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Invoice OCR

Automatically extract data from unstructured invoices

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Mindee’s Invoice OCR API uses deep learning to automatically, accurately, and instantaneously parse invoices in your applications. It takes the API a few seconds to extract data from your PDFs or photos of invoices. The API extracts data such as:

  • Line items
  • Due date
  • Invoice date
  • Invoice number
  • Reference numbers
  • Locale & currency
  • Payment details (IBAN, Swift, Bic, Account number...)
  • Supplier company registrations (SIRET, EIN, VAT number...)
  • Supplier name
  • Taxes details
  • Total amount including taxes
  • Total net amount (excluding taxes)
  • Customer address
  • Customer company registrations
  • Customer name
  • Supplier address

Supported Countries

We officially support the following countries, which doesn't prevent you to use the API for invoices from different locations: you may get the country-specific data like taxes.

North America

United States & Canada

Europe

Austria, Belgium, Croatia, Czech Republic, Denmark, Estonia, Finland, France, Germany, Hungary, Iceland, Ireland, Italy, Latvia, Luxembourg, Monaco, Netherlands, Norway, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden, Switzerland & United Kingdom

Set up the API

📘

Before making any API calls, you need to have created your API key.

  1. You'll need to get an invoice. This can be a recently received invoice or you can google for free invoice samples that you can download to test with. Alternatively, you can use the sample invoice provided below.
    sample invoice

  2. Access your Invoice API by clicking on the Invoice card in the APIs Store.

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  1. From the left navigation, go to documentation > API reference, you'll find sample code in popular languages and command line.
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curl -X POST \
  https://api.mindee.net/v1/products/mindee/invoices/v3/predict \
  -H 'Authorization: Token my-api-key-here' \
  -F [email protected]/path/to/your/file.png

import requests

url = "https://api.mindee.net/v1/products/mindee/invoices/v3/predict"

with open("/path/to/my/file", "rb") as myfile:
    files = {"document": myfile}
    headers = {"Authorization": "Token my-api-key-here"}
    response = requests.post(url, files=files, headers=headers)
    print(response.text)

// works for NODE > v10
const axios = require('axios');
const fs = require("fs");
const FormData = require('form-data')

async function makeRequest() {
    let data = new FormData()
    data.append('document', fs.createReadStream('./file.jpg'))
    const config = {
        method: 'POST',
        url: 'https://api.mindee.net/v1/products/mindee/invoices/v3/predict',
        headers: { 
          'Authorization':'Token my-api-key-here',
          ...data.getHeaders()
           },
        data
    }

    try {
      let response = await axios(config)
      console.log(response.data);
    } catch (error) {
      console.log(error)
    }

}

makeRequest()

# tested with Ruby 2.5
require 'uri'
require 'net/http'
require 'net/https'
require 'mime/types'

url = URI("https://api.mindee.net/v1/products/mindee/invoices/v3/predict")
file = "/path/to/your/file.png"

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Token my-api-key-here'
request.set_form([['document', File.open(file)]], 'multipart/form-data')

response = http.request(request)
puts response.read_body

<form onsubmit="mindeeSubmit(event)" >
  <input type="file" id="my-file-input" name="file" />
  <input type="submit" />
</form>

<script type="text/javascript">
const mindeeSubmit = (evt) => {
  evt.preventDefault()
  let myFileInput = document.getElementById('my-file-input');
  let myFile = myFileInput.files[0]
  if (!myFile) { return }
  let data = new FormData();
  data.append("document", myFile, myFile.name);

  let xhr = new XMLHttpRequest();

  xhr.addEventListener("readystatechange", function () {
    if (this.readyState === 4) {
      console.log(this.responseText);
    }
  });

  xhr.open("POST", "https://api.mindee.net/v1/products/mindee/invoices/v3/predict");
  xhr.setRequestHeader("Authorization", "Token my-api-key-here");
  xhr.send(data);
}
</script>
  • Replace my-api-key-here with your new API key, or use the select an API key feature and it will be filled automatically.
  • Copy and paste the sample code of your desired choice in your application, code environment, terminal etc.
  • Replace /path/to/your/file/png with the path to your invoice.

❗️

Always remember to replace your API key!

  1. Run your code. You will receive a JSON response with the invoice details.

API Response

Below is the full sample JSON response you get when you call the API. Since the response is quite verbose, we will walk through the fields section by section.

