This page describes an old version of the Barcode Scanning API, which was part of ML Kit for Firebase. Development of this API has been moved to the standalone ML Kit SDK, which you can use with or without Firebase.Learn more.

SeeScan Barcodes with ML Kit on Android for the latest documentation.

You can use ML Kit to recognize and decode barcodes.

1. If you haven't already,add Firebase to your Android project.
2. Add the dependencies for the ML Kit Android libraries to your module (app-level) Gradle file (usuallyapp/build.gradle):

   applyplugin:'com.android.application'applyplugin:'com.google.gms.google-services'dependencies{// ...implementation'com.google.firebase:firebase-ml-vision:24.0.3'implementation'com.google.firebase:firebase-ml-vision-barcode-model:16.0.1'}

Input image guidelines

• For ML Kit to accurately read barcodes, input images must contain barcodes that are represented by sufficient pixel data.

  The specific pixel data requirements are dependent on both the type of barcode and the amount of data that is encoded in it (since most barcodes support a variable length payload). In general, the smallest meaningful unit of the barcode should be at least 2 pixels wide (and for 2-dimensional codes, 2 pixels tall).

  For example, EAN-13 barcodes are made up of bars and spaces that are 1, 2, 3, or 4 units wide, so an EAN-13 barcode image ideally has bars and spaces that are at least 2, 4, 6, and 8 pixels wide. Because an EAN-13 barcode is 95 units wide in total, the barcode should be at least 190 pixels wide.

  Denser formats, such as PDF417, need greater pixel dimensions for ML Kit to reliably read them. For example, a PDF417 code can have up to 34 17-unit wide "words" in a single row, which would ideally be at least 1156 pixels wide.

• Poor image focus can hurt scanning accuracy. If you aren't getting acceptable results, try asking the user to recapture the image.

• For typical applications, it is recommended to provide a higher resolution image (such as 1280x720 or 1920x1080), which makes barcodes detectable from a larger distance away from the camera.

  However, in applications where latency is critical, you can improve performance by capturing images at a lower resolution, but requiring that the barcode make up the majority of the input image. Also seeTips to improve real-time performance.

1. Configure the barcode detector

For example, to detect only Aztec code and QR codes, build aFirebaseVisionBarcodeDetectorOptions object as in the following example:

FirebaseVisionBarcodeDetectorOptionsoptions=newFirebaseVisionBarcodeDetectorOptions.Builder().setBarcodeFormats(FirebaseVisionBarcode.FORMAT_QR_CODE,FirebaseVisionBarcode.FORMAT_AZTEC).build();

valoptions=FirebaseVisionBarcodeDetectorOptions.Builder().setBarcodeFormats(FirebaseVisionBarcode.FORMAT_QR_CODE,FirebaseVisionBarcode.FORMAT_AZTEC).build()

The following formats are supported:

• Code 128 (FORMAT_CODE_128)
• Code 39 (FORMAT_CODE_39)
• Code 93 (FORMAT_CODE_93)
• Codabar (FORMAT_CODABAR)
• EAN-13 (FORMAT_EAN_13)
• EAN-8 (FORMAT_EAN_8)
• ITF (FORMAT_ITF)
• UPC-A (FORMAT_UPC_A)
• UPC-E (FORMAT_UPC_E)
• QR Code (FORMAT_QR_CODE)
• PDF417 (FORMAT_PDF417)
• Aztec (FORMAT_AZTEC)
• Data Matrix (FORMAT_DATA_MATRIX)

1. Create aFirebaseVisionImage object from your image.

   • To create aFirebaseVisionImage object from amedia.Image object, such as when capturing an image from a device's camera, pass themedia.Image object and the image's rotation toFirebaseVisionImage.fromMediaImage().

