# Business Cards OCR

Mindee’s Business Cards OCR API uses deep learning to automatically, accurately, and instantaneously parse your documents details. In a few seconds, the API extracts a set of data from your PDFs or photos of business cards, including:

* Firstname
* Lastname
* Job Title
* Company
* Email
* Phone Number
* Mobile Number
* Fax Number
* Address
* Website
* social Media

The Business Cards OCR API supports documents from any geographies and languages.

## Set up the API

{% hint style="info" %}
**Create an API key**

To begin using the Mindee V1 OCR API, your first step is to [create your V1 API key](https://docs.mindee.com/v1/get-started/create-api-key).
{% endhint %}

1. To test your API, you can use the sample document provided below.

   <figure><img src="https://126655343-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F2al1MDqAP9Dg9iDRjkWg%2Fuploads%2Fgit-blob-8ca7f3854eacd14547cd0cd598cf8de49b2e2d1b%2F038e49b9f08d4f54db98a1a9d7bae6ff3010751233e968642e7336f834f582b2-image.png?alt=media" alt=""><figcaption></figcaption></figure>
2. Access your Business Card OCR API by clicking on the corresponding product card in the **Document Catalog**

   <figure><img src="https://126655343-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F2al1MDqAP9Dg9iDRjkWg%2Fuploads%2Fgit-blob-ad6e5df33effb17503c3872d9bb8709f866bb01c%2Fdbed09bcdf3106a2aca59ea3ac147ccc64621a2ac0fa3195c04ba0e90c1e0dfe-image.png?alt=media" alt=""><figcaption></figcaption></figure>
3. From the left navigation, go to [**documentation**](https://docs.mindee.com/v1/platform-ui-tour/api-documentation#api-reference) **> API Reference**, you'll find sample code in popular languages and command line.

{% tabs %}
{% tab title="Python" %}

```python
from mindee import Client, product, AsyncPredictResponse

# Init a new client
mindee_client = Client(api_key="my-api-key-here")

# Load a file from disk
input_doc = mindee_client.source_from_path("/path/to/the/file.ext")

# Load a file from disk and enqueue it.
result: AsyncPredictResponse = mindee_client.enqueue_and_parse(
    product.BusinessCardV1,
    input_doc,
)

# Print a brief summary of the parsed data
print(result.document)
```

{% endtab %}

{% tab title="Node.js" %}

```javascript
const mindee = require("mindee");
// for TS or modules:
// import * as mindee from "mindee";

// Init a new client
const mindeeClient = new mindee.v1.Client({ apiKey: "my-api-key-here" });

// Load a file from disk
const inputSource = mindeeClient.docFromPath("/path/to/the/file.ext");

// Parse the file
const apiResponse = mindeeClient.enqueueAndParse(
  mindee.v1.product.BusinessCardV1,
  inputSource
);

// Handle the response Promise
apiResponse.then((resp) => {
  // print a string summary
  console.log(resp.document.toString());
});
```

{% endtab %}

{% tab title=".NET" %}

```csharp
using Mindee;
using Mindee.Input;
using Mindee.Product.BusinessCard;

string apiKey = "my-api-key-here";
string filePath = "/path/to/the/file.ext";

// Construct a new client
MindeeClient mindeeClient = new MindeeClient(apiKey);

// Load an input source as a path string
// Other input types can be used, as mentioned in the docs
var inputSource = new LocalInputSource(filePath);

// Call the product asynchronously with auto-polling
var response = await mindeeClient
    .EnqueueAndParseAsync<BusinessCardV1>(inputSource);

// Print a summary of all the predictions
System.Console.WriteLine(response.Document.ToString());

// Print only the document-level predictions
// System.Console.WriteLine(response.Document.Inference.Prediction.ToString());
```

{% endtab %}

{% tab title="PHP" %}

```php
<?php

use Mindee\Client;
use Mindee\Product\BusinessCard\BusinessCardV1;

// Init a new client
$mindeeClient = new Client("my-api-key-here");

// Load a file from disk
$inputSource = $mindeeClient->sourceFromPath("/path/to/the/file.ext");

// Parse the file asynchronously
$apiResponse = $mindeeClient->enqueueAndParse(BusinessCardV1::class, $inputSource);

echo $apiResponse->document;
```

{% endtab %}

{% tab title="Ruby" %}

```ruby
#
# Install the Ruby client library by running:
# gem install mindee
#

require 'mindee'

# Init a new client
mindee_client = Mindee::Client.new(api_key: 'my-api-key')

# Load a file from disk
input_source = mindee_client.source_from_path('/path/to/the/file.ext')

# Parse the file
result = mindee_client.parse(
  input_source,
  Mindee::Product::BusinessCard::BusinessCardV1
)

# Print a full summary of the parsed data in RST format
puts result.document

# Print the document-level parsed data
# puts result.document.inference.prediction
```

