Classification Quick Start

Integrate a Classification Model.

Install the Client Library

Install the Mindee SDK for your language or framework of choice

Requires Python ≥ 3.9. Python ≥ 3.11 is recommended.

Simply install the PyPi package using pip:

pip install -U mindee~=4.36

Don't see support for your favorite language or framework? Make a feature request!

Send a File and Poll

Use the client library to send the file to your Classification Model and return the result.

Requires Python ≥ 3.9. Python ≥ 3.11 is recommended. Requires the Mindee Python SDK version 4.35.1 or greater.

from mindee import (
    ClientV2,
    PathInput,
    ClassificationParameters,
    ClassificationResponse,
)

input_path = "/path/to/the/file.ext"
api_key = "MY_API_KEY"
model_id = "MY_MODEL_ID"

# Init a new client
mindee_client = ClientV2(api_key)

# Set parameters
model_params = ClassificationParameters(
    # ID of the model, required.
    model_id=model_id,
)

# Load a file from disk
input_source = PathInput(input_path)

# Send for processing using polling
response = mindee_client.enqueue_and_get_result(
    ClassificationResponse,
    input_source,
    model_params,
)

# Print a brief summary of the parsed data
print(response.inference)

# Access the classification result
classification: str = response.inference.result.classification.document_type

Also take a look at the Classification Result documentation.

Requires Node.js ≥ 20.1. Node.js ≥ 22 is recommended. Requires the Mindee Node.js SDK version 5.3.0 or greater.

import * as mindee from "mindee";
// If you're on CommonJS:
// const mindee = require("mindee");

const apiKey = "MY_API_KEY";
const filePath = "/path/to/the/file.ext";
const modelId = "MY_MODEL_ID";

// Init a new client
const mindeeClient = new mindee.Client(
  { apiKey: apiKey }
);

// Set product parameters
const modelParams = {
  modelId: modelId,
};

// Load a file from disk
const inputSource = new mindee.PathInput({ inputPath: filePath });

// Send for processing
const response = await mindeeClient.enqueueAndGetResult(
  mindee.product.Classification,
  inputSource,
  modelParams,
);

// print a string summary
console.log(response.inference.toString());

// Access the classification result
const classification = response.inference.result.classification;

Also take a look at the Classification Result documentation.

Requires PHP ≥ 8.1. PHP ≥ 8.3 is recommended. Requires the Mindee PHP SDK version 2.7.1 or greater.

<?php

use Mindee\ClientV2;
use Mindee\V2\Product\Classification\Params\ClassificationParameters;
use Mindee\V2\Product\Classification\ClassificationResponse;
use Mindee\Input\PathInput;

$apiKey = "MY_API_KEY";
$filePath = "/path/to/the/file.ext";
$modelId = "MY_MODEL_ID";

// Init a new client
$mindeeClient = new ClientV2($apiKey);

// Set classification parameters
$modelParams = new ClassificationParameters(
    // ID of the model, required.
    $modelId
);

// Load a file from disk
$inputSource = new PathInput($filePath);

// Send for processing using polling
$response = $mindeeClient->enqueueAndGetResult(
    ClassificationResponse::class,
    $inputSource,
    $modelParams
);

// Print a summary of the response
echo strval($response->inference);

// Access the classification results
$classification = $response->inference->result->classification;

Also take a look at the Classification Result documentation.

Requires Ruby ≥ 3.2. Requires the Mindee Ruby SDK version 5.2.1 or greater.

require 'mindee'
require 'mindee/v2/product'

input_path = '/path/to/the/file.ext'
api_key = 'MY_API_KEY'
model_id = 'MY_MODEL_ID'

# Init a new client
mindee_client = Mindee::V2::Client.new(api_key: api_key)

# Set inference parameters
model_params = {
    # ID of the model, required.
    model_id: model_id,
}

# Load a file from disk
input_source = Mindee::Input::Source::PathInputSource.new(input_path)

# Send for processing
response = mindee_client.enqueue_and_get_result(
    Mindee::V2::Product::Classification::Classification,
    input_source,
    model_params
)

# Access the classification result
puts response.inference.result.classification

Also take a look at the Classification Result documentation.

Requires Java ≥ 11. Java ≥ 17 is recommended. Requires the Mindee Java SDK version 5.1.0 or greater.

import com.mindee.input.LocalInputSource;
import com.mindee.v2.MindeeClient;
import com.mindee.v2.product.classification.ClassificationResponse;
import com.mindee.v2.product.classification.params.ClassificationParameters;
import java.io.IOException;

public class SimpleMindeeClientV2 {

  public static void main(String[] args)
      throws IOException, InterruptedException
  {
    String apiKey = "MY_API_KEY";
    String modelId = "MY_MODEL_ID";
    String filePath = "/path/to/the/file.ext";

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

    // Set inference parameters
    // Note: modelId is mandatory.
    var modelParams = ClassificationParameters
        // ID of the model, required.
        .builder(modelId)
        .build();

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

    // Send for processing using polling
    ClassificationResponse response = mindeeClient.enqueueAndGetResult(
        ClassificationResponse.class,
        inputSource,
        modelParams
    );

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

    // Access the classification result
    var result = response.getInference().getResult();
    String documentType = result.getClassification().getDocumentType();
  }
}

Also take a look at the Classification Result documentation.

.NET ≥ 8.0 is recommended. Requires the Mindee .NET SDK version 4.3.0 or greater.

using Mindee;
using Mindee.Input;
using Mindee.V2;
using Mindee.V2.Product.Classification;
using Mindee.V2.Product.Classification.Params;

string filePath = "/path/to/the/file.ext";
string apiKey = "MY_API_KEY";
string modelId = "MY_MODEL_ID";

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

// Set inference parameters
var modelParams = new ClassificationParameters(
    modelId: modelId
);

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

// Upload the file
var response = await mindeeClient.EnqueueAndGetResultAsync<ClassificationResponse>(
    inputSource, modelParams);

// Print a summary of the response
System.Console.WriteLine(response.Inference.ToString());

// Access the classification results
var classification = response.Inference.Result.Classification;

Also take a look at the Classification Result documentation.

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Last updated 8 days ago

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