@microblink/blinkid-in-browser-sdk
Advanced tools
A simple ID scanning library for WebAssembly-enabled browsers.
BlinkID In-browser SDK enables scanning of various identity documents, including driving licenses, national identity cards, passports and others. The SDK provides real-time in-browser data extraction, without any need for sending images to servers for processing.
For more information on how to integrate the BlinkID SDK into your web app read the instructions below. Make sure you read the latest changelog for most recent changes and improvements.
Check out the official demo app or live examples to see the BlinkID SDK in action:
Finally, check out the examples directory to see the source code of the aforementioned examples.
BlinkID In-browser SDK is meant to be used natively in a web browser. It will not work correctly within a iOS/Android WebView or NodeJS backend service. If you are looking for Cordova/PhoneGap version, please go here. If you want to use BlinkID as a backend service, please go here.
Recognizer concept, RecognizerRunner and VideoRecognizer
MetadataCallbacksThis repository contains WebAssembly file and support JS files which contains the core implementation of BlinkID functionalities.
In order to make integration of the WebAssembly easier and more developer friendly, a JavaScript/TypeScript support code is also provided, giving an easy to use integration API to the developer.
This repository also contains a sample JS/TS integration app which demonstrates how you can integrate the BlinkID into your web app.
BlinkID requires a browser with a support for WebAssembly, but works best with latest versions of Firefox, Chrome, Safari and Microsoft Edge. It's worth noting that scan performance depends on the device processing capabilities.
Using BlinkID in your web app requires a valid license key.
You can obtain a free trial license key by registering to Microblink dashboard. After registering, you will be able to generate a license key for your web app.
The license key is bound to fully qualified domain name of your web app, so please make sure you enter the correct name when asked. Also, keep in mind that if you plan to serve your web app from different domains, you will need different license keys.
It's recommended to install the stable version via NPM or Yarn:
# NPM
npm install @microblink/blinkid-in-browser-sdk
# Yarn
yarn add @microblink/blinkid-in-browser-sdk
Which then can be used with a module bundler in Node environment:
import * as BlinkIDSDK from "@microblink/blinkid-in-browser-sdk";
Source code of BlinkIDSDK is written in TypeScript and types are exposed in the public NPM package, so it's possible to use the SDK in both JavaScript and TypeScript projects.
Alternatively, it's possible to use UMD builds, which can be loaded from the dist folder on unpkg. The UMD builds make BlinkID available as a window.BlinkIDSDK global variable:
<script src="https://unpkg.com/@microblink/blinkid-in-browser-sdk/dist/blinkid-sdk.min.js"></script>
Finally, it's possible to use ES builds, which can be downloaded from the es folder on unpkg. ES modules are used in a similar manner as NPM package:
import * as BlinkIDSDK from "./es/blinkid-sdk.js";
After adding the BlinkID SDK to your project, make sure to include all files from its resources folder in your distribution. Those files contain compiled WebAssembly module, support JS code and WebWorker.
Do not add those files to the main app bundle, but rather place them on a publicly available location so SDK can load them at the appropriate time. For example, place the resources in my-angular-app/src/assets/ folder if using ng new, or place the resources in my-react-app/public/ folder if using create-react-app.
For more information on how to setup aforementioned resources, check out the Configuration of SDK section.
Note: following code snippets are written in TypeScript, but it's possible to use them in plain JavaScript.
Make sure to have a valid license key. Information on how to get a license key can be seen in the Obtaining a license key section.
Add SDK to your web app by using one of the options provided in the Installation section.