     If you use the CameraX library, theOnImageCapturedListener andImageAnalysis.Analyzer classes calculate the rotation value for you, so you just need to convert the rotation to one of ML Kit'sROTATION_ constants before callingFirebaseVisionImage.fromMediaImage():

     Java

     privateclassYourAnalyzerimplementsImageAnalysis.Analyzer{privateintdegreesToFirebaseRotation(intdegrees){switch(degrees){case0:returnFirebaseVisionImageMetadata.ROTATION_0;case90:returnFirebaseVisionImageMetadata.ROTATION_90;case180:returnFirebaseVisionImageMetadata.ROTATION_180;case270:returnFirebaseVisionImageMetadata.ROTATION_270;default:thrownewIllegalArgumentException("Rotation must be 0, 90, 180, or 270.");}}@Overridepublicvoidanalyze(ImageProxyimageProxy,intdegrees){if(imageProxy==null||imageProxy.getImage()==null){return;}ImagemediaImage=imageProxy.getImage();introtation=degreesToFirebaseRotation(degrees);FirebaseVisionImageimage=FirebaseVisionImage.fromMediaImage(mediaImage,rotation);// Pass image to an ML Kit Vision API// ...}}

     Kotlin

     privateclassYourImageAnalyzer:ImageAnalysis.Analyzer{privatefundegreesToFirebaseRotation(degrees:Int):Int=when(degrees){0->FirebaseVisionImageMetadata.ROTATION_090->FirebaseVisionImageMetadata.ROTATION_90180->FirebaseVisionImageMetadata.ROTATION_180270->FirebaseVisionImageMetadata.ROTATION_270else->throwException("Rotation must be 0, 90, 180, or 270.")}overridefunanalyze(imageProxy:ImageProxy?,degrees:Int){valmediaImage=imageProxy?.imagevalimageRotation=degreesToFirebaseRotation(degrees)if(mediaImage!=null){valimage=FirebaseVisionImage.fromMediaImage(mediaImage,imageRotation)// Pass image to an ML Kit Vision API// ...}}}

     If you don't use a camera library that gives you the image's rotation, you can calculate it from the device's rotation and the orientation of camera sensor in the device:

     Java

     privatestaticfinalSparseIntArrayORIENTATIONS=newSparseIntArray();static{ORIENTATIONS.append(Surface.ROTATION_0,90);ORIENTATIONS.append(Surface.ROTATION_90,0);ORIENTATIONS.append(Surface.ROTATION_180,270);ORIENTATIONS.append(Surface.ROTATION_270,180);}/** * Get the angle by which an image must be rotated given the device's current * orientation. */@RequiresApi(api=Build.VERSION_CODES.LOLLIPOP)privateintgetRotationCompensation(StringcameraId,Activityactivity,Contextcontext)throwsCameraAccessException{// Get the device's current rotation relative to its "native" orientation.// Then, from the ORIENTATIONS table, look up the angle the image must be// rotated to compensate for the device's rotation.intdeviceRotation=activity.getWindowManager().getDefaultDisplay().getRotation();introtationCompensation=ORIENTATIONS.get(deviceRotation);// On most devices, the sensor orientation is 90 degrees, but for some// devices it is 270 degrees. For devices with a sensor orientation of// 270, rotate the image an additional 180 ((270 + 270) % 360) degrees.CameraManagercameraManager=(CameraManager)context.getSystemService(CAMERA_SERVICE);intsensorOrientation=cameraManager.getCameraCharacteristics(cameraId).get(CameraCharacteristics.SENSOR_ORIENTATION);rotationCompensation=(rotationCompensation+sensorOrientation+270)%360;// Return the corresponding FirebaseVisionImageMetadata rotation value.intresult;switch(rotationCompensation){case0:result=FirebaseVisionImageMetadata.ROTATION_0;break;case90:result=FirebaseVisionImageMetadata.ROTATION_90;break;case180:result=FirebaseVisionImageMetadata.ROTATION_180;break;case270:result=FirebaseVisionImageMetadata.ROTATION_270;break;default:result=FirebaseVisionImageMetadata.ROTATION_0;Log.e(TAG,"Bad rotation value: "+rotationCompensation);}returnresult;}
     VisionImage.java

