dynamsoft-label-recognizer
Advanced tools
Dynamsoft Label Recognizer (DLR) is an SDK designed to recognize meaningful zonal text or symbols in an image (Label). Common scenarios include price tags in supermarkets, inventory labels in warehouses, VIN codes on car windshields, driver licenses, pass
With Dynamsoft Label Recognizer JavaScript edition (DLR-JS), you can add the capability of reading text labels such as passport MRZs, ID cards, VIN numbers, etc. in your web application with just a few lines of code.
Once integrated, your users will be able to launch your website in a web browser, activate their camera functionality, and directly recognize the designated text from the video feed.
In this guide, you will learn step by step on how to integrate this SDK into your website.
Table of Contents
Let's start by testing an example that demonstrates how to enable a web page to recognize the text in the machine readable zone (MRZ) of a passport from a live video stream.
The complete code of the example is shown below
<!DOCTYPE html>
<html>
<body>
<script src="https://cdn.jsdelivr.net/npm/dynamsoft-core@3.2.10/dist/core.js"></script>
<script src="https://cdn.jsdelivr.net/npm/dynamsoft-license@3.2.10/dist/license.js"></script>
<script src="https://cdn.jsdelivr.net/npm/dynamsoft-utility@1.2.10/dist/utility.js"></script>
<script src="https://cdn.jsdelivr.net/npm/dynamsoft-label-recognizer@3.2.10/dist/dlr.js"></script>
<script src="https://cdn.jsdelivr.net/npm/dynamsoft-capture-vision-router@2.2.10/dist/cvr.js"></script>
<script src="https://cdn.jsdelivr.net/npm/dynamsoft-camera-enhancer@4.0.2/dist/dce.js"></script>
<div id="cameraViewContainer" style="width: 100%; height: 60vh"></div>
<textarea id="results" style="width: 100%; min-height: 10vh; font-size: 3vmin; overflow: auto" disabled></textarea>
<script>
Dynamsoft.License.LicenseManager.initLicense(
"DLS2eyJvcmdhbml6YXRpb25JRCI6IjIwMDAwMSJ9"
);
(async () => {
let router = await Dynamsoft.CVR.CaptureVisionRouter.createInstance();
let view = await Dynamsoft.DCE.CameraView.createInstance();
let cameraEnhancer = await Dynamsoft.DCE.CameraEnhancer.createInstance(view);
document.querySelector("#cameraViewContainer").append(view.getUIElement());
router.setInput(cameraEnhancer);
const resultsContainer = document.querySelector("#results");
const resultReceiver = new Dynamsoft.CVR.CapturedResultReceiver();
resultReceiver.onRecognizedTextLinesReceived = (result) => {
if (result.textLineResultItems.length > 0) {
resultsContainer.textContent = "";
for (let item of result.textLineResultItems) {
resultsContainer.textContent += `${item.text}\n`;
}
}
};
router.addResultReceiver(resultReceiver);
let filter = new Dynamsoft.Utility.MultiFrameResultCrossFilter();
filter.enableResultCrossVerification("text_line", true);
filter.enableResultDeduplication("text_line", true);
await router.addResultFilter(filter);
await router.initSettings("https://tst.dynamsoft.com/public/samples/dcvTemplates/readPassportMRZ.json");
await cameraEnhancer.open();
await router.startCapturing("passport-mrz");
})();
</script>
</body>
</html>
Dynamsoft.License.LicenseManager.initLicense(): This method initializes the license for using the SDK in the application. Note that the string "DLS2eyJvcmdhbml6YXRpb25JRCI6IjIwMDAwMSJ9" used in this example points to an online license that requires a network connection to work. Read more on Specify the license.
Dynamsoft.CVR.CaptureVisionRouter.createInstance(): This method creates a CaptureVisionRouter object router which controls the entire process in three steps:
router connects to the image source through the ImageSourceAdapter interface with the method setInput().
router.setInput(cameraEnhancer);
The image source in our case is a CameraEnhancer object created with
Dynamsoft.DCE.CameraEnhancer.createInstance(view)
router starts the process by specifying a template "passport-mrz" in the method startCapturing().