Initialize the SDK using the following code snippet:
import * as BlinkIDSDK from "@microblink/blinkid-in-browser-sdk";
// Check if browser is supported
if ( BlinkIDSDK.isBrowserSupported() )
{
const loadSettings = new BlinkIDSDK.WasmSDKLoadSettings( "your-base64-license-key" );
BlinkIDSDK.loadWasmModule( loadSettings ).then
(
( wasmSDK: BlinkIDSDK.WasmSDK ) =>
{
// The SDK was initialized successfully, save the wasmSDK for future use
},
( error: any ) =>
{
// Error happened during the initialization of the SDK
console.log( "Error during the initialization of the SDK!", error );
}
)
}
else
{
console.log( "This browser is not supported by the SDK!" );
}
Create recognizer objects that will perform image recognition, configure them and use them to create a RecognizerRunner object:
import * as BlinkIDSDK from "@microblink/blinkid-in-browser-sdk";
const recognizer = await BlinkIDSDK.createBlinkIdRecognizer( wasmSDK );
const recognizerRunner = await BlinkIDSDK.createRecognizerRunner( wasmSDK, [ recognizer ], true );
Obtain a reference to your HTML video element and create a VideoRecognizer using the element and your instance of RecognizerRunner which then can be used to process input video stream:
const cameraFeed = <HTMLVideoElement>document.getElementById( "myCameraVideoElement" );
try
{
const videoRecognizer = await BlinkIDSDK.VideoRecognizer.createVideoRecognizerFromCameraStream(
cameraFeed,
recognizerRunner
);
const processResult = await videoRecognizer.recognize();
// To obtain recognition results see next step
}
catch ( error )
{
if ( error.name === "VideoRecognizerError" )
{
// Reason is of type BlinkIDSDK.NotSupportedReason and contains information why video
// recognizer could not be used. Usually this happens when user didn't give permission
// to use the camera or when a hardware or OS error occurs.
const reason = ( error as BlinkIDSDK.VideoRecognizerError ).reason;
}
}
If processResult returned from VideoRecognizer's method recognize is not BlinkIDSDK.RecognizerResultState.Empty, then at least one recognizer given to the RecognizerRunner above contains a recognition result. You can extract the result from each recognizer using its getResult method:
if ( processResult !== BlinkIDSDK.RecognizerResultState.Empty )
{
const recognitionResult = await recognizer.getResult();
console.log( recognitionResult );
}
else
{
console.log( "Recognition was not successful!" );
}
Finally, release the memory on the WebAssembly heap by calling delete method on both RecognizerRunner and each of your recognizers. Also, release the camera stream by calling releaseVideoFeed on instance of VideoRecognizer:
videoRecognizer.releaseVideoFeed();
recognizerRunner.delete();
recognizer.delete();
Note that after releasing those objects it is not valid to call any methods on them, as they are literally destroyed. This is required to release memory resources on WebAssembly heap which are not automatically released with JavaScript's garbage collector. Also, note that results returned from getResult method are placed on JavaScript's heap and will be cleaned by garbage collector, just like any other normal JavaScript object.
For more information about available recognizers and RecognizerRunner, see RecognizerRunner and available recognizers.
If you just want to perform recognition of still images and do not need live camera recognition, you can do that as well.
Initialize recognizers and RecognizerRunner just as in the steps 1-4 above.
Make sure you have the image set to a HTMLImageElement. If you only have the URL of the image that needs recognizing, You can attach it to the image element with following code snippet:
const imageElement = <HTMLImageElement>document.getElementById( "imageToProcess" );
imageElement.src = URL.createObjectURL( imageURL );
await imageElement.decode();
Obtain the CapturedFrame object using function captureFrame and give it to the processImage method of the RecognizerRunner:
const imageFrame = BlinkIDSDK.captureFrame( imageElement );
const processResult = await recognizerRunner.processImage( imageFrame );
Proceed as in steps 6-7 above. Note that in there is no VideoRecognizer here that needs freeing its resources, but RecognizerRunner and recognizers must be deleted using the delete method.
It's possible to modify default behaviour of the SDK before WASM module is loaded.
Following code snippet shows how to configure the SDK and which non-development options are available:
// Create instance of WASM SDK load settings
const loadSettings = new BlinkIDSDK.WasmSDKLoadSettings( "your-base64-license-key" );
/**
* Write a hello message to the browser console when license check is successfully performed.
*
* Hello message will contain the name and version of the SDK, which are required information for all support
* tickets.
*
* Default value is true.
*/
loadSettings.allowHelloMessage = true;
/**
* Location of WASM and related JS/data files. Useful when resource files should be loaded over CDN, or when web
* frameworks/libraries are used which store resources in specific locations, e.g. inside "assets" folder.
*
* If relative path is defined, the path will be resolved relative to the location of worker file.