     Kotlin

     privatevalORIENTATIONS=SparseIntArray()init{ORIENTATIONS.append(Surface.ROTATION_0,90)ORIENTATIONS.append(Surface.ROTATION_90,0)ORIENTATIONS.append(Surface.ROTATION_180,270)ORIENTATIONS.append(Surface.ROTATION_270,180)}/** * Get the angle by which an image must be rotated given the device's current * orientation. */@RequiresApi(api=Build.VERSION_CODES.LOLLIPOP)@Throws(CameraAccessException::class)privatefungetRotationCompensation(cameraId:String,activity:Activity,context:Context):Int{// Get the device's current rotation relative to its "native" orientation.// Then, from the ORIENTATIONS table, look up the angle the image must be// rotated to compensate for the device's rotation.valdeviceRotation=activity.windowManager.defaultDisplay.rotationvarrotationCompensation=ORIENTATIONS.get(deviceRotation)// On most devices, the sensor orientation is 90 degrees, but for some// devices it is 270 degrees. For devices with a sensor orientation of// 270, rotate the image an additional 180 ((270 + 270) % 360) degrees.valcameraManager=context.getSystemService(CAMERA_SERVICE)asCameraManagervalsensorOrientation=cameraManager.getCameraCharacteristics(cameraId).get(CameraCharacteristics.SENSOR_ORIENTATION)!!rotationCompensation=(rotationCompensation+sensorOrientation+270)%360// Return the corresponding FirebaseVisionImageMetadata rotation value.valresult:Intwhen(rotationCompensation){0->result=FirebaseVisionImageMetadata.ROTATION_090->result=FirebaseVisionImageMetadata.ROTATION_90180->result=FirebaseVisionImageMetadata.ROTATION_180270->result=FirebaseVisionImageMetadata.ROTATION_270else->{result=FirebaseVisionImageMetadata.ROTATION_0Log.e(TAG,"Bad rotation value:$rotationCompensation")}}returnresult}
     VisionImage.kt

     Then, pass themedia.Image object and the rotation value toFirebaseVisionImage.fromMediaImage():

     Java

     FirebaseVisionImageimage=FirebaseVisionImage.fromMediaImage(mediaImage,rotation);
     VisionImage.java

     Kotlin

     valimage=FirebaseVisionImage.fromMediaImage(mediaImage,rotation)
     VisionImage.kt

   • To create aFirebaseVisionImage object from a file URI, pass the app context and file URI toFirebaseVisionImage.fromFilePath(). This is useful when you use anACTION_GET_CONTENT intent to prompt the user to select an image from their gallery app.

     Java

     FirebaseVisionImageimage;try{image=FirebaseVisionImage.fromFilePath(context,uri);}catch(IOExceptione){e.printStackTrace();}
     VisionImage.java

     Kotlin

     valimage:FirebaseVisionImagetry{image=FirebaseVisionImage.fromFilePath(context,uri)}catch(e:IOException){e.printStackTrace()}
     VisionImage.kt

   • To create aFirebaseVisionImage object from aByteBuffer or a byte array, first calculate the image rotation as described above formedia.Image input.

     Then, create aFirebaseVisionImageMetadata object that contains the image's height, width, color encoding format, and rotation:

     Java

     FirebaseVisionImageMetadatametadata=newFirebaseVisionImageMetadata.Builder().setWidth(480)// 480x360 is typically sufficient for.setHeight(360)// image recognition.setFormat(FirebaseVisionImageMetadata.IMAGE_FORMAT_NV21).setRotation(rotation).build();
     VisionImage.java

     Kotlin

     valmetadata=FirebaseVisionImageMetadata.Builder().setWidth(480)// 480x360 is typically sufficient for.setHeight(360)// image recognition.setFormat(FirebaseVisionImageMetadata.IMAGE_FORMAT_NV21).setRotation(rotation).build()
     VisionImage.kt

     Use the buffer or array, and the metadata object, to create aFirebaseVisionImage object:

     Java

     FirebaseVisionImageimage=FirebaseVisionImage.fromByteBuffer(buffer,metadata);// Or: FirebaseVisionImage image = FirebaseVisionImage.fromByteArray(byteArray, metadata);
     VisionImage.java

     Kotlin

     valimage=FirebaseVisionImage.fromByteBuffer(buffer,metadata)// Or: val image = FirebaseVisionImage.fromByteArray(byteArray, metadata)
     VisionImage.kt

   • To create aFirebaseVisionImage object from aBitmap object:

     Java

     FirebaseVisionImageimage=FirebaseVisionImage.fromBitmap(bitmap);
     VisionImage.java

     Kotlin

     valimage=FirebaseVisionImage.fromBitmap(bitmap)
     VisionImage.kt

     The image represented by theBitmap object must be upright, with no additional rotation required.

