image for Rekor to analyze and provide metadata back The image is sent as a URL. The Rekor service will download the image and process it

post

/recognize_url

Query parameters

image_urlstringrequired

A URL to an image that you wish to analyze

secret_keystringrequired

The secret key used to authenticate your account. You can view your secret key by visiting https://cloud.openalpr.com/

recognize_vehicleinteger · enum

If set to 1, the vehicle will also be recognized in the image This requires an additional credit per request

Options: 0, 1

countrystringrequired

Defines the training data used by Rekor. "us" analyzes North-American style plates. "eu" analyzes European-style plates.

This field is required if using the "plate" task

return_imageinteger · enum

If set to 1, the image you uploaded will be encoded in base64 and sent back along with the response

Options: 0, 1

topninteger · min: 1 · max: 1000 · default: 10

The number of results you would like to be returned for plate candidates and vehicle classifications

Responses

application/json

application/json

application/json

application/json

application/json

cURL

JavaScript

Python

HTTP

cURL

curl -L \
  --request POST \
  --url 'https://api.openalpr.com/v3/recognize_url?image_url=text&secret_key=text&country=text'

200

400

401

402

403

200

{
  "img_width": 1,
  "img_height": 1,
  "credit_cost": 1,
  "credits_monthly_used": 1,
  "credits_monthly_total": 1,
  "epoch_time": 1,
  "version": 1,
  "data_type": "alpr_results",
  "results": [
    {
      "plate": "text",
      "matches_template": 1,
      "requested_topn": 1,
      "processing_time_ms": 1,
      "confidence": 1,
      "region": "text",
      "region_confidence": 1,
      "vehicle_region": {
        "x": 1,
        "y": 1,
        "width": 1,
        "height": 1
      },
      "vehicle": {
        "color": [
          {
            "name": "text",
            "confidence": 1
          }
        ],
        "make": [
          {
            "name": "text",
            "confidence": 1
          }
        ],
        "make_model": [
          {
            "name": "text",
            "confidence": 1
          }
        ],
        "body_type": [
          {
            "name": "text",
            "confidence": 1
          }
        ],
        "orientation": [
          {
            "name": "text",
            "confidence": 1
          }
        ],
        "year": [
          {
            "name": "text",
            "confidence": 1
          }
        ]
      },
      "coordinates": [
        {
          "x": 1,
          "y": 1
        }
      ],
      "candidates": [
        {
          "plate": "text",
          "confidence": 1,
          "matches_template": 1
        }
      ]
    }
  ],
  "regions_of_interest": [
    {
      "x": 1,
      "y": 1,
      "width": 1,
      "height": 1
    }
  ],
  "vehicles": [
    {
      "x": 1,
      "y": 1,
      "width": 1,
      "height": 1,
      "details": {
        "color": [
          {
            "name": "text",
            "confidence": 1
          }
        ],
        "make": [
          {
            "name": "text",
            "confidence": 1
          }
        ],
        "make_model": [
          {
            "name": "text",
            "confidence": 1
          }
        ],
        "body_type": [
          {
            "name": "text",
            "confidence": 1
          }
        ],
        "orientation": [
          {
            "name": "text",
            "confidence": 1
          }
        ],
        "year": [
          {
            "name": "text",
            "confidence": 1
          }
        ]
      }
    }
  ],
  "processing_time": {
    "total": 1,
    "plates": 1,
    "vehicles": 1
  }
}

OK

Send an image for Rekor to analyze and provide metadata back The image is sent as base64 encoded bytes.

post

/recognize_bytes

Query parameters

secret_keystringrequired

The secret key used to authenticate your account. You can view your secret key by visiting https://cloud.openalpr.com/

recognize_vehicleinteger · enum

If set to 1, the vehicle will also be recognized in the image This requires an additional credit per request

Options: 0, 1

countrystringrequired

Defines the training data used by Rekor. "us" analyzes North-American style plates. "eu" analyzes European-style plates.

This field is required if using the "plate" task

return_imageinteger · enum

If set to 1, the image you uploaded will be encoded in base64 and sent back along with the response

Options: 0, 1

topninteger · min: 1 · max: 1000 · default: 10

The number of results you would like to be returned for plate candidates and vehicle classifications

Body

string

Responses

application/json

application/json

application/json

application/json

application/json

cURL

JavaScript

Python

HTTP

cURL

curl -L \
  --request POST \
  --url 'https://api.openalpr.com/v3/recognize_bytes?secret_key=text&country=text' \
  --header 'Content-Type: application/json'

200

400

401

402

403

200

{
  "img_width": 1,
  "img_height": 1,
  "credit_cost": 1,
  "credits_monthly_used": 1,
  "credits_monthly_total": 1,
  "epoch_time": 1,
  "version": 1,
  "data_type": "alpr_results",
  "results": [
    {
      "plate": "text",
      "matches_template": 1,
      "requested_topn": 1,
      "processing_time_ms": 1,
      "confidence": 1,
      "region": "text",
      "region_confidence": 1,
      "vehicle_region": {
        "x": 1,
        "y": 1,
        "width": 1,
        "height": 1
      },
      "vehicle": {
        "color": [
          {
            "name": "text",
            "confidence": 1
          }
        ],
        "make": [
          {
            "name": "text",
            "confidence": 1
          }
        ],
        "make_model": [
          {
            "name": "text",
            "confidence": 1
          }
        ],
        "body_type": [
          {
            "name": "text",
            "confidence": 1
          }
        ],
        "orientation": [
          {
            "name": "text",
            "confidence": 1
          }
        ],
        "year": [
          {
            "name": "text",
            "confidence": 1
          }
        ]
      },
      "coordinates": [
        {
          "x": 1,
          "y": 1
        }
      ],
      "candidates": [
        {
          "plate": "text",
          "confidence": 1,
          "matches_template": 1
        }
      ]
    }
  ],
  "regions_of_interest": [
    {
      "x": 1,
      "y": 1,
      "width": 1,
      "height": 1
    }
  ],
  "vehicles": [
    {
      "x": 1,
      "y": 1,
      "width": 1,
      "height": 1,
      "details": {
        "color": [
          {
            "name": "text",
            "confidence": 1
          }
        ],
        "make": [
          {
            "name": "text",
            "confidence": 1
          }
        ],
        "make_model": [
          {
            "name": "text",
            "confidence": 1
          }
        ],
        "body_type": [
          {
            "name": "text",
            "confidence": 1
          }
        ],
        "orientation": [
          {
            "name": "text",
            "confidence": 1
          }
        ],
        "year": [
          {
            "name": "text",
            "confidence": 1
          }
        ]
      }
    }
  ],
  "processing_time": {
    "total": 1,
    "plates": 1,
    "vehicles": 1
  }
}

OK

Get a list of available results for plate and vehicle recognition

get

/config

Responses

application/json

cURL

JavaScript

Python

HTTP

cURL

curl -L \
  --url 'https://api.openalpr.com/v3/config'

200

200

{
  "vehicle_labels": {
    "bodytype": [
      "sedan-compact"
    ],
    "orientation": [
      45
    ],
    "color": [
      "blue"
    ],
    "make": [
      "volvo"
    ],
    "makemodel": [
      "volvo_v40"
    ],
    "year": [
      "2000-2004"
    ]
  },
  "countries": [
    {
      "code": "us",
      "name": "North America"
    }
  ]
}

ok