*
* Important: if engine is hosted on another origin, CORS must be enabled between two hosts. That is, server where
* engine is hosted must have 'Access-Control-Allow-Origin' header for the location of the web app.
*
* Important: SDK, worker script and WASM resources must be from the same version of package.
*
* Default value is empty string, i.e. "".
*/
loadSettings.engineLocation = "";
/**
* Optional callback function that will report the SDK loading progress.
*
* This can be useful for displaying progress bar for users on slow connections.
*
* Default value is "null".
*
* @example
* loadSettings.loadProgressCallback = (percentage: number) => console.log(`${ percentage }% loaded!`);
*/
loadSettings.loadProgressCallback = null;
/**
* Location of Web Worker script file. Useful when web frameworks/libraries are used which store
* resources in specific locations, e.g. inside "assets" folder.
*
* Important: worker must be served via HTTPS and must be on the same origin as the initiator.
* See https://github.com/w3c/ServiceWorker/issues/940 (same applies for Web Workers).
*
* Important: SDK, worker script and WASM resources must be from the same version of package.
*
* Default value is empty string, i.e. "". Valid only if "useWebWorker" is set to "true".
*/
loadSettings.workerLocation = "";
// After load settings are configured, proceed with the loading
BlinkIDSDK.loadWasmModule( loadSettings ).then( ... );
There are some additonal development options which can be seen in the configuration class WasmLoadSettings.
This section contains information on how to deploy a web app which uses BlinkID In-browser SDK.
Make sure to serve the web app on HTTPS protocol.
Otherwise, web camera and loading of remote scripts will be blocked by web browser due to security policies.
Files: resources/BlinkIDWasmSDK.{data,js,wasm}
When browser loads the .wasm file it needs to compile it to the native code. This is unlike JavaScript code, which is interpreted and compiled to native code only if needed (JIT, a.k.a. Just-in-time compilation). Therefore, before BlinkID is loaded, the browser must download and compile the provided .wasm file.
In order to make this faster, you should configure your web server to serve .wasm files with Content-Type: application/wasm. This will instruct the browser that this is a WebAssembly file, which most modern browsers will utilize to perform streaming compilation, i.e. they will start compiling the WebAssembly code as soon as first bytes arrive from the server, instead of waiting for the entire file to download.
For more information about streaming compilation, check this article on MDN.
If your server supports serving compressed files, you should utilize that to minimize the download size of your web app. It's easy to notice that .wasm file is not a small file, but it is very compressible. This is also true for all other files that you need to serve for your web app.
For more information about configuring your web server for using compression and for optimal delivery of your web app that uses BlinkID SDK, you should also check the official Emscripten documentation.
It's possible to host WASM and related support files on a location different than the one where web app is located.
For example, it's possible to host WASM and related support files on https://cdn.example.com, while the web app is hosted on https://example.com.
In that case it's important to set CORS headers in response from https://cdn.example.com. i.e. set header Access-Control-Allow-Origin with proper value.
If WASM and related support files are not placed in the same folder with the web app, don't forget to configure instance of WasmSDKLoadSettings:
...
const loadSettings = new BlinkIDSDK.WasmSDKLoadSettings( licenseKey );
loadSettings.engineLocation = "https://cdn.example.com/wasm";
...
File: resources/BlinkIDWasmSDK.worker.min.js
Due to browser security policies, web worker must be placed on the same origin as the web app.
For example, it's not possible to host web worker on https://cdn.example.com, while web app is hosted on the https://example.com.
To provide some level of flexibility, we've exposed configuration option which can be used to define the location of the web worker on the same origin.
For example, it's possible to serve the web app at https://example.com, while web worker file can be placed in the resources subdirectory:
...
const loadSettings = new BlinkIDSDK.WasmSDKLoadSettings( licenseKey );
loadSettings.workerLocation = "/resources";
...
Since license key of BlinkID SDK is tied to the domain name, it's required to initialize the SDK with different license keys based on the location of the web app.
A common scenario is to have different license keys for development on the local machine, staging environment and production environment.
There are two most common approaches regarding setup of license key:
Common approach when working with modern frameworks/libraries.
