A plugin that provides a UI component to access the different functionalities of Google's ML Kit SDK.
npm install @nativescript/mlkit-core
The usage of @nativescript/mlkit-core
has the following flow:
-
Registering and adding MLKitView to your markup.
-
Setting the
detectionType
and listening to thedetection
event.
To access all the vision APIs at once, set the detectionType
property to 'all'
and identify them in the detection
event's handler.
To access a specific API, Barcode scanning for example, set the detectionType
property to the API name ('barcode'
for Barcode scanning), AND import that API's NativeScript plugin(@nativescript/mlkit-barcode-scanning
).
- Check if ML Kit is supported
To verify if ML Kit is supported on the device, call the static
isAvailable()
method on MLKitView class.
if(MLKitView.isAvailable()){
}
- Request for permission to access the device camera by calling
requestCameraPermission()
:
mlKitView.requestCameraPermission().then(()=>{
})
The following are examples of registering and using MLKitView
in the different JS flavors.
-
Register MLKitView by adding
xmlns:ui="@nativescript/mlkit-core"
to the Page element. -
Use the
ui
prefix to accessMLKitView
from the plugin.
<ui:MLKitView
cameraPosition="back"
detectionType="all"
detection="onDetection"
/>
- In Angular, register the
MLKitView
by addingMLKitModule
to theNgModule
of the component where you want to useMLKitView
.
import { MLKitModule } from '@nativescript/mlkit-core/angular';
@NgModule({
imports: [
MLKitModule
],
declarations: [
AppComponent
],
bootstrap: [AppComponent]
})
- Use
MLKitView
in markup.
<MLKitView
cameraPosition="back"
detectionType="all"
(detection)="onDetection($event)"
></MLKitView>
- To use MLKitView, register it in the
app.ts
by passing it to theuse
method of the app instance.
import { createApp } from 'nativescript-vue'
import MLKit from '@nativescript/mlkit-core/vue'
import Home from './components/Home.vue';
const app = createApp(Home)
app.use(MLKit)
- Use
MLKitView
in markup.
<MLKitView
cameraPosition="back"
detectionType="all"
@detection="onDetection"
/>
Important: Detection works only for optional modules installed
npm i @nativescript/mlkit-barcode-scanning
import { DetectionType, DetectionEvent } from '@nativescript/mlkit-core';
import { BarcodeResult } from '@nativescript/mlkit-barcode-scanning';
onDetection(event: DetectionEvent){
if(event.type === DetectionType.Barcode){
const barcode: BarcodeResult[] = event.data;
}
}
For more details, see @nativescript/mlkit-barcode-scanning
npm install @nativescript/mlkit-face-detection
import { DetectionType, DetectionEvent } from '@nativescript/mlkit-core';
import { FaceResult } from '@nativescript/mlkit-face-detection';
onDetection(event: DetectionEvent){
if(event.type === DetectionType.Face){
const faces: FaceResult[] = event.data;
}
}
For more details, see @nativescript/mlkit-face-detection
npm install @nativescript/mlkit-image-labeling
import { DetectionType, DetectionEvent } from '@nativescript/mlkit-core';
import { ImageLabelingResult } from '@nativescript/mlkit-image-labeling';
onDetection(event: DetectionEvent){
if(event.type === DetectionType.Image){
const labels: ImageLabelingResult[] = event.data;
}
}
For more details, see nativescript/mlkit-image-labeling
npm install @nativescript/mlkit-object-detection
import { DetectionType, DetectionEvent } from '@nativescript/mlkit-core';
import { ObjectResult } from '@nativescript/mlkit-object-detection'
onDetection(event: DetectionEvent){
if(event.type === DetectionType.Object){
const objects: ObjectResult[] = event.data;
}
}
For more details, see @nativescript/mlkit-object-detection
npm install @nativescript/mlkit-pose-detection
import { DetectionType, DetectionEvent } from '@nativescript/mlkit-core';
import { PoseResult } from '@nativescript/mlkit-pose-detection';
onDetection(event: DetectionEvent){
if(event.type === DetectionType.Pose){
const poses: PoseResult = event.data;
}
}
For more details, see @nativescript/mlkit-pose-detection
npm install @nativescript/mlkit-text-recognition
import { DetectionType, DetectionEvent } from '@nativescript/mlkit-core';
import { TextResult } from '@nativescript/mlkit-text-recognition';
onDetection(event: DetectionEvent){
if(event.type === DetectionType.Text){
const text: TextResult = event.data;
}
}
For more details, see @nativescript/mlkit-text-recognition
import { DetectionType, detectWithStillImage } from "@nativescript/mlkit-core";
async processStill(args) {
try {
result: { [key: string]: any } = await detectWithStillImage(image: ImageSource, options)
} catch (e) {
console.log(e);
}
}
Detects barcode, pose, etc from a still image instead of using the camera.