{% endtab %}

{% tab title="Java" %}

{% endtab %}

{% tab title="undefined" %}

```java
import com.mindee.MindeeClient;
import com.mindee.input.LocalInputSource;
import com.mindee.parsing.common.AsyncPredictResponse;
import com.mindee.product.businesscard.BusinessCardV1;
import java.io.File;
import java.io.IOException;

public class SimpleMindeeClient {

  public static void main(String[] args) throws IOException, InterruptedException {
    String apiKey = "my-api-key-here";
    String filePath = "/path/to/the/file.ext";

    // Init a new client
    MindeeClient mindeeClient = new MindeeClient(apiKey);

    // Load a file from disk
    LocalInputSource inputSource = new LocalInputSource(new File(filePath));

    // Parse the file asynchronously
    AsyncPredictResponse<BusinessCardV1> response = mindeeClient.enqueueAndParse(
        BusinessCardV1.class,
        inputSource
    );

    // Print a summary of the response
    System.out.println(response.toString());

    // Print a summary of the predictions
//  System.out.println(response.getDocumentObj().toString());

    // Print the document-level predictions
//    System.out.println(response.getDocumentObj().getInference().getPrediction().toString());

    // Print the page-level predictions
//    response.getDocumentObj().getInference().getPages().forEach(
//        page -> System.out.println(page.toString())
//    );
  }

}
```

{% endtab %}

{% tab title="Bash" %}

```bash
API_KEY='my-api-key-here'
ACCOUNT='mindee'
ENDPOINT='business_card'
VERSION='1'
FILE_PATH='/path/to/your/file.png'

# Maximum amount of retries to get the result of a queue
MAX_RETRIES=10

# Delay between requests
DELAY=6

# Enqueue the document for async parsing
QUEUE_RESULT=$(curl -sS --request POST \
  -H "Authorization: Token $API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F "document=@$FILE_PATH" \
  "https://api.mindee.net/v1/products/$ACCOUNT/$ENDPOINT/v$VERSION/predict_async")

# Status code sent back from the server
STATUS_CODE=$(echo "$QUEUE_RESULT" | grep -oP "[\"|']status_code[\"|']:[\s][\"|']*[a-zA-Z0-9-]*" | rev | cut --complement -f2- -d" " | rev)

# Check that the document was properly queued
if [ -z "$STATUS_CODE" ] || [ "$STATUS_CODE" -gt 399 ] || [ "$STATUS_CODE" -lt 200 ]
then
  if [ -z "$STATUS_CODE" ]
  then
    echo "Request couldn't be processed."
    exit 1
  fi
  echo "Error $STATUS_CODE was returned by API during enqueuing. "

  # Print the additional details, if there are any:
  ERROR=$(echo "$QUEUE_RESULT" | grep -oP "[\"|']error[\"|']:[\s]\{[^\}]*" | rev | cut --complement -f2- -d"{" | rev)
  if [ -z "$ERROR" ]
  then
    exit 1
  fi

  # Details on the potential error:
  ERROR_CODE=$(echo "$ERROR" | grep -oP "[\"|']code[\"|']:[\s]\"[^(\"|\')]*" | rev | cut --complement -f2- -d"\"" | rev)
  MESSAGE=$(echo "$QUEUE_RESULT" | grep -oP "[\"|']message[\"|']:[\s]\"[^(\"|\')]*" | rev | cut --complement -f2- -d"\"" | rev)
  DETAILS=$(echo "$QUEUE_RESULT" | grep -oP "[\"|']details[\"|']:[\s]\"[^(\"|\')]*" | rev | cut --complement -f2- -d"\"" | rev)
  echo "This was the given explanation:"
  echo "-------------------------"
  echo "Error Code: $ERROR_CODE"
  echo "Message: $MESSAGE"
  echo "Details: $DETAILS"
  echo "-------------------------"
  exit 1
else

  echo "File sent, starting to retrieve from server..."

  # Get the document's queue ID
  QUEUE_ID=$(echo "$QUEUE_RESULT" | grep -oP "[\"|']id[\"|']:[\s][\"|'][a-zA-Z0-9-]*" | rev | cut --complement -f2- -d"\"" | rev)

  # Amount of attempts to retrieve the parsed document were made
  TIMES_TRIED=1

  # Try to fetch the file until we get it, or until we hit the maximum amount of retries
  while [ "$TIMES_TRIED" -lt "$MAX_RETRIES" ]
  do
    # Wait for a bit at each step
    sleep $DELAY

    # Note: we use -L here because the location of the file might be behind a redirection
    PARSED_RESULT=$(curl -sS -L \
      -H "Authorization: Token $API_KEY" \
      "https://api.mindee.net/v1/products/$ACCOUNT/$ENDPOINT/v$VERSION/documents/queue/$QUEUE_ID")

    # Isolating the job (queue) & the status to monitor the document
    JOB=$(echo "$PARSED_RESULT" | grep -ioP "[\"|']job[\"|']:[\s]\{[^\}]*" | rev | cut --complement -f2- -d"{" | rev)
    QUEUE_STATUS=$(echo "$JOB" | grep -ioP "[\"|']status[\"|']:[\s][\"|'][a-zA-Z0-9-]*" | rev | cut --complement -f2- -d"\"" | rev)
    if [ "$QUEUE_STATUS" = "completed" ]
    then
      # Print the result
      echo "$PARSED_RESULT"

      # Optional: isolate the document:
      # DOCUMENT=$(echo "$PARSED_RESULT" | grep -ioP "[\"|']document[\"|']:[\s].*([\"|']job[\"|'])" | rev | cut -f2- -d"," | rev)
      # echo "{$DOCUMENT}"

      # Remark: on compatible shells, fields can also be extracted through the use of tools like jq:
      # DOCUMENT=$(echo "$PARSED_RESULT" | jq '.["document"]')
      exit 0
    fi
    TIMES_TRIED=$((TIMES_TRIED+1))
  done
fi

echo "Operation aborted, document not retrieved after $TIMES_TRIED tries"
exit 1
```

