nativescript-firebase-updated-new
Version:
107 lines • 4.28 kB
JavaScript
import { ImageSource } from "@nativescript/core";
import { MLKitImageLabeling as MLKitImageLabelingBase } from "./imagelabeling-common";
export class MLKitImageLabeling extends MLKitImageLabelingBase {
createDetector() {
return getDetector(this.confidenceThreshold);
}
createSuccessListener() {
return (labels, error) => {
if (error !== null) {
console.log(error.localizedDescription);
}
else if (labels !== null && labels.count > 0) {
const result = {
labels: []
};
for (let i = 0, l = labels.count; i < l; i++) {
const label = labels.objectAtIndex(i);
result.labels.push({
text: label.text,
confidence: label.confidence
});
}
this.notify({
eventName: MLKitImageLabeling.scanResultEvent,
object: this,
value: result
});
}
};
}
rotateRecording() {
return true;
}
}
function getDetector(confidenceThreshold) {
const firVision = FIRVision.vision();
const fIRVisionOnDeviceImageLabelerOptions = FIRVisionOnDeviceImageLabelerOptions.new();
fIRVisionOnDeviceImageLabelerOptions.confidenceThreshold = confidenceThreshold || 0.5;
return firVision.onDeviceImageLabelerWithOptions(fIRVisionOnDeviceImageLabelerOptions);
}
export function labelImageOnDevice(options) {
return new Promise((resolve, reject) => {
try {
const labelDetector = getDetector(options.confidenceThreshold);
labelDetector.processImageCompletion(getImage(options), (labels, error) => {
if (error !== null) {
reject(error.localizedDescription);
}
else if (labels !== null) {
const result = {
labels: []
};
for (let i = 0, l = labels.count; i < l; i++) {
const label = labels.objectAtIndex(i);
result.labels.push({
text: label.text,
confidence: label.confidence
});
}
resolve(result);
}
});
}
catch (ex) {
console.log("Error in firebase.mlkit.labelImageOnDevice: " + ex);
reject(ex);
}
});
}
export function labelImageCloud(options) {
return new Promise((resolve, reject) => {
try {
const fIRVisionCloudImageLabelerOptions = FIRVisionCloudImageLabelerOptions.new();
fIRVisionCloudImageLabelerOptions.confidenceThreshold = options.confidenceThreshold || 0.5;
const firVision = FIRVision.vision();
const labeler = firVision.cloudImageLabelerWithOptions(fIRVisionCloudImageLabelerOptions);
labeler.processImageCompletion(getImage(options), (labels, error) => {
if (error !== null) {
reject(error.localizedDescription);
}
else if (labels !== null) {
const result = {
labels: []
};
for (let i = 0, l = labels.count; i < l; i++) {
const label = labels.objectAtIndex(i);
result.labels.push({
text: label.text,
confidence: label.confidence
});
}
console.log(">>> cloud image labeling result: " + JSON.stringify(result.labels));
resolve(result);
}
});
}
catch (ex) {
console.log("Error in firebase.mlkit.labelImageCloud: " + ex);
reject(ex);
}
});
}
function getImage(options) {
const image = options.image instanceof ImageSource ? options.image.ios : options.image.imageSource.ios;
return FIRVisionImage.alloc().initWithImage(image);
}
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