npm package discovery and stats viewer.

Discover Tips

  • General search

    [free text search, go nuts!]

  • Package details

    pkg:[package-name]

  • User packages

    @[username]

Sponsor

Optimize Toolset

I’ve always been into building performant and accessible sites, but lately I’ve been taking it extremely seriously. So much so that I’ve been building a tool to help me optimize and monitor the sites that I build to make sure that I’m making an attempt to offer the best experience to those who visit them. If you’re into performant, accessible and SEO friendly sites, you might like it too! You can check it out at Optimize Toolset.

About

Hi, 👋, I’m Ryan Hefner  and I built this site for me, and you! The goal of this site was to provide an easy way for me to check the stats on my npm packages, both for prioritizing issues and updates, and to give me a little kick in the pants to keep up on stuff.

As I was building it, I realized that I was actually using the tool to build the tool, and figured I might as well put this out there and hopefully others will find it to be a fast and useful way to search and browse npm packages as I have.

If you’re interested in other things I’m working on, follow me on Twitter or check out the open source projects I’ve been publishing on GitHub.

I am also working on a Twitter bot for this site to tweet the most popular, newest, random packages from npm. Please follow that account now and it will start sending out packages soon–ish.

Open Software & Tools

This site wouldn’t be possible without the immense generosity and tireless efforts from the people who make contributions to the world and share their work via open source initiatives. Thank you 🙏

© 2026 – Pkg Stats / Ryan Hefner

@capacitor-mlkit/text-recognition

v8.2.0

Published

Capacitor plugin for ML Kit Text Recognition on Android and iOS.

Readme

Capacitor ML Kit Text Recognition Plugin

Unofficial Capacitor plugin for ML Kit Text Recognition.[^1]

Use Cases

The Text Recognition plugin is typically used whenever an app needs to extract text from an image, for example:

  • Document digitization: Convert printed documents, receipts, or business cards into machine-readable text.
  • Data entry automation: Extract text from forms or labels to prefill input fields and reduce manual typing.
  • Accessibility: Read text found in images aloud to support screen readers and other assistive technologies.
  • Translation pipelines: Recognize text in an image before passing it on to a translation service.

Compatibility

| Plugin Version | Capacitor Version | Status | | -------------- | ----------------- | -------------- | | 8.x.x | >=8.x.x | Active support |

Installation

You can use our AI-Assisted Setup to install the plugin. Add the Capawesome Skills to your AI tool using the following command:

npx skills add capawesome-team/skills --skill capacitor-plugins

Then use the following prompt:

Use the `capacitor-plugins` skill from `capawesome-team/skills` to install the `@capacitor-mlkit/text-recognition` plugin in my project.

If you prefer Manual Setup, install the plugin by running the following commands and follow the platform-specific instructions below:

npm install @capacitor-mlkit/text-recognition
npx cap sync

Attention: This plugin only supports CocoaPods for iOS dependency management. Swift Package Manager (SPM) is not supported for the ML Kit SDK, see this comment.

App Size Impact

This plugin bundles a separate model for each supported script (Latin, Chinese, Devanagari, Japanese, and Korean). Each model increases the size of your app by several megabytes. Keep this in mind when deciding which scripts your app actually needs.

Android

Variables

If needed, you can define the following project variables in your app’s variables.gradle file to change the default version of the dependencies:

  • $mlkitTextRecognitionVersion version of com.google.mlkit:text-recognition (default: 16.0.1)
  • $mlkitTextRecognitionChineseVersion version of com.google.mlkit:text-recognition-chinese (default: 16.0.1)
  • $mlkitTextRecognitionDevanagariVersion version of com.google.mlkit:text-recognition-devanagari (default: 16.0.1)
  • $mlkitTextRecognitionJapaneseVersion version of com.google.mlkit:text-recognition-japanese (default: 16.0.1)
  • $mlkitTextRecognitionKoreanVersion version of com.google.mlkit:text-recognition-korean (default: 16.0.1)

This can be useful if you encounter dependency conflicts with other plugins in your project.

iOS

Minimum Deployment Target

Make sure to set the deployment target in your ios/App/Podfile to at least 15.5:

platform :ios, '15.5'

Configuration

No configuration required for this plugin.

Demo

A working example can be found here: robingenz/capacitor-mlkit-plugin-demo

Usage

The following example shows how to recognize text in an image.

Recognize text in an image

Recognize text in an image at a local path. You can select the script of the text to recognize. Only available on Android and iOS:

import { Script, TextRecognition } from '@capacitor-mlkit/text-recognition';

const processImage = async () => {
  const { text, blocks } = await TextRecognition.processImage({
    path: 'path/to/image.jpg',
    script: Script.Latin,
  });
  return { text, blocks };
};

API

processImage(...)

processImage(options: ProcessImageOptions) => Promise<ProcessImageResult>

Recognizes text in the supplied image.

