Receipt OCR

Automatically extract data from receipts and bills

Mindee’s receipt OCR API uses deep learning to automatically, accurately, and instantaneously parse your receipt details. In under a second, the API extracts a set of data from your PDFs or photos of receipts, including:

  • Expense category
  • Locale & currency
  • Receipt date
  • Receipt time
  • Supplier
  • Taxes details
  • Total tax
  • Tip & Gratuity (typed and handwritten)
  • Total amount (typed and handwritten)
  • Total net (excluding taxes)

The Receipt OCR API supports handwritten characters for Tip&Gratuity and Total amount fields.

Set up the API

📘

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

  1. You'll need a receipt. You can use the sample receipt provided below.
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  1. Access your Receipt API by clicking on the Expense Receipts 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/expense_receipts/v4/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/expense_receipts/v4/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/expense_receipts/v4/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/expense_receipts/v4/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/expense_receipts/v4/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 or terminal.
  • Replace /path/to/my/file with the path to your receipt.

❗️

Always remember to replace your API key!

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

API Response

Here is the full JSON response you get when you call the API:

{
  "api_request": {
    "error": {},
    "resources": [
      "document"
    ],
    "status": "success",
    "status_code": 201,
    "url": "https://api.mindee.net/v1/products/mindee/expense_receipts/v4/predict"
  },
  "document": {
    "id": "cc875b84-e83e-4799-aabe-4b2c18f44b27",
    "name": "sample_receipt.jpg",
    "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": 1.121,
      "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 receipt 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": {
        "category": {
            "confidence": 0.94,
            "value": "food"
        },
        "date": {
            "confidence": 0.99,
            "page_id": 0,
            "polygon": [
                [0.238, 0.132],
                [0.353, 0.132],
                [0.353, 0.161],
                [0.238, 0.161]
            ],
            "value": "2014-07-07"
        },
        "locale": {
            "confidence": 0.69,
            "country": "US",
            "currency": "USD",
            "language": "en",
            "value": "en-US"
        },
        "supplier": {
            "confidence": 0.97,
            "page_id": 0,
            "polygon": [
                [0.386, 0.228],
                [0.479, 0.228],
                [0.479, 0.252],
                [0.386, 0.252]
            ],
            "value": "LOGANS"
        },
        "taxes": [
            {
                "basis": null,
                "code": "TAX",
                "confidence": 0.97,
                "page_id": 0,
                "polygon": [
                    [0.147, 0.65],
                    [0.78, 0.65],
                    [0.78, 0.679],
                    [0.147, 0.679]
                ],
                "rate": null,
                "value": 3.34
            }
        ],
        "time": {
            "confidence": 0.99,
            "page_id": 0,
            "polygon": [
                [0.635, 0.142],
                [0.778, 0.142],
                [0.778, 0.168],
                [0.635, 0.168]
            ],
            "value": "20:20"
        },
        "tip": {
            "confidence": 0.89,
            "page_id": 0,
            "polygon": [
                [0.6, 0.752],
                [0.774, 0.752],
                [0.774, 0.801],
                [0.6, 0.801]
            ],
            "value": 10
        },
        "total_amount": {
            "confidence": 0.05,
            "page_id": 0,
            "polygon": [
                [0.61, 0.813],
                [0.773, 0.813],
                [0.773, 0.87],
                [0.61, 0.87]
            ],
            "value": 53.82
        },
        "total_net": {
            "confidence": 0.99,
            "page_id": 0,
            "polygon": [
                [0.698, 0.625],
                [0.78, 0.625],
                [0.78, 0.649],
                [0.698, 0.649]
            ],
            "value": 40.48
        },
        "total_tax": {
            "confidence": 0.97,
            "page_id": 0,
            "polygon": [],
            "value": 3.34
        }
    }
}

Extracted receipt data

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

Category

  • category: The API makes a prediction on the type of purchase. In the following example, it is 99% sure it is food. The possible categories that can be extracted are:
    • accommodation
    • food
    • gasoline
    • parking
    • transport
    • toll
    • telecom
    • miscellaneous
{
  "category": {
    "confidence": 0.99,
    "value": "food"
  }
}

Date

{
  "date": {
    "confidence": 0.99,
    "page_id": 0,
    "polygon": [[0.479, 0.173], [0.613, 0.173], [0.613, 0.197], [0.479, 0.197]],
    "value": "2016-02-26"
  }
}