// Loads the file that contains the template "passport-mrz".
await router.initSettings("https://tst.dynamsoft.com/public/samples/dcvTemplates/readPassportMRZ.json");
await router.startCapturing("passport-mrz");
CapturedResultReceiver object resultReceiver is registered to router via the method addResultReceiver().
router.addResultReceiver(resultReceiver);
router via the method addResultFilter().
await router.addResultFilter(filter);
Read more on Capture Vision Router.
The easiest way to run the example is to use the JSFiddle code editor. You will be asked to allow access to your camera, after which the video will be displayed on the page. After that, you can point the camera at a passport biographical page to read the text in the machine-readable zone.
When the text is recognized, you will see it show up below the video and the location will be highlighted in the video feed.
Alternatively, you can test locally by copying and pasting the code shown above into a local file (e.g. "read-passport-mrz.html") and opening it in your browser.
Note:
If you open the web page as file:/// or http:// , the camera may not work correctly because the MediaDevices: getUserMedia() method only works in secure contexts (HTTPS), in some or all supporting browsers.
To make sure your web application can access the camera, please configure your web server to support HTTPS. The following links may help.
If the test doesn't go as expected, you can contact us.
To utilize the SDK, the initial step involves including the corresponding resource files:
core.js encompasses common classes, interfaces, and enumerations that are shared across all Dynamsoft SDKs.license.js introduces the LicenseManager class, which manages the licensing for all Dynamsoft SDKs.utility.js encompasses auxiliary classes that are shared among all Dynamsoft SDKs.dlr.js defines interfaces and enumerations specifically tailored to the label recognizer module.cvr.js introduces the CaptureVisionRouter class, which governs the entire image processing workflow.dce.js comprises classes that offer camera support and basic user interface functionalities.The simplest way to include the SDK is to use either the jsDelivr or UNPKG CDN. The "hello world" example above uses jsDelivr.
jsDelivr
<script src="https://cdn.jsdelivr.net/npm/dynamsoft-core@3.2.10/dist/core.js"></script>
<script src="https://cdn.jsdelivr.net/npm/dynamsoft-license@3.2.10/dist/license.js"></script>
<script src="https://cdn.jsdelivr.net/npm/dynamsoft-utility@1.2.10/dist/utility.js"></script>
<script src="https://cdn.jsdelivr.net/npm/dynamsoft-label-recognizer@3.2.10/dist/dlr.js"></script>
<script src="https://cdn.jsdelivr.net/npm/dynamsoft-capture-vision-router@2.2.10/dist/cvr.js"></script>
<script src="https://cdn.jsdelivr.net/npm/dynamsoft-camera-enhancer@4.0.2/dist/dce.js"></script>
UNPKG
<script src="https://unpkg.com/dynamsoft-core@3.2.10/dist/core.js"></script>
<script src="https://unpkg.com/dynamsoft-license@3.2.10/dist/license.js"></script>
<script src="https://unpkg.com/dynamsoft-utility@1.2.10/dist/utility.js"></script>
<script src="https://unpkg.com/dynamsoft-label-recognizer@3.2.10/dist/dlr.js"></script>
<script src="https://unpkg.com/dynamsoft-capture-vision-router@2.2.10/dist/cvr.js"></script>
<script src="https://unpkg.com/dynamsoft-camera-enhancer@4.0.2/dist/dce.js"></script>
In some rare cases (such as some restricted areas), you might not be able to access the CDN. If this happens, you can use the following files for the test.
However, please DO NOT use download2.dynamsoft.com resources in a production application as they are for temporary testing purposes only. Instead, you can try hosting the SDK yourself.
Besides using the public CDN, you can also download the SDK and host its files on your own server or a commercial CDN before including it in your application.