image
: The image to detect the object fromoptions
: An optional StillImageDetectionOptions object parameter specifying the detection characteristics.
The MLKitView class provides the camera view for detection.
It has the following members.
Property | Type |
---|---|
detectionEvent |
string |
cameraPosition |
CameraPosition |
detectionType |
DetectionType |
barcodeFormats |
BarcodeFormats |
faceDetectionPerformanceMode |
FaceDetectionPerformanceMode |
faceDetectionTrackingEnabled |
boolean |
faceDetectionMinFaceSize |
number |
imageLabelerConfidenceThreshold |
number |
objectDetectionMultiple |
boolean |
objectDetectionClassify |
boolean |
torchOn |
boolean |
pause |
boolean |
processEveryNthFrame |
number |
readonly latestImage? |
ImageSource |
retrieveLatestImage |
boolean |
Method | Returns | Description |
---|---|---|
isAvailable() |
boolean |
A static method to check if the device supports ML Kit. |
stopPreview() |
void |
|
startPreview() |
void |
|
toggleCamera() |
void |
|
requestCameraPermission() |
Promise<void> |
|
hasCameraPermission() |
boolean |
|
on() |
void |
interface StillImageDetectionOptions {
detectorType: DetectionType;
barcodeScanning?: {
barcodeFormat?: [BarcodeFormats];
};
faceDetection?: {
faceTracking?: boolean;
minimumFaceSize: ?number;
detectionMode?: 'fast' | 'accurate';
landmarkMode?: 'all' | 'none';
contourMode?: 'all' | 'none';
classificationMode?: 'all' | 'none';
};
imageLabeling?: {
confidenceThreshold?: number;
};
objectDetection?: {
multiple: boolean;
classification: boolean;
};
selfieSegmentation?: {
enableRawSizeMask?: boolean;
smoothingRatio?: number;
};
}
export enum DetectionType {
Barcode = 'barcode',
DigitalInk = 'digitalInk',
Face = 'face',
Image = 'image',
Object = 'object',
Pose = 'pose',
Text = 'text',
All = 'all',
Selfie = 'selfie',
None = 'none',
}
export enum CameraPosition {
FRONT = 'front',
BACK = 'back',
}
export enum BarcodeFormats {
ALL = 'all',
CODE_128 = 'code_128',
CODE_39 = 'code_39',
CODE_93 = 'code_93',
CODABAR = 'codabar',
DATA_MATRIX = 'data_matrix',
EAN_13 = 'ean_13',
EAN_8 = 'ean_8',
ITF = 'itf',
QR_CODE = 'qr_code',
UPC_A = 'upc_a',
UPC_E = 'upc_e',
PDF417 = 'pdf417',
AZTEC = 'aztec',
UNKOWN = 'unknown',
}
export enum FaceDetectionPerformanceMode {
Fast = 'fast',
Accurate = 'accurate',
}
Apache License Version 2.0