Locale & currency

  • locale: From the receipt, the API can predict where the purchase was made, the language, and the currency. Check the documentation for the latest support. At the time of writing, support is centered on Europe and North America.
    • 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.
    • country (String): Country code in ISO 3166-1 alpha-2 format as seen on the invoice. The following country codes are supported: CA, CH, DE, ES, FR, GB, IT, NL, PT, and US.
    • currency (String): Currency code in ISO 4217 format as seen on the receipt. We support the following 44 currencies:
Europe (13)North America (3)South America (4)Middle East (5)Asia (12)Africa (6)Australia (1)
EUR, GBP, CHF, CZK, NOK, SEK, HUF, RON, PLN, RUB, DKK, XPF, TRYUSD, CAD, MXNCOP, BRL, CLP, ARSAED, SAR, QAR, ILS, OMRCNY, PHP, SGD, HKD, JPY, MYR, KRW, TWD, THB, VND, IMR, IDRDZD, MAD, TND, XOF, ZAR, XAFAUD
{
  "locale": {
    "confidence": 0.82,
    "country": "GB",
    "currency": "GBP",
    "language": "en",
    "value": "en-GB"
  }
}

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

📘

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

Supplier

  • supplier: In the JSON response below, we have the value of the merchant as found on the receipt.
{
  "supplier": {
    "confidence": 0.71,
    "page_id": 0,
    "polygon": [[0.394, 0.068], [0.477, 0.068], [0.477, 0.087], [0.394, 0.087]],
    "value": "CLACHAN"
  }
}

Taxes

  • taxes: In the JSON response below, we have the list of taxes detected in the receipt. Each of these items includes:
    • value: the amount of the tax line in the receipt currency
    • rate: float between 0 and 1
    • basis: the amount used to calculate the tax
    • code: the tax code. The output is one of the following: VAT, TVA, MWST, IVA, BTW, UST, GST, QST, PST, HST, RST, MERCHANT TAX, GOVERNMENT TAX, TRANSPORTATION TAX, EXCISE TAX, COUNTY TAX, CITY TAX, STATE TAX, LOCAL TAX, SALES TAX, ACCOMMODATION TAX, FOOD TAX, BEVERAGE TAX, FLIGHT TAX, TAX
{
  "taxes": [
    {
      "code": "VAT",
      "confidence": 0.98,
      "page_id": 0,
      "polygon": [[0.19, 0.403], [0.698, 0.403], [0.698, 0.432], [0.19, 0.432]],
      "rate": 20.0,
      "basis": 8.50,
      "value": 1.7
    }
  ]
}

Total tax

  • total_tax: Total tax amount of the purchase.
{
  "total_tax": {
    "confidence": 0.79,
    "page_id": 0,
    "polygon": [[0.549, 0.619], [0.715, 0.619], [0.715, 0.64], [0.549, 0.64]],
    "value": 2.42
  }
}

Tip & Gratuity

  • tip: Total amount of tip and gratuity. Both typed and handwritten characters are supported.
{
  "tip": {
    "confidence": 0.29,
    "page_id": 0,
    "polygon": [[0.549, 0.619], [0.715, 0.619], [0.715, 0.64], [0.549, 0.64]],
    "value": 12.00
  }
}

Time

  • time: ISO formatted time as seen on the receipt in HH: MM format.
{
  "time": {
    "confidence": 0.99,
    "page_id": 0,
    "polygon": [[0.62, 0.173], [0.681, 0.173], [0.681, 0.191], [0.62, 0.191]],
    "value": "15:20"
  }
}

Total amount

  • total_amount: Perhaps the most important part of the receipt is the total spent including taxes, discounts, fees, tips, and gratuity. The Receipt OCR API supports both typed and handwritten characters for this field. The output comes with a confidence score and the bounding box indicating the location on the receipt.
{
  "total_amount": {
    "confidence": 0.99,
    "page_id": 0,
    "polygon": [[0.549, 0.619], [0.715, 0.619], [0.715, 0.64], [0.549, 0.64]],
    "value": 10.2
  }
}

Total net (excluding taxes)

  • total_net: Total amount of the purchase excluding taxes.
{
  "total_net": {
    "confidence": 0.89,
    "page_id": 0,
    "polygon": [[0.549, 0.619], [0.715, 0.619], [0.715, 0.64], [0.549, 0.64]],
    "value": 14.27
  }
}

 

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