ImageToTextTask

View full price

Text Captcha

$0.3 / 1000 tokens

99%

This is a regular captcha, which is an image with text to be entered into the corresponding line.

Request parameters

type<string>required

ImageToTextTask

---

body<string>required

File body encoded in base64*. Make sure to send it without line breaks.

---

capMonsterModule<string>optional

The name of recognizing module, for example, “yandex“. Alternative way to pass module name and list of all available modules you can find here.
Example: yandex, special and others

---

recognizingThreshold<integer>optional

Captcha recognition threshold with a possible value from 0 to 100. For example, if recognizingThreshold was set to 90 and the task was solved with a confidence of 80, you won't be charged. In this case the user will get a response ERROR_CAPTCHA_UNSOLVABLE.

---

case<boolean>optional

true - if captcha is case sensitive.

---

numeric<integer>optional

1 - if captcha contains numbers only.
Possible values: 0, 1

---

math<boolean>optional

false — undefined;
true — if captcha requires a mathematical operation (for example: captcha 2 + 6 = will return a value of 8).

*Base64 is a data encoding method that allows you to represent binary data as text. Here is an example of obtaining a captcha image in base64 format using the console in the Developer Tools:

const captchaUrl = 'https://example.com/captcha.jpg';

function loadAndEncodeCaptchaToBase64(url) {
    fetch(url)
        .then(response => response.blob())
        .then(blob => {
            const reader = new FileReader();
            reader.readAsDataURL(blob);

            reader.onloadend = function() {
                const base64Data = reader.result;                
                console.log('Base64 Encoded Captcha:', base64Data);

                          };
        })
        .catch(error => {
            console.error('Error occurred while loading or encoding the captcha:', error);
        });
}

loadAndEncodeCaptchaToBase64(captchaUrl);

Create task method

POST

https://api.capmonster.cloud/createTask

Request

{
  "clientKey":"API_KEY",
  "task": {
	"type":"ImageToTextTask",
	"body":"BASE64_BODY_HERE!"
  }
}

Response

{
  "errorId":0,
  "taskId":407533072
}

Get task result method

Use the getTaskResult method to get the captcha solution. Depending on the system load, you will receive an answer within an interval from 300 ms to 6 s

POST

https://api.capmonster.cloud/getTaskResult

Request

{
  "clientKey":"API_KEY",
  "taskId": 407533072
}

Response

{
  "errorId":0,
  "status":"ready",
  "solution": {
	"text":"answer"
  }
}

Property	Type	Description
text	String	Captcha answer

Use SDK Library

JavaScript

// https://github.com/ZennoLab/capmonstercloud-client-js

import { CapMonsterCloudClientFactory, ClientOptions, ImageToTextRequest } from '@zennolab_com/capmonstercloud-client';

document.addEventListener('DOMContentLoaded', async () => {
  const cmcClient = CapMonsterCloudClientFactory.Create(new ClientOptions({ clientKey: '<your capmonster.cloud API key>' }));
  console.log(await cmcClient.getBalance());

  const imageToTextRequest = new ImageToTextRequest({
    body: 'some base64 body',
    CapMonsterModule: CapMonsterModules.YandexWave,
    Case: true,
    numeric: 1,
    recognizingThreshold: 65,
    math: false,
  });

  console.log(await cmcClient.Solve(imageToTextRequest));
});

Python

# https://github.com/ZennoLab/capmonstercloud-client-python

import asyncio
import base64
from capmonstercloudclient import CapMonsterClient, ClientOptions
from capmonstercloudclient.requests import ImageToTextRequest

client_options = ClientOptions(api_key="your_api_key")  # Replace with your CapMonsterCloud API key
cap_monster_client = CapMonsterClient(options=client_options)

image_base64 = "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAgGBgc…wwzqR4U/yZ//Z"

image_bytes = base64.b64decode(image_base64)

image_to_text_request = ImageToTextRequest(
    image_bytes=image_bytes,
    module_name=None,  # Optional, can specify a module name if needed
    threshold=50,      # Optional, set a threshold value between 1 and 100
    case=True,         # Optional, specify whether case sensitivity is required
    numeric=0,         # Optional, set numeric flag (0 or 1)
    math=False         # Optional, specify whether math operations are involved
)

async def solve_captcha():
    return await cap_monster_client.solve_captcha(image_to_text_request)

responses = asyncio.run(solve_captcha())
print(responses)

C#

// https://github.com/ZennoLab/capmonstercloud-client-dotnet

using Zennolab.CapMonsterCloud.Requests;
using Zennolab.CapMonsterCloud;

class Program
{
    static async Task Main(string[] args)
    {
        var clientOptions = new ClientOptions
        {
            ClientKey = "your_api_key" // Replace with your CapMonster Cloud API key
        };

        var cmCloudClient = CapMonsterCloudClientFactory.Create(clientOptions);

        var imageToTextRequest = new ImageToTextRequest
        {
            Body = "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0aHBwgJC4nICIsIxwcKDcpLDAxNDQ0Hyc5PTgyPC4zNDL/2wBDAQkJCQwLDBgNDRgyIRwhMjIyMjIyMjIyMjIyMj", // Base64 encoded image
            CapMonsterModule = "None",  // Optional, can specify a module name if needed
            RecognizingThreshold = 70, // Optional, set a threshold value between 1 and 100
            CaseSensitive = true, // Optional, specify whether case sensitivity is required
            Numeric = false, 
            Math = false
        };

        var imageToTextResult = await cmCloudClient.SolveAsync(imageToTextRequest);

        Console.WriteLine("Captcha Solved: " + imageToTextResult.Solution.Value);
    }
}