{
  "api_request": {
    "error": {},
    "resources": [
      "document"
    ],
    "status": "success",
    "status_code": 201,
    "url": "http://api.mindee.net/v1/products/mindee/invoices/v3/predict"
  },
  "document": {
    "id":  "ecdbe7bd-1037-47a5-87a8-b90d49475a1f",
    "name": "sample_invoce.jpeg",
    "n_pages": 1,
    "is_rotation_applied": true,
    "inference": {
      "started_at": "2021-05-06T16:37:28+00:00",
      "finished_at": "2021-05-06T16:37:29+00:00",
      "processing_time": 1.125,
      "pages": [
        {
          "id": 0,
          "orientation": {"value": 0},
          "prediction": { .. },
          "extras": {}
        }
      ],
      "prediction": { .. },
      "extras": {}
    }
  }
}

You can find the prediction within the prediction key found in two locations:

  • In document > inference > prediction for document-level predictions: it contains the different fields extracted at the document level, meaning that for multi-pages PDFs, we reconstruct a single invoice object using all the pages.
  • In document > inference > pages[ ] > prediction for page-level predictions: it gives the prediction for each page independently. With images, there is only one element on this array, but with PDFs, you can find the extracted data for each PDF page.

Each predicted field may contain one or several values:

  • a confidence score
  • a polygon highlighting the information location
  • a page_id where the information was found (document level only)
{
  "prediction": {
    "supplier_company_registrations": [
     {
      "confidence": 0.99,
      "page_id": 0,
      "polygon": [[ 0.515, 0.962 ], [ 0.59, 0.962 ], [ 0.59, 0.973 ], [ 0.515, 0.973 ]],
      "type": "SIRET",
      "value": "XXX81125600010"
    },
    {
      "confidence": 0.99,
      "page_id": 0,
      "polygon": [[ 0.658, 0.963 ], [ 0.729, 0.963 ], [ 0.729, 0.973 ], [ 0.658, 0.973 ]],
      "type": "VAT NUMBER",
      "value": "FR44837811XXX"
      }
    ],
    "customer_name": {
      "confidence": 0.84,
      "page_id": 0,
      "polygon": [[0.035, 0.284], [0.098, 0.284], [0.098, 0.296], [0.035, 0.296]],
      "value": "JIRO DOI"
    },
    "customer_address": {
      "confidence": 0.3,
      "page_id": 0,
      "polygon": [[0.035, 0.304], [0.214, 0.304], [0.214, 0.353], [0.035, 0.353]],
      "value": "1954 Bloon Street West Toronto, ON, M6P 3K9 Canada"
    },
    "customer_company_registrations":[
      {
      "confidence": 0.84,
      "page_id": 0,
      "polygon": [[0.113, 0.251], [0.206, 0.251], [0.206, 0.266], [0.113, 0.266]],
      "type": "TIN",
      "value": "736952710"
         }
    ],
    "date": {
      "confidence": 0.99,
      "page_id": 0,
      "polygon": [[0.842, 0.305], [0.931, 0.305], [0.931, 0.319], [0.842, 0.319]],
      "value": "2018-09-25"
    },
    "document_type": {
      "value": "INVOICE"
    },
    "due_date": {
      "confidence": 0.93,
      "page_id": 0,
      "polygon": [[0.84, 0.326], [0.943, 0.326], [0.943, 0.34], [0.84, 0.34]],
      "raw": "receipt Upon",
      "value": "2018-09-25"
    },
    "invoice_number": {
      "confidence": 0.99,
      "page_id": 0,
      "polygon": [[0.843, 0.265], [0.861, 0.265], [0.861, 0.28], [0.843, 0.28]],
      "value": "14"
    },
    "reference_numbers": [
          {
            "confidence": 0.91,
            "polygon": [[0.84, 0.284],[0.914, 0.284],[0.914, 0.298],[0.84, 0.298]],
            "value": "AD29094"
          }
    ], 
    "locale": {
      "confidence": 0.93,
      "currency": "CAD",
      "language": "en"
    },
    "orientation": {
      "confidence": 0.99,
      "degrees": 0
    },
    "supplier_payment_details": [
     {
      "account_number": "XXXX",
      "confidence": 0.95,
      "iban": "XXXX",
      "page_id": 0,
      "polygon": [[0.035, 0.304], [0.214, 0.304], [0.214, 0.353], [0.035, 0.0353]],
      "routing_number": "XXX",
      "swift": "XXX"
     }
   ],
    "supplier_name": {
      "confidence": 0.72,
      "page_id": 0,
      "polygon": [[0.164, 0.087], [0.4, 0.087], [0.4, 0.147], [0.164, 0.147]],
      "value": "TURNPIKE DESIGNS CO."
    },
    "supplier_address": {
      "confidence": 0.49,
      "page_id": 0,
      "polygon": [[0.756, 0.128], [0.964, 0.128], [0.964, 0.162], [0.756, 0.162]],
      "value": "156 University Ave, Toronto ON, Canada M5H 2H7"
    },
    "taxes":[
      {
      "confidence": 0.76,
      "page_id": 0,
      "polygon": [[0.785, 0.745], [0.965, 0.745], [0.965, 0.758], [0.785, 0.758]],
       "rate": 8,
       "value": 193.2
            }
    ],
    "total_net": {
      "confidence": 0,
      "page_id": null,
      "polygon": [[0.886, 0.839], [0.971, 0.839], [0.971, 0.858], [0.886, 0.858]],
      "value": 2608.2
    },
    "total_amount": {
      "confidence": 0.99,
      "page_id": 0,
      "polygon": [[0.887, 0.84], [0.97, 0.84], [0.97, 0.858], [0.887, 0.858]],
      "value": 2608.2
    }
  }
}

Depending on the field type specified, additional attributes can be extracted from the invoice object. Using the above invoice example, the following are the basic fields that can be extracted.