{% endtab %}
{% endtabs %}

* 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/the/file.ext` with the path to your input document.

{% hint style="warning" %}
Remember to replace with your V1 API key.
{% endhint %}

4. Run your code. You will receive a JSON response with your document details.

## API Response

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

```json
{
  "api_request": {
    "error": {},
    "resources": [
      "document",
      "job"
    ],
    "status": "success",
    "status_code": 200,
    "url": "https://api.mindee.net/v1/products/mindee/business_card/v1/documents/093ef5cb-74af-44b9-b50a-7ecf3254b3cd"
  },
  "document": {
    "id": "093ef5cb-74af-44b9-b50a-7ecf3254b3cd",
    "inference": {
      "extras": {},
      "finished_at": "2024-11-07T14:54:39.410000",
      "is_rotation_applied": true,
      "pages": [
        {
          "extras": {},
          "id": 0,
          "orientation": {
            "value": 0
          },
          "prediction": {}
        }
      ],
      "prediction": {
        "address": {
          "value": "178 Main Avenue, Providence, RI 02111"
        },
        "company": {
          "value": "RemoteGlobal"
        },
        "email": {
          "value": "amorin@remoteglobalconsulting.com"
        },
        "fax_number": {
          "value": null
        },
        "firstname": {
          "value": "Andrew"
        },
        "job_title": {
          "value": "Founder & CEO"
        },
        "lastname": {
          "value": "Morin"
        },
        "mobile_number": {
          "value": null
        },
        "phone_number": {
          "value": "+14015555555"
        },
        "social_media": [],
        "website": {
          "value": "www.remoteglobalconsulting.com"
        }
      },
      "processing_time": 2.74,
      "product": {
        "features": [
          "firstname",
          "lastname",
          "job_title",
          "company",
          "email",
          "phone_number",
          "mobile_number",
          "fax_number",
          "address",
          "website",
          "social_media"
        ],
        "name": "mindee/business_card",
        "type": "standard",
        "version": "1.0"
      },
      "started_at": "2024-11-07T14:54:36.465000"
    },
    "n_pages": 1,
    "name": "October-Blog-BC.png"
  },
  "job": {
    "available_at": "2024-11-07T14:54:39.421000",
    "error": {},
    "id": "a78b4492-3da0-4e4f-ad99-f5f7600fa317",
    "issued_at": "2024-11-07T14:54:36.465000",
    "status": "completed"
  }
}
```

You can find the prediction within the `prediction` key found 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 object using all the pages.

## Detailed Field Information

Using the above document example the following are the basic fields that can be extracted.

* [Firstname](#firstname)
* [Lastname](#lastname)
* [Job Title](#job-title)
* [Company](#company)
* [Email](#email)
* [Phone Number](#phone-number)
* [Mobile Number](#mobile-number)
* [Fax Number](#fax-number)
* [Address](#address)
* [Website](#website)
* [Social Media](#social-media)

### Firstname

* **firstname**: The given name of the person.

```json
{
  "firstname": {
    "value": "Andrew"
  }
}

```

### Lastname

* **lastname**: The lastname of the person.

```json
{
  "lastname": {
    "value": "Morin"
  }
}

```

### Job Title

* **job\_title**: The job title of the person.

```json
{
  "job_title": {
    "value": "Founder & CEO"
  }
}

```

### Company

* company: The company the person works for.

```json
{
  "company": {
    "value": "RemoteGlobal"
  }
}

```

### Email

* **email**: The email address of the person.

```json
{
  "email": {
    "value": "amorin@remoteglobalconsulting.com"
  }
}

```

### Phone Number

* **phone\_number**: The phone number of the person.

```json
{
  "phone_number": {
    "value": "+14015555555"
  }
}
```

### Mobile Number

* **mobile\_number**: The mobile number of the person.

```json
{
  "mobile_number": {
    "value": null
  }
}
```

### Fax Number

* **firstname**: The Fax number of the person.

```json
{
  "fax_number": {
    "value": null
  }
}
```

### Address

* **address**: The address of the person.

```json
{
  "address": {
    "value": "178 Main Avenue, Providence, RI 02111"
  }
}
```

### Website

* **website**: The website of the person or company.

```json
{
  "website": {
    "value": "www.remoteglobalconsulting.com"
  }
}
```

### Social Media

* **social\_media**: The social media profiles of the person or company.

```json
{
  "social_media": []
}
```