Options to download the SDK:
From the website
yarn
yarn add dynamsoft-core@3.2.10 --save
yarn add dynamsoft-license@3.2.10 --save
yarn add dynamsoft-utility@1.2.10 --save
yarn add dynamsoft-label-recognizer@3.2.10 --save
yarn add dynamsoft-capture-vision-router@2.2.10 --save
yarn add dynamsoft-camera-enhancer@4.0.2 --save
yarn add dynamsoft-capture-vision-std@1.2.0 --save
yarn add dynamsoft-image-processing@2.2.10 --save
yarn add dynamsoft-capture-vision-dnn@1.0.10 --save
yarn add dynamsoft-label-recognizer-data@1.0.10 --save
npm
npm install dynamsoft-core@3.2.10 --save
npm install dynamsoft-license@3.2.10 --save
npm install dynamsoft-utility@1.2.10 --save
npm install dynamsoft-label-recognizer@3.2.10 --save
npm install dynamsoft-capture-vision-router@2.2.10 --save
npm install dynamsoft-camera-enhancer@4.0.2 --save
npm install dynamsoft-capture-vision-std@1.2.0 --save
npm install dynamsoft-image-processing@2.2.10 --save
npm install dynamsoft-capture-vision-dnn@1.0.10 --save
npm install dynamsoft-label-recognizer-data@1.0.10 --save
Depending on how you downloaded the SDK and how you intend to use it, you can typically include it like this:
<script src="./dynamsoft/distributables/dynamsoft-core@3.2.10/dist/core.js"></script>
<script src="./dynamsoft/distributables/dynamsoft-license@3.2.10/dist/license.js"></script>
<script src="./dynamsoft/distributables/dynamsoft-utility@1.2.10/dist/utility.js"></script>
<script src="./dynamsoft/distributables/dynamsoft-label-recognizer@3.2.10/dist/dlr.js"></script>
<script src="./dynamsoft/distributables/dynamsoft-capture-vision-router@2.2.10/dist/cvr.js"></script>
<script src="./dynamsoft/distributables/dynamsoft-camera-enhancer@4.0.2/dist/dce.js"></script>
or
<script src="/node_modules/dynamsoft-core/dist/core.js"></script>
<script src="/node_modules/dynamsoft-license/dist/license.js"></script>
<script src="/node_modules/dynamsoft-utility/dist/utility.js"></script>
<script src="/node_modules/dynamsoft-label-recognizer/dist/dlr.js"></script>
<script src="/node_modules/dynamsoft-capture-vision-router/dist/cvr.js"></script>
<script src="/node_modules/dynamsoft-camera-enhancer/dist/dce.js"></script>
or
import "dynamsoft-license";
import "dynamsoft-capture-vision-router";
import "dynamsoft-label-recognizer";
import { CoreModule } from 'dynamsoft-core';
import { LicenseManager } from 'dynamsoft-license';
Note:
Certain legacy web application servers may lack support for the application/wasm mimetype for .wasm files. To address this, you have two options:
To work properly, the SDK requires a few engine files, which are relatively large and may take quite a few seconds to download. We recommend that you set a longer cache time for these engine files, to maximize the performance of your web application.
Cache-Control: max-age=31536000
Reference: Cache-Control.
Before using the SDK, you need to configure a few things.
To enable the SDK's functionality, you must provide a valid license. Utilize the method initLicense() to set your license key.
Dynamsoft.License.LicenseManager.initLicense("DLS2eyJvcmdhbml6YXRpb25JRCI6IjIwMDAwMSJ9");
As previously stated, the key "DLS2eyJvcmdhbml6YXRpb25JRCI6IjIwMDAwMSJ9" serves as a test license valid for 24 hours, applicable to any newly authorized browser. To test the SDK further, you can request a 30-day free trial license via the customer portal.
Upon registering a Dynamsoft account and obtaining the SDK package from the official website, Dynamsoft will automatically create a 30-day free trial license and embed the corresponding license key into all the provided SDK samples.
This is usually only required with frameworks like Angular or React, etc. where the referenced JavaScript files such as cvr.js, dlr.js are compiled into another file.