Line items

  • line_items: In the JSON response below, we have the list of items included in the body of the invoice. Each item may contain:
    • description (String Generic): The description of the item
    • product_code (String Generic): the code that identifies the product in the line. It can be a reference number, a product ID, an Article code…
    • quantity (number)
    • unit_price (number)
    • total_amount (number): The line total amount
    • tax_amount (number)
    • tax_rate (number): Returned in %
{
  "line_items": [
          {
            "confidence": 0.97,
            "description": "Platinum web hosting package Down 35mb, Up 100mb",
            "polygon": [
              [0.035, 0.501],
              [0.965, 0.501],
              [0.965, 0.537],
              [0.035, 0.537]
            ],
            "product_code": null,
            "quantity": 1,
            "tax_amount": null,
            "tax_rate": null,
            "total_amount": 65,
            "unit_price": 65
          },
          {
            "confidence": 0.97,
            "description": "2 page website design Includes basic wireframes, and responsive templates",
            "polygon": [
              [0.035, 0.562],
              [0.964, 0.562],
              [0.964, 0.599],
              [0.035, 0.599]
            ],
            "product_code": null,
            "quantity": 3,
            "tax_amount": null,
            "tax_rate": null,
            "total_amount": 2100,
            "unit_price": 2100
          },
          {
            "confidence": 0.96,
            "description": "Mobile designs Includes responsive navigation",
            "polygon": [
              [0.035, 0.626],
              [0.964, 0.626],
              [0.964, 0.662],
              [0.035, 0.662]
            ],
            "product_code": null,
            "quantity": 1,
            "tax_amount": null,
            "tax_rate": null,
            "total_amount": 250,
            "unit_price": 250
          }
        ]
}

Reference numbers

  • reference_numbers: In the JSON response we have a list of variable size with references extracted including PO numbers, reference numbers or more rarely project numbers. 
{
"reference_numbers": [
          {
            "confidence": 1,
            "polygon": [
              [0.628, 0.374],
              [0.703, 0.374],
              [0.703, 0.383],
              [0.628, 0.383]
            ],
            "value": "PO-00001827"
          },
          {
            "confidence": 1,
            "polygon": [
              [0.156, 0.901],
              [0.211, 0.901],
              [0.211, 0.908],
              [0.156, 0.908]
            ],
            "value": "1C5H17N"
          }
        ]
}

Customer Information

  • customer_name: In the JSON response, we have the value of the customer name as found on the invoice.
{
  "customer_name": {
    "confidence": 0.84,
    "page_id": 0,
    "polygon": [[0.035, 0.284], [0.098, 0.298], [0.098, 0.296], [0.035, 0.296]],
    "value": "JIRO DOI"
  }
}
  • customer_address: In the JSON response, we have the value of the customer address as found on the invoice.
{
  "customer_address": {
    "confidence": 0.3,
    "page_id": 0,
    "polygon": [[0.035, 0.304], [0.214, 0.304], [0.214, 0.353], [0.035, 0.0353]],
    "value": "1954 Bloon Street West Toronto, ON, M6P 3K9 Canada"
  }
}

{
  "customer_company_registrations": [
    {
      "confidence": 0.99,
      "page_id": 0,
      "polygon": [[ 0.515, 0.962 ], [ 0.59, 0.962 ], [ 0.59, 0.973 ], [ 0.515, 0.973 ]],
      "type": "SIRET",
      "value": "XXX81125600010"
    },
    {
      "confidence": 0.99,
      "page_id": 0,
      "polygon": [[ 0.658, 0.963 ], [ 0.729, 0.963 ], [ 0.729, 0.973 ], [ 0.658, 0.973 ]],
      "type": "VAT NUMBER",
      "value": "FR44837811XXX"
    }
  ]
}

Date

  • invoice date: In the JSON response below, we have the value of the invoice date in an ISO format(yyyy-mm-dd).
{
  "date": {
    "confidence": 0.99,
    "page_id": 0,
    "polygon": [[0.84, 0.305], [0.932, 0.305], [0.932, 0.318], [0.84, 0.318]],
    "value": "2018-09-25"
  }
}
  • due_date: In the JSON response below, we have the value of the invoice due_ date in an ISO format(yyyy-mm-dd).
{
  "due_date": {
    "confidence": 0.86,
    "page_id": 0,
    "polygon": [[0.841, 0.323], [0.941, 0.323], [0.941, 0.338], [0.841, 0.338]],
    "raw": "Upon receipt",
    "value": "2018-09-25"
  }
}