Simple approach, where handling of license key is done inside the web app.
Here is one possible solution:
let licenseKey = "..."; // Place your development license key here
if ( window.location.hostname === "staging.example.com" ) // Place your staging domain here
{
licenseKey = "..."; // Place your staging license key here
}
if ( window.location.hostname === "example.com" ) // Place your production domain here
{
licenseKey = "..."; // Place your production license key here
}
...
Recognizer concept, RecognizerRunner and VideoRecognizerThis section will first describe what is a Recognizer and how it should be used to perform recognition of the images, videos and camera stream. Next, we will describe what is a RecognizerRunner and how it can be used to tweak the recognition procedure. Finally, a VideoRecognizer will be described and how it builds on top of RecognizerRunner in order to provide support for recognizing a video or a camera stream.
Recognizer conceptThe Recognizer is the basic unit of processing within the BlinkID SDK. Its main purpose is to process the image and extract meaningful information from it. As you will see later, the BlinkID SDK has lots of different Recognizer objects that have various purposes.
The Recognizer is the object on the WebAssembly heap, which means that it will not be automatically cleaned up by the garbage collector once it's not required anymore. Once you are done with using it, you must call the delete method on it to release the memory on the WebAssembly heap. Failing to do so will result in memory leak on the WebAssembly heap which may result with crash of the browser tab running your web app.
Each Recognizer has a Result object, which contains the data that was extracted from the image. The Result for each specific Recognizer can be obtained by calling its getResult method, which will return a Result object placed on the JS heap, i.e. managed by the garbage collector. Therefore, you don't need to call any delete-like methods on the Result object.
Every Recognizer is a stateful object that can be in two possible states: idle state and working state.
While in idle state, you are allowed to call method updateSettings which will update its properties according to given settings object. At any time, you can call its currentSettings method to obtain its currently applied settings object.
After you create a RecognizerRunner with array containing your recognizer, the state of the Recognizer will change to working state, in which Recognizer object will be used for processing. While being in working state, it is not possible to call method updateSettings (calling it will crash your web app). If you need to change configuration of your recognizer while its being used, you need to call its currentSettings method to obtain its current configuration, update it as you need it, create a new Recognizer of the same type, call updateSettings on it with your modified configuration and finally replace the original Recognizer within the RecognizerRunner by calling its reconfigureRecognizers method.
When written as a pseudocode, this would look like:
import * as BlinkIDSDK from "@microblink/blinkid-in-browser-sdk";
// Assume myRecognizerInUse is used by the recognizerRunner
const currentSettings = await myRecognizerInUse.currentSettings();
// Modify currentSettings as you need
const newRecognizer = await BlinkIDSDK.createRecognizer(); // use appropriate recognizer creation function
await newRecognizer.updateSettings( currentSettings );
// Reconfigure recognizerRunner
await recognizerRunner.reconfigureRecognizers( [ newRecognizer ], true ); // use `true` or `false` depending of what you want to achieve (see below for the description)
// newRecognizer is now in use and myRecognizerInUse is no longer in use -
// you can delete it if you don't need it anymore
await myRecognizerInUse.delete();
While Recognizer object works, it changes its internal state and its result. The Recognizer object's Result always starts in Empty state. When corresponding Recognizer object performs the recognition of given image, its Result can either stay in Empty state (in case Recognizer failed to perform recognition), move to Uncertain state (in case Recognizer performed the recognition, but not all mandatory information was extracted) or move to Valid state (in case Recognizer performed recognition and all mandatory information was successfully extracted from the image).
RecognizerRunnerThe RecognizerRunner is the object that manages the chain of individual Recognizer objects within the recognition process.
It must be created by createRecognizerRunner method of the WasmModuleProxy interface, which is a member of WasmSDK interface which is resolved in a promise returned by the loadWasmModule function you've seen above. The function requires a two parameters: an array of Recognizer objects that will be used for processing and a boolean indicating whether multiple Recognizer objects are allowed to have their Results enter the Valid state.
To explain further the boolean parameter, we first need to understand how RecognizerRunner performs image processing.