The purpose is to tell the SDK where to find the engine files (*.worker.js, *.wasm.js and *.wasm, etc.). The API is called Dynamsoft.Core.CoreModule.engineResourcePaths:
Object.assign(Dynamsoft.Core.CoreModule.engineResourcePaths, {
// The following code uses the jsDelivr CDN, feel free to change it to your own location of these files
core: "https://cdn.jsdelivr.net/npm/dynamsoft-core@3.2.10/dist/",
license: "https://cdn.jsdelivr.net/npm/dynamsoft-license@3.2.10/dist/",
dlr: "https://cdn.jsdelivr.net/npm/dynamsoft-label-recognizer@3.2.10/dist/",
cvr: "https://cdn.jsdelivr.net/npm/dynamsoft-capture-vision-router@2.2.10/dist/",
dce: "https://cdn.jsdelivr.net/npm/dynamsoft-camera-enhancer@4.0.2/dist/",
std: "https://cdn.jsdelivr.net/npm/dynamsoft-capture-vision-std@1.2.0/dist/",
dip: "https://cdn.jsdelivr.net/npm/dynamsoft-image-processing@2.2.10/dist/",
dnn: "https://cdn.jsdelivr.net/npm/dynamsoft-capture-vision-dnn@1.0.10/dist/",
// "dlrData" refers to the location of the Convolutional Neural Network (CNN) inference model used for dlr recognition.
dlrData: "https://cdn.jsdelivr.net/npm/dynamsoft-label-recognizer-data@1.0.10/dist/"
});
The image processing logic is encapsulated within .wasm library files, and these files may require some time for downloading. To enhance the speed, we advise utilizing the following method to preload the libraries.
// Preload the .wasm files
Dynamsoft.Core.CoreModule.loadWasm(["dlr"]);
To use the SDK, we first create a CaptureVisionRouter object.
Dynamsoft.License.LicenseManager.initLicense("DLS2eyJvcmdhbml6YXRpb25JRCI6IjIwMDAwMSJ9");
let router = null;
try {
router = await Dynamsoft.CVR.CaptureVisionRouter.createInstance();
} catch (ex) {
console.error(ex);
}
The CaptureVisionRouter object, denoted as router, is responsible for handling images provided by an image source. In our scenario, we aim to detect text directly from a live video stream. To facilitate this, we initialize a CameraEnhancer object, identified as cameraEnhancer, which is specifically designed to capture image frames from the video feed and subsequently forward them to router.
To enable video streaming on the webpage, we create a CameraView object referred to as view, which is then passed to cameraEnhancer, and its content is displayed on the webpage.
<div id="cameraViewContainer" style="width: 100%; height: 100vh"></div>
let view = await Dynamsoft.DCE.CameraView.createInstance();
let cameraEnhancer = await Dynamsoft.DCE.CameraEnhancer.createInstance(view);
document.querySelector("#cameraViewContainer").append(view.getUIElement());
router.setInput(cameraEnhancer);
Once the image processing is complete, the results are sent to all the registered CapturedResultReceiver objects. Each CapturedResultReceiver object may encompass one or multiple callback functions associated with various result types. In our particular case, our focus is on recognized text within the images, so it's sufficient to define the callback function onRecognizedTextLinesReceived:
const resultsContainer = document.querySelector("#results");
const resultReceiver = new Dynamsoft.CVR.CapturedResultReceiver();
resultReceiver.onRecognizedTextLinesReceived = (result) => {
if (result.textLineResultItems.length > 0) {
resultsContainer.textContent = "";
for (let item of result.textLineResultItems) {
resultsContainer.textContent += `${item.text}\n`;
}
}
};
router.addResultReceiver(resultReceiver);
You can also write code like this. It is the same.
router.addResultReceiver({
onRecognizedTextLinesReceived: (result) => {
if (result.textLineResultItems.length > 0) {
resultsContainer.textContent = "";
for (let item of result.textLineResultItems) {
resultsContainer.textContent += `${item.text}\n`;
}
}
},
});
Check out CapturedResultReceiver for more information.