Only available on Android and iOS.

| Param | Type | | ------------- | ------------------------------------------------------------------- | | options | ProcessImageOptions |

Returns: Promise<ProcessImageResult>

Since: 8.2.0


Interfaces

ProcessImageResult

| Prop | Type | Description | Since | | ------------ | ------------------------ | ------------------------------ | ----- | | text | string | The full recognized text. | 8.2.0 | | blocks | TextBlock[] | The recognized blocks of text. | 8.2.0 |

TextBlock

Represents a block of text.

A block is a contiguous set of text lines, such as a paragraph or a column.

| Prop | Type | Description | Since | | ------------------------ | ------------------------------------- | --------------------------------------------------------------------------------------------------------------- | ----- | | text | string | The recognized text of the block. | 8.2.0 | | boundingBox | Rect | The bounding box of the block. | 8.2.0 | | cornerPoints | Point[] | The four corner points of the block in clockwise order, starting with the top-left point relative to the image. | 8.2.0 | | recognizedLanguage | string | The BCP-47 language code of the recognized language of the block. | 8.2.0 | | lines | TextLine[] | The recognized lines of text within the block. | 8.2.0 |

Rect

Represents a rectangle.

| Prop | Type | Description | Since | | ------------ | ------------------- | --------------------------------------- | ----- | | left | number | The left coordinate of the rectangle. | 8.2.0 | | top | number | The top coordinate of the rectangle. | 8.2.0 | | right | number | The right coordinate of the rectangle. | 8.2.0 | | bottom | number | The bottom coordinate of the rectangle. | 8.2.0 |

Point

Represents a point.

| Prop | Type | Description | Since | | ------- | ------------------- | ------------------------------ | ----- | | x | number | The x coordinate of the point. | 8.2.0 | | y | number | The y coordinate of the point. | 8.2.0 |

TextLine

Represents a line of text.

| Prop | Type | Description | Since | | ------------------------ | ------------------------------------- | -------------------------------------------------------------------------------------------------------------- | ----- | | text | string | The recognized text of the line. | 8.2.0 | | boundingBox | Rect | The bounding box of the line. | 8.2.0 | | cornerPoints | Point[] | The four corner points of the line in clockwise order, starting with the top-left point relative to the image. | 8.2.0 | | recognizedLanguage | string | The BCP-47 language code of the recognized language of the line. | 8.2.0 | | elements | TextElement[] | The recognized elements of text within the line. | 8.2.0 |

TextElement

Represents an element of text.

An element is a contiguous set of characters, such as a word.

| Prop | Type | Description | Since | | ------------------------ | ------------------------------------- | ----------------------------------------------------------------------------------------------------------------- | ----- | | text | string | The recognized text of the element. | 8.2.0 | | boundingBox | Rect | The bounding box of the element. | 8.2.0 | | cornerPoints | Point[] | The four corner points of the element in clockwise order, starting with the top-left point relative to the image. | 8.2.0 | | recognizedLanguage | string | The BCP-47 language code of the recognized language of the element. | 8.2.0 |

ProcessImageOptions

| Prop | Type | Description | Default | Since | | ------------ | ----------------------------------------- | -------------------------------------------------------------------------------------------------------- | ------------------------- | ----- | | path | string | The local path to the image file. | | 8.2.0 | | script | Script | The script of the text to recognize. Each script requires a separate model that is bundled with the app. | Script.Latin | 8.2.0 |

Enums

Script

| Members | Value | Description | Since | | ---------------- | ------------------------- | ---------------------- | ----- | | Latin | 'LATIN' | The Latin script. | 8.2.0 | | Chinese | 'CHINESE' | The Chinese script. | 8.2.0 | | Devanagari | 'DEVANAGARI' | The Devanagari script. | 8.2.0 | | Japanese | 'JAPANESE' | The Japanese script. | 8.2.0 | | Korean | 'KOREAN' | The Korean script. | 8.2.0 |

FAQ

Which platforms are supported by this plugin?

The processImage(...) method is only available on Android and iOS. The Web platform is not supported by the underlying ML Kit Text Recognition SDK.

Which scripts are supported?

The plugin supports the Latin, Chinese, Devanagari, Japanese, and Korean scripts. Use the script option to select the script of the text you want to recognize. Each script uses a separate model that is bundled with your app.

Does bundling all scripts increase the app size?

Yes. Each script model adds several megabytes to your app. All five models are bundled so that every script can be used at runtime without an additional download.

In which format do I have to provide the image path?

The path must be a local file path (e.g. file:///path/to/image.jpg). Remote URLs are not supported.

Can I use this plugin with Ionic, React, Vue or Angular?

Yes, the plugin is framework-agnostic. It works in any Capacitor app regardless of the web framework, including Ionic with Angular, React, or Vue, as well as plain JavaScript projects.

Related Plugins

Terms & Privacy

This plugin uses the Google ML Kit:

Newsletter

Stay up to date with the latest news and updates about the Capawesome, Capacitor, and Ionic ecosystem by subscribing to our Capawesome Newsletter.

Changelog

See CHANGELOG.md.

License

See LICENSE.

[^1]: This project is not affiliated with, endorsed by, sponsored by, or approved by Google LLC or any of their affiliates or subsidiaries.