When the processImage method is called, it processes the image with the first Recognizer in chain. If the Recognizer's Result object changes its state to Valid, then if the above boolean parameter is false, the recognition chain will be broken and promise returned by the method will be immediately resolved. If the above parameter is true, then the image will also be processed with other Recognizer objects in chain, regardless of the state of their Result objects. If, after processing the image with the first Recognizer in chain, its Result object's state is not changed to Valid, the RecognizerRunner will use the next Recognizer object in chain for processing the image and so on - until the end of the chain (if no results become valid or always if above parameter is true) or until it finds the recognizer that has successfully processed the image and changed its Result's state to Valid (if above parameter is false).
You cannot change the order of the Recognizer objects within the chain - no matter the order in which you give Recognizer objects to RecognizerRunner (either to its creation function createRecognizerRunner or to its reconfigureRecognizers method), they are internally ordered in a way that provides best possible performance and accuracy.
Also, in order for BlinkID SDK to be able to order Recognizer objects in recognition chain in the best way possible, it is not allowed to have multiple instances of Recognizer objects of the same type within the chain. Attempting to do so will crash your application.
VideoRecognizerUsing RecognizerRunner directly could be difficult in cases when you want to perform recognition of the video or the live camera stream. Additionally, handling camera management from the web browser can be sometimes challenging. In order to make this much easier, we provided a VideoRecognizer class.
To perform live camera recognition using the VideoRecognizer, you will need an already set up RecognizerRunner object and a reference to HTMLVideoElement to which camera stream will be attached.
To perform the recognition, you should simply write:
const cameraFeed = <HTMLVideoElement> document.getElementById( "cameraFeed" );
try
{
const videoRecognizer = await MicroblinkSDK.VideoRecognizer.createVideoRecognizerFromCameraStream(
cameraFeed,
recognizerRunner
);
const processResult = await videoRecognizer.recognize();
}
catch ( error )
{
// Handle camera error
}
The recognize method of the VideoRecognizer will start the video capture and recognition loop from the camera and will return a Promise that will be resolved when either processImage of the given RecognizerRunner returns Valid for some frame or the timeout given to recognize method is reached (if no timeout is given, a default one is used).
If, instead of performing recognition of live video stream, you want to perform recognition of pre-recorded video file, you should simply construct VideoRecognizer using a different function, as shown below:
const videoRecognizer = await MicroblinkSDK.createVideoRecognizerFromVideoPath(
videoPath,
htmlVideoElement,
recognizerRunner
);
const processResult = await videoRecognizer.recognize();
VideoRecognizerThe procedure for using VideoRecognizer described above is quite simple, but has some limits. For example, you can only perform one shot scan with it. As soon as the promise returned by recognize method resolves, the camera feed is paused and you need to start new recognition. However, if you need to perform multiple recognitions in single camera session, without pausing the camera preview, you can use the startRecognition method, as described in the example below;
videoRecognizer.startRecognition
(
( recognitionState: MicroblinkSDK.RecognizerResultState ) =>
{
// Pause recognition before performing any async operation - this will make sure that
// recognition will not continue while returning the control flow back from this function.
videoRecognizer.pauseRecognition();
// Obtain recognition results directly from recognizers associated with the RecognizerRunner
// that is associated with the VideoRecognizer
if ( shouldContinueScanning )
{
// Resume recognition
videoRecognizer.resumeRecognition( true );
}
else
{
// Pause the camera feed
videoRecognizer.pauseVideoFeed();
// After this line, the VideoRecognizer is in the same state as if promise returned from
// recognizer was resolved
}
// If videoRecognizer is not paused or terminated, after this line the recognition will
// continue and recognition state will be retained
}
);
MetadataCallbacksProcessing events, also known as Metadata callbacks are purely intended for giving processing feedback on UI or to capture some debug information during development of your web app using BlinkID SDK.
Callbacks for all events are bundled into the MetadataCallbacks object. We suggest that you check for more information about available callbacks and events to which you can handle in the source code of the MetadataCallbacks interface.