With the setup now complete, we can proceed to process the images in two straightforward steps:
open() method on cameraEnhancer to initiate video streaming and simultaneously initiate the collection of images. These collected images will be dispatched to router as per its request.initSettings();await cameraEnhancer.open();
await router.initSettings("https://tst.dynamsoft.com/public/samples/dcvTemplates/readPassportMRZ.json");
await router.startCapturing("passport-mrz");
Note:
router is engineered to consistently request images from the image source.readPassportMRZ.json, is used.| Template Name | Function Description |
|---|---|
| RecognizeTextLines_Default | Identifies and reads any text present. |
| RecognizeNumbers | Specializes in recognizing numerical data. |
| RecognizeLetters | Identifies both uppercase and lowercase English alphabets. |
| RecognizeNumbersAndLetters | Reads both numbers and English alphabets (any case). |
| RecognizeNumbersAndUppercaseLetters | Scans numbers and uppercase English alphabets. |
| RecognizeUppercaseLetters | Focuses on recognizing uppercase English alphabets. |
Read more on the preset CaptureVisionTemplates.
When making adjustments to some basic tasks, we often only need to modify SimplifiedCaptureVisionSettings.
We have the option to modify the template to retrieve the original image containing the text. For example:
let settings = await router.getSimplifiedSettings("passport-mrz");
settings.capturedResultItemTypes |=
Dynamsoft.Core.EnumCapturedResultItemType.CRIT_ORIGINAL_IMAGE;
await router.updateSettings("passport-mrz", settings);
await router.startCapturing("passport-mrz");
Please be aware that it is necessary to update the CapturedResultReceiver object to obtain the original image. For instance:
const resultReceiver = new Dynamsoft.CVR.CapturedResultReceiver();
resultReceiver.onCapturedResultReceived = (result) => {
let textLines = result.items.filter(
(item) =>
item.type === Dynamsoft.Core.EnumCapturedResultItemType.CRIT_TEXT_LINE
);
if (textLines.length > 0) {
let image = result.items.filter(
(item) =>
item.type ===
Dynamsoft.Core.EnumCapturedResultItemType.CRIT_ORIGINAL_IMAGE
)[0].imageData;
// The image that we found the text on.
}
};
The SDK is initially configured to process images sequentially without any breaks. Although this setup maximizes performance, it can lead to elevated power consumption, potentially causing the device to overheat. In many cases, it's possible to reduce the reading speed while still satisfying business requirements. The following code snippet illustrates how to adjust the SDK to process an image every 500 milliseconds:
Please bear in mind that in the following code, if an image's processing time is shorter than 500 milliseconds, the SDK will wait for the full 500 milliseconds before proceeding to process the next image. Conversely, if an image's processing time exceeds 500 milliseconds, the subsequent image will be processed immediately upon completion.
let settings = await router.getSimplifiedSettings("passport-mrz");
settings.minImageCaptureInterval = 500;
await router.updateSettings("passport-mrz", settings);
await router.startCapturing("passport-mrz");
You can use the parameter roi (region of interest) together with the parameter roiMeasuredInPercentage to configure the SDK to only read a specific region on the image frames. For example:
let settings = await router.getSimplifiedSettings("passport-mrz");
settings.roiMeasuredInPercentage = true;
settings.roi.points = [
{ x: 5, y: 70 },
{ x: 95, y: 70 },
{ x: 95, y: 90 },
{ x: 5, y: 90 },
];
await router.updateSettings("passport-mrz", settings);
await router.startCapturing("passport-mrz");
While the code above accomplishes the task, a more effective approach is to restrict the scan region directly at the image source, as demonstrated in the following code snippet.