2. Get an instance ofFirebaseVisionBarcodeDetector:

   Java

   FirebaseVisionBarcodeDetectordetector=FirebaseVision.getInstance().getVisionBarcodeDetector();// Or, to specify the formats to recognize:// FirebaseVisionBarcodeDetector detector = FirebaseVision.getInstance()//        .getVisionBarcodeDetector(options);

   Kotlin

   valdetector=FirebaseVision.getInstance().visionBarcodeDetector// Or, to specify the formats to recognize:// val detector = FirebaseVision.getInstance()//        .getVisionBarcodeDetector(options)

3. Finally, pass the image to thedetectInImage method:

   Java

   Task<List<FirebaseVisionBarcode>>result=detector.detectInImage(image).addOnSuccessListener(newOnSuccessListener<List<FirebaseVisionBarcode>>(){@OverridepublicvoidonSuccess(List<FirebaseVisionBarcode>barcodes){// Task completed successfully// ...}}).addOnFailureListener(newOnFailureListener(){@OverridepublicvoidonFailure(@NonNullExceptione){// Task failed with an exception// ...}});

   Kotlin

   valresult=detector.detectInImage(image).addOnSuccessListener{barcodes->// Task completed successfully// ...}.addOnFailureListener{// Task failed with an exception// ...}

3. Get information from barcodes

For example:

for(FirebaseVisionBarcodebarcode:barcodes){Rectbounds=barcode.getBoundingBox();Point[]corners=barcode.getCornerPoints();StringrawValue=barcode.getRawValue();intvalueType=barcode.getValueType();// See API reference for complete list of supported typesswitch(valueType){caseFirebaseVisionBarcode.TYPE_WIFI:Stringssid=barcode.getWifi().getSsid();Stringpassword=barcode.getWifi().getPassword();inttype=barcode.getWifi().getEncryptionType();break;caseFirebaseVisionBarcode.TYPE_URL:Stringtitle=barcode.getUrl().getTitle();Stringurl=barcode.getUrl().getUrl();break;}}

for(barcodeinbarcodes){valbounds=barcode.boundingBoxvalcorners=barcode.cornerPointsvalrawValue=barcode.rawValuevalvalueType=barcode.valueType// See API reference for complete list of supported typeswhen(valueType){FirebaseVisionBarcode.TYPE_WIFI->{valssid=barcode.wifi!!.ssidvalpassword=barcode.wifi!!.passwordvaltype=barcode.wifi!!.encryptionType}FirebaseVisionBarcode.TYPE_URL->{valtitle=barcode.url!!.titlevalurl=barcode.url!!.url}}}

Tips to improve real-time performance

If you want to scan barcodes in a real-time application, follow these guidelines to achieve the best framerates:

• Don't capture input at the camera’s native resolution. On some devices, capturing input at the native resolution produces extremely large (10+ megapixels) images, which results in very poor latency with no benefit to accuracy. Instead, only request the size from the camera that is required for barcode detection: usually no more than 2 megapixels.

  If scanning speed is important, you can further lower the image capture resolution. However, bear in mind the minimum barcode size requirements outlined above.

• Throttle calls to the detector. If a new video frame becomes available while the detector is running, drop the frame.
• If you are using the output of the detector to overlay graphics on the input image, first get the result from ML Kit, then render the image and overlay in a single step. By doing so, you render to the display surface only once for each input frame.

• If you use the Camera2 API, capture images inImageFormat.YUV_420_888 format.

  If you use the older Camera API, capture images inImageFormat.NV21 format.