Business Cards OCR

from mindee import Client, AsyncPredictResponse, product

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

# Add the corresponding endpoint (document). Set the account_name to "mindee" if you are using OTS.
my_endpoint = mindee_client.create_endpoint(
    account_name="mindee",
    endpoint_name="business_card",
    version="1"
)

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

# Parse the file.
# The endpoint must be specified since it cannot be determined from the class.
result: AsyncPredictResponse = mindee_client.enqueue_and_parse(
    product.GeneratedV1,
    input_doc,
    endpoint=my_endpoint
)

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

# # Iterate over all the fields in the document
# for field_name, field_values in result.document.inference.prediction.fields.items():
#     print(field_name, "=", field_values)

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

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

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

// Create a custom endpoint for your product
const customEndpoint = mindeeClient.createEndpoint(
  "business_card",
  "mindee",
  "1" // Defaults to "1"
);

// Parse the file asynchronously.
const asyncApiResponse = mindeeClient.enqueueAndParse(
  mindee.product.GeneratedV1,
  inputSource,
  { endpoint: customEndpoint }
);

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

using Mindee;
using Mindee.Input;
using Mindee.Http;
using Mindee.Product.Generated;

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);

// Set the endpoint configuration
CustomEndpoint endpoint = new CustomEndpoint(
    endpointName: "business_card",
    accountName: "mindee",
    version: "1"
);

// Call the product asynchronously with auto-polling
var response = await mindeeClient
    .EnqueueAndParseAsync<GeneratedV1>(inputSource, endpoint);

// 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());

require 'mindee'

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

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

# Initialize a custom endpoint for this product
custom_endpoint = mindee_client.create_endpoint(
  account_name: 'mindee',
  endpoint_name: 'business_card',
  version: '1'
)

# Parse the file
result = mindee_client.enqueue_and_parse(
  input_source,
  Mindee::Product::Generated::GeneratedV1,
  endpoint: custom_endpoint
)

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

import com.mindee.MindeeClient;
import com.mindee.input.LocalInputSource;
import com.mindee.parsing.common.AsyncPredictResponse;
import com.mindee.product.generated.GeneratedV1;
import com.mindee.http.Endpoint;
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));

    // Configure the endpoint
    Endpoint endpoint = new Endpoint(
        "business_card",
        "mindee",
        "1"
    );

    // Parse the file asynchronously
    AsyncPredictResponse<GeneratedV1> response = mindeeClient.enqueueAndParse(
        GeneratedV1.class,
        endpoint,
        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())
//    );
  }

}

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

<?php

use Mindee\Client;
use Mindee\Product\Generated\GeneratedV1;
use Mindee\Input\PredictMethodOptions;

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

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

// Create a custom endpoint
$customEndpoint = $mindeeClient->createEndpoint(
    "business_card",
    "mindee",
    "1"
);

// Add the custom endpoint to the prediction options.
$predictOptions = new PredictMethodOptions();
$predictOptions->setEndpoint($customEndpoint);

// Parse the file
$apiResponse = $mindeeClient->enqueueAndParse(GeneratedV1::class, $inputSource, $predictOptions);

echo strval($apiResponse->document);

{
  "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": "[email protected]"
        },
        "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"
  }
}

{
  "firstname": {
    "value": "Andrew"
  }
}

{
  "lastname": {
    "value": "Morin"
  }
}

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

{
  "company": {
    "value": "RemoteGlobal"
  }
}

{
  "email": {
    "value": "[email protected]"
  }
}

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

{
  "mobile_number": {
    "value": null
  }
}

{
  "fax_number": {
    "value": null
  }
}

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

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

{
  "social_media": []
}