- With the region configured at the image source, the images are cropped right before they are gathered for processing, eliminating the necessity to modify the processing settings further.
cameraEnhancerelevates interactivity by overlaying a mask on the video, providing a clear delineation of the scanning region.- See also: CameraEnhancer::setScanRegion
cameraEnhancer = await Dynamsoft.DCE.CameraEnhancer.createInstance(view);
cameraEnhancer.setScanRegion({
x: 5,
y: 70,
width: 90,
height: 20,
isMeasuredInPercentage: true,
});
While processing video frames, it's common for the same text line to be detected multiple times. To enhance the user experience, we can use MultiFrameResultCrossFilter object, having two options currently at our disposal:
let filter = new Dynamsoft.Utility.MultiFrameResultCrossFilter();
filter.enableResultCrossVerification("text_line", true);
await router.addResultFilter(filter);
Note:
enableResultCrossVerification was designed to cross-validate the outcomes across various frames in a video streaming scenario, enhancing the reliability of the final results.let filter = new Dynamsoft.Utility.MultiFrameResultCrossFilter();
filter.enableResultDeduplication("text_line", true);
await router.addResultFilter(filter);
Note:
enableResultDeduplication was designed to prevent high usage in video streaming scenarios, addressing the repetitive processing of the same text line within a short period of time.Initially, the filter is set to forget a result 3 seconds after it is first received. During this time frame, if an identical result appears, it is ignored.
Under certain circumstances, this duration can be extended with the method setDuplicateForgetTime().
let filter = new Dynamsoft.Utility.MultiFrameResultCrossFilter();
filter.setDuplicateForgetTime(5000); // Extend the duration to 5 seconds.
await router.addResultFilter(filter);
You can also enable both options at the same time:
let filter = new Dynamsoft.Utility.MultiFrameResultCrossFilter();
filter.enableResultCrossVerification("text_line", true);
filter.enableResultDeduplication("text_line", true);
filter.setDuplicateForgetTime(5000);
await router.addResultFilter(filter);
When a text line is detected within the video stream, its position is immediately displayed within the video. Furthermore, utilizing the "Dynamsoft Camera Enhancer" SDK, we can introduce feedback mechanisms, such as emitting a "beep" sound or triggering a "vibration".
The following code snippet adds a "beep" sound for when a text line is found:
const resultReceiver = new Dynamsoft.CVR.CapturedResultReceiver();
resultReceiver.onRecognizedTextLinesReceived = (result) => {
if (result.textLineResultItems.length > 0) {
Dynamsoft.DCE.Feedback.beep();
}
};
await router.addResultReceiver(resultReceiver);
The UI is part of the auxiliary SDK "Dynamsoft Camera Enhancer", read more on how to customize the UI.
DLR requires the following features to work:
Secure context (HTTPS deployment)
When deploying your application / website for production, make sure to serve it via a secure HTTPS connection. This is required for two reasons
Some browsers like Chrome may grant the access for
http://127.0.0.1andhttp://localhostor even for pages opened directly from the local disk (file:///...). This can be helpful for temporary development and test.
WebAssembly, Blob, URL/createObjectURL, Web Workers
The above four features are required for the SDK to work.
MediaDevices/getUserMedia
This API is required for in-browser video streaming.
getSettings
This API inspects the video input which is a MediaStreamTrack object about its constrainable properties.
The following table is a list of supported browsers based on the above requirements:
| Browser Name | Version |
|---|---|
| Chrome | v78+1 |
| Firefox | v62+1 |
| Edge | v79+ |
| Safari | v14+ |
1 devices running iOS needs to be on iOS 14.3+ for camera video streaming to work in Chrome, Firefox or other Apps using webviews.
Apart from the browsers, the operating systems may impose some limitations of their own that could restrict the use of the SDK. Browser compatibility ultimately depends on whether the browser on that particular operating system supports the features listed above.
Learn about what are included in each release at https://www.dynamsoft.com/label-recognition/docs/web/programming/javascript/release-notes/index.html.
Now that you have got the SDK integrated, you can choose to move forward in the following directions
FAQs
Dynamsoft Label Recognizer (DLR) is an SDK designed to recognize meaningful zonal text or symbols in an image (Label). Common scenarios include price tags in supermarkets, inventory labels in warehouses, VIN codes on car windshields, driver licenses, pass
We found that dynamsoft-label-recognizer 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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