--- description: Unofficial Capacitor plugin for the Google ML Kit Text Recognition SDK to extract and recognize text from images on Android and iOS. title: Capacitor ML Kit Text Recognition Plugin - Capawesome image: https://capawesome.io/docs/assets/images/social/sdks/capacitor/mlkit/text-recognition.png --- [Skip to content ](#capacitor-ml-kit-text-recognition-plugin) [πŸ” Introducing the **Capacitor Vault** plugin β€” store secrets behind biometrics or a device passcode. ](/blog/announcing-the-capacitor-vault-plugin/) * [ SDKs ](/docs/sdks/) * [ Formbricks ](/docs/sdks/capacitor/formbricks/) * [ Geocoder ](/docs/sdks/capacitor/geocoder/) * [ Google Sign-In ](/docs/sdks/capacitor/google-sign-in/) * [ Grafana Faro ](/docs/sdks/capacitor/grafana-faro/) * [ Gyroscope ](/docs/sdks/capacitor/gyroscope/) * [ Haptics ](/docs/sdks/capacitor/haptics/) * [ Home Indicator ](/docs/sdks/capacitor/home-indicator/) * [ In-App Browser ](/docs/sdks/capacitor/in-app-browser/) * [ Install Referrer 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* [ Insiders ](/docs/insiders/) * [ Billing & Plans ](/docs/insiders/billing-and-plans/) * [ FAQ ](/docs/insiders/faq/) * [ License ](https://capawesome.io/legal/eula/) * [ Support ](/docs/support/) * [ Contributing ](/docs/contributing/) * Contributing code * [ Code of Conduct ](/docs/contributing/code-of-conduct/) * [ Questions ](https://docs.github.com/en/discussions/collaborating-with-your-community-using-discussions/participating-in-a-discussion#creating-a-discussion) * [ Blog ](/blog/) * Categories * [ iOS ](#ios) * [ Configuration ](#configuration) * [ Demo ](#demo) * [ Usage ](#usage) * [ API ](#api) * [ Enums ](#enums) * [ FAQ ](#faq) * [ Related Plugins ](#related-plugins) * [ Terms & Privacy ](#terms-privacy) * [ Newsletter ](#newsletter) * [ Changelog ](#changelog) * [ License ](#license) # Capacitor ML Kit Text Recognition Plugin[ΒΆ](#capacitor-ml-kit-text-recognition-plugin "Permanent link") Unofficial Capacitor plugin for [ML Kit Text Recognition](https://developers.google.com/ml-kit/vision/text-recognition/v2).[1](#fn:1) [ ![Deliver Live Updates to your Capacitor app with Capawesome Cloud](../../../../assets/external/cloud.capawesome.io/assets/banners/cloud-build-and-deploy-capacitor-apps.69628c3f.png) ](https://cloud.capawesome.io/) ## Use Cases[ΒΆ](#use-cases "Permanent link") 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[ΒΆ](#compatibility "Permanent link") | Plugin Version | Capacitor Version | Status | | -------------- | ----------------- | -------------- | | 8.x.x | \>=8.x.x | Active support | ## Installation[ΒΆ](#installation "Permanent link") You can use our **AI-Assisted Setup** to install the plugin. Add the [Capawesome Skills](https://github.com/capawesome-team/skills) to your AI tool using the following command: `[](#%5F%5Fcodelineno-0-1)npx skills add capawesome-team/skills --skill capacitor-plugins ` Then use the following prompt: `` [](#%5F%5Fcodelineno-1-1)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: `[](#%5F%5Fcodelineno-2-1)npm install @capacitor-mlkit/text-recognition [](#%5F%5Fcodelineno-2-2)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](https://github.com/googlesamples/mlkit/issues/180#issuecomment-1298964099). ### App Size Impact[ΒΆ](#app-size-impact "Permanent link") 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[ΒΆ](#android "Permanent link") #### Variables[ΒΆ](#variables "Permanent link") 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[ΒΆ](#ios "Permanent link") #### Minimum Deployment Target[ΒΆ](#minimum-deployment-target "Permanent link") Make sure to set the deployment target in your `ios/App/Podfile` to at least `15.5`: `[](#%5F%5Fcodelineno-3-1)platform :ios, '15.5' ` ## Configuration[ΒΆ](#configuration "Permanent link") No configuration required for this plugin. ## Demo[ΒΆ](#demo "Permanent link") A working example can be found here: [robingenz/capacitor-mlkit-plugin-demo](https://github.com/robingenz/capacitor-mlkit-plugin-demo) ## Usage[ΒΆ](#usage "Permanent link") The following example shows how to recognize text in an image. ### Recognize text in an image[ΒΆ](#recognize-text-in-an-image "Permanent link") 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: `[](#%5F%5Fcodelineno-4-1)import { Script, TextRecognition } from '@capacitor-mlkit/text-recognition'; [](#%5F%5Fcodelineno-4-2) [](#%5F%5Fcodelineno-4-3)const processImage = async () => { [](#%5F%5Fcodelineno-4-4) const { text, blocks } = await TextRecognition.processImage({ [](#%5F%5Fcodelineno-4-5) path: 'path/to/image.jpg', [](#%5F%5Fcodelineno-4-6) script: Script.Latin, [](#%5F%5Fcodelineno-4-7) }); [](#%5F%5Fcodelineno-4-8) return { text, blocks }; [](#%5F%5Fcodelineno-4-9)}; ` ## API[ΒΆ](#api "Permanent link") * [processImage(...)](#processimage) * [Interfaces](#interfaces) * [Enums](#enums) ### processImage(...)[ΒΆ](#processimage "Permanent link") `[](#%5F%5Fcodelineno-5-1)processImage(options: ProcessImageOptions) => Promise ` Recognizes text in the supplied image. Only available on Android and iOS. | Param | Type | | ----------- | ------------------------------------------- | | **options** | [ProcessImageOptions](#processimageoptions) | **Returns:** `Promise<[ProcessImageResult](#processimageresult)>` **Since:** 8.2.0 --- ### Interfaces[ΒΆ](#interfaces "Permanent link") #### ProcessImageResult[ΒΆ](#processimageresult "Permanent link") | Prop | Type | Description | Since | | ---------- | ------------- | ------------------------------ | ----- | | **text** | string | The full recognized text. | 8.2.0 | | **blocks** | TextBlock\[\] | The recognized blocks of text. | 8.2.0 | #### TextBlock[ΒΆ](#textblock "Permanent link") 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](#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[ΒΆ](#rect "Permanent link") 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[ΒΆ](#point "Permanent link") 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[ΒΆ](#textline "Permanent link") Represents a line of text. | Prop | Type | Description | Since | | ---------------------- | --------------- | -------------------------------------------------------------------------------------------------------------- | ----- | | **text** | string | The recognized text of the line. | 8.2.0 | | **boundingBox** | [Rect](#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[ΒΆ](#textelement "Permanent link") 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](#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[ΒΆ](#processimageoptions "Permanent link") | Prop | Type | Description | Default | Since | | ---------- | ----------------- | -------------------------------------------------------------------------------------------------------- | ------------ | ----- | | **path** | string | The local path to the image file. | | 8.2.0 | | **script** | [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[ΒΆ](#enums "Permanent link") #### Script[ΒΆ](#script "Permanent link") | 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[ΒΆ](#faq "Permanent link") ### Which platforms are supported by this plugin?[ΒΆ](#which-platforms-are-supported-by-this-plugin "Permanent link") 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?[ΒΆ](#which-scripts-are-supported "Permanent link") 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?[ΒΆ](#does-bundling-all-scripts-increase-the-app-size "Permanent link") 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?[ΒΆ](#in-which-format-do-i-have-to-provide-the-image-path "Permanent link") 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?[ΒΆ](#can-i-use-this-plugin-with-ionic-react-vue-or-angular "Permanent link") 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[ΒΆ](#related-plugins "Permanent link") * [ML Kit Barcode Scanning](https://capawesome.io/docs/sdks/capacitor/mlkit/barcode-scanning/): Scan barcodes with ML Kit Barcode Scanning. * [ML Kit Image Labeling](https://capawesome.io/docs/sdks/capacitor/mlkit/image-labeling/): Detect labels in images with ML Kit Image Labeling. * [ML Kit Face Detection](https://capawesome.io/docs/sdks/capacitor/mlkit/face-detection/): Detect faces in images with ML Kit Face Detection. ## Terms & Privacy[ΒΆ](#terms-privacy "Permanent link") This plugin uses the [Google ML Kit](https://developers.google.com/ml-kit): * [Terms & Privacy](https://developers.google.com/ml-kit/terms) * [Android Data Disclosure](https://developers.google.com/ml-kit/android-data-disclosure) * [iOS Data Disclosure](https://developers.google.com/ml-kit/ios-data-disclosure) ## Newsletter[ΒΆ](#newsletter "Permanent link") Stay up to date with the latest news and updates about the Capawesome, Capacitor, and Ionic ecosystem by subscribing to our [Capawesome Newsletter](https://cloud.capawesome.io/newsletter/). ## Changelog[ΒΆ](#changelog "Permanent link") See [CHANGELOG.md](https://github.com/capawesome-team/capacitor-mlkit/blob/main/packages/text-recognition/CHANGELOG.md). ## License[ΒΆ](#license "Permanent link") See [LICENSE](https://github.com/capawesome-team/capacitor-mlkit/blob/main/packages/text-recognition/LICENSE). --- 1. This project is not affiliated with, endorsed by, sponsored by, or approved by Google LLC or any of their affiliates or subsidiaries. [↩](#fnref:1 "Jump back to footnote 1 in the text") July 10, 2026 Back to top ```json {"@context": "https://schema.org", "@graph": [{"@type": "TechArticle", "@id": "https://capawesome.io/docs/sdks/capacitor/mlkit/text-recognition/#article", "headline": "Capacitor ML Kit Text Recognition Plugin", "name": "Capacitor ML Kit Text Recognition Plugin", "description": "Unofficial Capacitor plugin for the Google ML Kit Text Recognition SDK to extract and recognize text from images on Android and iOS.", "inLanguage": "en", "url": "https://capawesome.io/docs/sdks/capacitor/mlkit/text-recognition/", "mainEntityOfPage": "https://capawesome.io/docs/sdks/capacitor/mlkit/text-recognition/", "author": {"@type": "Organization", "name": "Capawesome", "url": "https://capawesome.io", "logo": {"@type": "ImageObject", "url": "https://capawesome.io/assets/images/logo.svg"}}, "publisher": {"@type": "Organization", "name": "Capawesome", "url": "https://capawesome.io", "logo": {"@type": "ImageObject", "url": "https://capawesome.io/assets/images/logo.svg"}}, "about": {"@id": "https://capawesome.io/docs/sdks/capacitor/mlkit/text-recognition/#software"}}, {"@type": "SoftwareSourceCode", "@id": "https://capawesome.io/docs/sdks/capacitor/mlkit/text-recognition/#software", "name": "Capacitor ML Kit Text Recognition Plugin", "description": "Unofficial Capacitor plugin for the Google ML Kit Text Recognition SDK to extract and recognize text from images on Android and iOS.", "url": "https://capawesome.io/docs/sdks/capacitor/mlkit/text-recognition/", "programmingLanguage": "TypeScript", "runtimePlatform": "Capacitor", "codeRepository": "https://github.com/capawesome-team", "author": {"@type": "Organization", "name": "Capawesome", "url": "https://capawesome.io", "logo": {"@type": "ImageObject", "url": "https://capawesome.io/assets/images/logo.svg"}}, "publisher": {"@type": "Organization", "name": "Capawesome", "url": "https://capawesome.io", "logo": {"@type": "ImageObject", "url": "https://capawesome.io/assets/images/logo.svg"}}}]} {"@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{"@type": "Question", "name": "Which platforms are supported by this plugin?", "acceptedAnswer": {"@type": "Answer", "text": "The processImage(...) method is only available on Android and iOS. The Web platform is not supported by the underlying ML Kit Text Recognition SDK."}}, {"@type": "Question", "name": "Which scripts are supported?", "acceptedAnswer": {"@type": "Answer", "text": "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."}}, {"@type": "Question", "name": "Does bundling all scripts increase the app size?", "acceptedAnswer": {"@type": "Answer", "text": "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."}}, {"@type": "Question", "name": "In which format do I have to provide the image path?", "acceptedAnswer": {"@type": "Answer", "text": "The path must be a local file path (e.g. file:///path/to/image.jpg). Remote URLs are not supported."}}, {"@type": "Question", "name": "Can I use this plugin with Ionic, React, Vue or Angular?", "acceptedAnswer": {"@type": "Answer", "text": "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."}}], "url": "https://capawesome.io/docs/sdks/capacitor/mlkit/text-recognition/"} ```