Locale

  • locale: In the JSON response, we have the currency and language found on the invoice.
    • language (String): Language code in ISO 639-1 format as seen on the invoice. The following language codes are supported: ca, de, en, es, fr, it, nl and pt.
    • currency (String): Currency code in ISO 4217 format as seen on the invoice. The following country codes are supported: USD, EUR, GBP, CAD, CHF, AED, AUD, BRL, CNY, COP, CZK, DKK, GNF, HKD, HUF, JPY, NOK, NZD, PLN, SEK, SGD, XPF
{
  "locale": {
    "confidence": 0.94,
    "currency": "CAD",
    "language": "en"
  }
}

Orientation

  • orientation: The orientation field is only available at the page level as it describes whether the page image should be rotated to be upright. The rotation value is also conveniently available in the JSON response at:
    document > inference > pages [ ] > orientation > value.
    If the page requires rotation for correct display, the orientation field gives a prediction among these 3 possible outputs:
    • 0 degree: the page is already upright
    • 90 degrees: the page must be rotated clockwise to be upright
    • 270 degrees: the page must be rotated counterclockwise to be upright

In our example, the receipt doesn't require any rotation.

{
  "orientation": {
    "confidence": 0.99,
    "degrees": 0
  }
}

📘

All polygon fields across the JSON response are already rotated accordingly!

Supplier Information

  • supplier_payment_details: On some invoices, there are many payment details written such as account number, IBAN, routing number, BIC etc. Our Invoice OCR extracts all of them. In the JSON response below, we have the list of the suppliers' payment details, each item contains different fields and they are set to null or filled with the right value depending on the invoice:
{
  "supplier_payment_details": [
   {
    "account_number": "XXXX",
    "confidence": 0.95,
    "iban": "XXXX",
    "page_id": 0,
    "polygon": [[0.035, 0.304], [0.214, 0.304], [0.214, 0.353], [0.035, 0.0353]],
    "routing_number": "XXX",
    "swift": "XXX"
         }
  ]
}

{
  "supplier_company_registrations": [
    {
    "confidence": 0.99,
    "page_id": 0,
    "polygon": [[0.515, 0.962], [0.59, 0.962], [0.59, 0.973], [0.515, 0.973]],
    "type": "SIRET",
    "value": "XXX81125600010"
         },

        {
    "confidence": 0.99,
    "page_id": 0,
    "polygon": [[0.658, 0.963], [0.729, 0.963], [0.729, 0.973], [0.658, 0.973]],
    "type": "VAT",
    "value": "FR44837811XXX"
    }
 ]
}
  • supplier_name: In the JSON response below, we have the value of the supplier name as written in the invoice.
{
  "supplier_name": {
    "confidence": 0.11,
    "page_id": 0,
    "polygon": [[0.165, 0.089], [0.385, 0.089], [0.385, 0.145], [0.165, 0.145]],
    "value": "DESIGNS TURNPIKE CO"
  }
}
  • supplier_address: In the JSON response, we have the value of the supplier address as found on the invoice.
{
  "supplier_address": {
    "confidence": 0.49,
    "page_id": 0,
    "polygon": [[0.756, 0.128], [0.964, 0.128], [0.964, 0.162], [0.756, 0.162]],
    "value": "156 University Ave, Toronto ON, Canada M5H 2H7"
  }
}

Taxes

  • taxes: In the JSON response below, we have the list of taxes detected in the invoice. Each tax item includes:
    • value (number): The tax amount.
    • rate (number): The tax rate.
{
  "taxes": [
    {
    "confidence": 0.76,
    "page_id": 0,
    "polygon": [[0.784, 0.744], [0.965, 0.744], [0.965, 0.758], [0.784, 0.758]],
    "rate": 8.0,
    "value": 193.2
        }
    ]
}

Total Amounts

  • total_amount: In the JSON response below, we have the value of the total amount including taxes.
{
  "total_amount": {
    "confidence": 0.99,
    "page_id": 0,
    "polygon": [[0.886, 0.839], [0.971, 0.839], [0.971, 0.858], [0.886, 0.858]],
    "value": 2608.2
  }
}
  • total_net: In the JSON response below, we have the value of the total amount excluding taxes.
{
  "total_net": {
    "confidence": 0.4,
    "page_id": 0,
    "polygon": [[0.886, 0.839], [0.971, 0.839], [0.971, 0.858], [0.886, 0.858]],
    "value": 2608.2
  }
}

 

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Updated 3 months ago