You can associate your implementation of MetadataCallbacks interface with RecognizerRunner either during creation or by invoking its method setMetadataCallbacks. Please note that both those methods need to pass information about available callbacks to the native code and for efficiency reasons this is done at the time setMetadataCallbacks method is called and not every time when change occurs within the MetadataCallbacks object. This means that if you, for example, set onQuadDetection to MetadataCallbacks after you already called setMetadataCallbacks method, the onQuadDetection will not be registered with the native code and therefore it will not be called.
Similarly, if you, for example, remove the onQuadDetection from MetadataCallbacks object after you already called setMetadataCallbacks method, your app will crash in attempt to invoke non-existing function when our processing code attempts to invoke it. We deliberately do not perform null check here because of two reasons:
Remember, each time you make some changes to MetadataCallbacks object, you need to apply those changes to to your RecognizerRunner by calling its setMetadataCallbacks method.
This section will give a list of all Recognizer objects that are available within BlinkID SDK, their purpose and recommendations how they should be used to get best performance and user experience.
The SuccessFrameGrabberRecognizer is a special Recognizer that wraps some other Recognizer and impersonates it while processing the image. However, when the Recognizer being impersonated changes its Result into Valid state, the SuccessFrameGrabberRecognizer captures the image and saves it into its own Result object.
Since SuccessFrameGrabberRecognizer impersonates its slave Recognizer object, it is not possible to have both concrete Recognizer object and SuccessFrameGrabberRecognizer that wraps it in the same RecognizerRunner at the same time. Doing so will have the same effect as having multiple instances of the same Recognizer in the same RecognizerRunner - it will crash your application. For more information, see paragraph about RecognizerRunner.
This recognizer is best for use cases when you need to capture the exact image that was being processed by some other Recognizer object at the time its Result became Valid. When that happens, SuccessFrameGrabber's Result will also become Valid and will contain described image. That image will be available in its successFrame property.
The IdBarcodeRecognizer is recognizer specialized for scanning barcodes from various ID cards.
The BlinkIdRecognizer scans and extracts data from the single side of the supported document.
You can find the list of the currently supported documents here.
We will continue expanding this recognizer by adding support for new document types in the future. Star this repo to stay updated.
Use BlinkIdCombinedRecognizer for scanning both sides of the supported document. First, it scans and extracts data from the front, then scans and extracts data from the back, and finally, combines results from both sides.
The BlinkIdCombinedRecognizer also performs data matching and returns a flag if the extracted data captured from the front side matches the data from the back.
You can find the list of the currently supported documents here.
We will continue expanding this recognizer by adding support for new document types in the future. Star this repo to stay updated.
In case of problems with the integration of the SDK, first make sure that you have tried integrating the SDK exactly as described in integration instructions.
If you have followed the instructions to the letter and you still have the problems, please contact us at help.microblink.com
In case of problems with using the SDK, you should do as follows:
If you are getting "invalid license key" error or having other license-related problems (e.g. some feature is not enabled that should be), first check the browser console. All license-related problems are logged to web console so it is easy to determine what went wrong.
When you have to determine what is the license-related problem or you simply do not understand the log, you should contact us help.microblink.com. When contacting us, please make sure you provide following information:
If you are having problems with scanning certain items, undesired behaviour on specific device(s), crashes inside BlinkID or anything unmentioned, please do as follows:
This entity is not allowed by currently active license! when I create a specific Recognizer object.Each license key contains information about which features are allowed to use and which are not. This error indicates that your production license does not allow using of specific Recognizer object. You should contact support to check if provided license is OK and that it really contains all features that you have purchased.
Complete source code of the TypeScript wrapper can be found in here.
For any other questions, feel free to contact us at help.microblink.com.
5.5.1
alert() from VideoRecognizer and added allowManualVideoPlayout to constructor of VideoRecognizer classlocateFile method to MicroblinkSDK to fix problem when SDK is not using web workerpackage.json
engines to explicitly specify Node version which was used during developmentrepository field so NPM package can be used with yarn, closes #5FAQs
A simple ID scanning library for WebAssembly-enabled browsers.
The npm package @microblink/blinkid-in-browser-sdk receives a total of 20,762 weekly downloads. As such, @microblink/blinkid-in-browser-sdk popularity was classified as popular.
We found that @microblink/blinkid-in-browser-sdk demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 0 open source maintainers collaborating on the project.
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