有了 ML Kit 的數位墨水辨識功能,您便可識別數位平面上數百種語言的手寫文字,以及分類草圖。
立即試用
- 請試用範例應用程式,瞭解這個 API 的使用範例。
事前準備
在 Podfile 中加入下列 ML Kit 程式庫:
pod 'GoogleMLKit/DigitalInkRecognition', '8.0.0'
安裝或更新專案的 Pod 後,請使用
.xcworkspace
開啟 Xcode 專案。Xcode 13.2.1 以上版本支援 ML Kit。
現在可以開始辨識 Ink
物件中的文字。
建構 Ink
物件
建立 Ink
物件的主要方式是在觸控螢幕上繪製。在 iOS 上,您可以使用 UIImageView 和觸控事件處理常式,在畫面上繪製筆觸,並儲存筆觸的點,以建構 Ink
物件。以下程式碼片段示範了這個一般模式。如需更完整的範例,請參閱快速入門應用程式,該範例會區分觸控事件處理、螢幕繪圖和筆劃資料管理。
Swift
@IBOutlet weak var mainImageView: UIImageView! var kMillisecondsPerTimeInterval = 1000.0 var lastPoint = CGPoint.zero private var strokes: [Stroke] = [] private var points: [StrokePoint] = [] func drawLine(from fromPoint: CGPoint, to toPoint: CGPoint) { UIGraphicsBeginImageContext(view.frame.size) guard let context = UIGraphicsGetCurrentContext() else { return } mainImageView.image?.draw(in: view.bounds) context.move(to: fromPoint) context.addLine(to: toPoint) context.setLineCap(.round) context.setBlendMode(.normal) context.setLineWidth(10.0) context.setStrokeColor(UIColor.white.cgColor) context.strokePath() mainImageView.image = UIGraphicsGetImageFromCurrentImageContext() mainImageView.alpha = 1.0 UIGraphicsEndImageContext() } override func touchesBegan(_ touches: Set, with event: UIEvent?) { guard let touch = touches.first else { return } lastPoint = touch.location(in: mainImageView) let t = touch.timestamp points = [StrokePoint.init(x: Float(lastPoint.x), y: Float(lastPoint.y), t: Int(t * kMillisecondsPerTimeInterval))] drawLine(from:lastPoint, to:lastPoint) } override func touchesMoved(_ touches: Set , with event: UIEvent?) { guard let touch = touches.first else { return } let currentPoint = touch.location(in: mainImageView) let t = touch.timestamp points.append(StrokePoint.init(x: Float(currentPoint.x), y: Float(currentPoint.y), t: Int(t * kMillisecondsPerTimeInterval))) drawLine(from: lastPoint, to: currentPoint) lastPoint = currentPoint } override func touchesEnded(_ touches: Set , with event: UIEvent?) { guard let touch = touches.first else { return } let currentPoint = touch.location(in: mainImageView) let t = touch.timestamp points.append(StrokePoint.init(x: Float(currentPoint.x), y: Float(currentPoint.y), t: Int(t * kMillisecondsPerTimeInterval))) drawLine(from: lastPoint, to: currentPoint) lastPoint = currentPoint strokes.append(Stroke.init(points: points)) self.points = [] doRecognition() }
Objective-C
// Interface @property (weak, nonatomic) IBOutlet UIImageView *mainImageView; @property(nonatomic) CGPoint lastPoint; @property(nonatomic) NSMutableArray*strokes; @property(nonatomic) NSMutableArray *points; // Implementations static const double kMillisecondsPerTimeInterval = 1000.0; - (void)drawLineFrom:(CGPoint)fromPoint to:(CGPoint)toPoint { UIGraphicsBeginImageContext(self.mainImageView.frame.size); [self.mainImageView.image drawInRect:CGRectMake(0, 0, self.mainImageView.frame.size.width, self.mainImageView.frame.size.height)]; CGContextMoveToPoint(UIGraphicsGetCurrentContext(), fromPoint.x, fromPoint.y); CGContextAddLineToPoint(UIGraphicsGetCurrentContext(), toPoint.x, toPoint.y); CGContextSetLineCap(UIGraphicsGetCurrentContext(), kCGLineCapRound); CGContextSetLineWidth(UIGraphicsGetCurrentContext(), 10.0); CGContextSetRGBStrokeColor(UIGraphicsGetCurrentContext(), 1, 1, 1, 1); CGContextSetBlendMode(UIGraphicsGetCurrentContext(), kCGBlendModeNormal); CGContextStrokePath(UIGraphicsGetCurrentContext()); CGContextFlush(UIGraphicsGetCurrentContext()); self.mainImageView.image = UIGraphicsGetImageFromCurrentImageContext(); UIGraphicsEndImageContext(); } - (void)touchesBegan:(NSSet *)touches withEvent:(nullable UIEvent *)event { UITouch *touch = [touches anyObject]; self.lastPoint = [touch locationInView:self.mainImageView]; NSTimeInterval time = [touch timestamp]; self.points = [NSMutableArray array]; [self.points addObject:[[MLKStrokePoint alloc] initWithX:self.lastPoint.x y:self.lastPoint.y t:time * kMillisecondsPerTimeInterval]]; [self drawLineFrom:self.lastPoint to:self.lastPoint]; } - (void)touchesMoved:(NSSet *)touches withEvent:(nullable UIEvent *)event { UITouch *touch = [touches anyObject]; CGPoint currentPoint = [touch locationInView:self.mainImageView]; NSTimeInterval time = [touch timestamp]; [self.points addObject:[[MLKStrokePoint alloc] initWithX:currentPoint.x y:currentPoint.y t:time * kMillisecondsPerTimeInterval]]; [self drawLineFrom:self.lastPoint to:currentPoint]; self.lastPoint = currentPoint; } - (void)touchesEnded:(NSSet *)touches withEvent:(nullable UIEvent *)event { UITouch *touch = [touches anyObject]; CGPoint currentPoint = [touch locationInView:self.mainImageView]; NSTimeInterval time = [touch timestamp]; [self.points addObject:[[MLKStrokePoint alloc] initWithX:currentPoint.x y:currentPoint.y t:time * kMillisecondsPerTimeInterval]]; [self drawLineFrom:self.lastPoint to:currentPoint]; self.lastPoint = currentPoint; if (self.strokes == nil) { self.strokes = [NSMutableArray array]; } [self.strokes addObject:[[MLKStroke alloc] initWithPoints:self.points]]; self.points = nil; [self doRecognition]; }
請注意,程式碼片段包含將筆觸繪製到 UIImageView 的範例函式,您應視應用程式需求進行調整。建議您在繪製線段時使用圓形端點,這樣長度為零的線段就會繪製成點 (例如小寫字母 i 上的點)。每次寫完筆劃後,系統都會呼叫 doRecognition()
函式,定義如下。
取得 DigitalInkRecognizer
的執行個體
如要執行辨識,我們需要將 Ink
物件傳遞至 DigitalInkRecognizer
例項。如要取得 DigitalInkRecognizer
執行個體,我們必須先下載所需語言的辨識器模型,然後將模型載入 RAM。您可以使用下列程式碼片段達成此目的,為求簡單,這個程式碼片段會放在 viewDidLoad()
方法中,並使用硬式編碼的語言名稱。如需向使用者顯示可用語言清單並下載所選語言的範例,請參閱快速入門應用程式。
Swift
override func viewDidLoad() { super.viewDidLoad() let languageTag = "en-US" let identifier = DigitalInkRecognitionModelIdentifier(forLanguageTag: languageTag) if identifier == nil { // no model was found or the language tag couldn't be parsed, handle error. } let model = DigitalInkRecognitionModel.init(modelIdentifier: identifier!) let modelManager = ModelManager.modelManager() let conditions = ModelDownloadConditions.init(allowsCellularAccess: true, allowsBackgroundDownloading: true) modelManager.download(model, conditions: conditions) // Get a recognizer for the language let options: DigitalInkRecognizerOptions = DigitalInkRecognizerOptions.init(model: model) recognizer = DigitalInkRecognizer.digitalInkRecognizer(options: options) }
Objective-C
- (void)viewDidLoad { [super viewDidLoad]; NSString *languagetag = @"en-US"; MLKDigitalInkRecognitionModelIdentifier *identifier = [MLKDigitalInkRecognitionModelIdentifier modelIdentifierForLanguageTag:languagetag]; if (identifier == nil) { // no model was found or the language tag couldn't be parsed, handle error. } MLKDigitalInkRecognitionModel *model = [[MLKDigitalInkRecognitionModel alloc] initWithModelIdentifier:identifier]; MLKModelManager *modelManager = [MLKModelManager modelManager]; [modelManager downloadModel:model conditions:[[MLKModelDownloadConditions alloc] initWithAllowsCellularAccess:YES allowsBackgroundDownloading:YES]]; MLKDigitalInkRecognizerOptions *options = [[MLKDigitalInkRecognizerOptions alloc] initWithModel:model]; self.recognizer = [MLKDigitalInkRecognizer digitalInkRecognizerWithOptions:options]; }
快速入門應用程式包含額外程式碼,可說明如何同時處理多個下載作業,以及如何處理完成通知,判斷哪些下載作業成功。
辨識 Ink
物件
接著是 doRecognition()
函式,為簡化起見,這個函式是從 touchesEnded()
呼叫。在其他應用程式中,您可能只想在逾時後或使用者按下按鈕觸發辨識時,才叫用辨識功能。
Swift
func doRecognition() { let ink = Ink.init(strokes: strokes) recognizer.recognize( ink: ink, completion: { [unowned self] (result: DigitalInkRecognitionResult?, error: Error?) in var alertTitle = "" var alertText = "" if let result = result, let candidate = result.candidates.first { alertTitle = "I recognized this:" alertText = candidate.text } else { alertTitle = "I hit an error:" alertText = error!.localizedDescription } let alert = UIAlertController(title: alertTitle, message: alertText, preferredStyle: UIAlertController.Style.alert) alert.addAction(UIAlertAction(title: "OK", style: UIAlertAction.Style.default, handler: nil)) self.present(alert, animated: true, completion: nil) } ) }
Objective-C
- (void)doRecognition { MLKInk *ink = [[MLKInk alloc] initWithStrokes:self.strokes]; __weak typeof(self) weakSelf = self; [self.recognizer recognizeInk:ink completion:^(MLKDigitalInkRecognitionResult *_Nullable result, NSError *_Nullable error) { typeof(weakSelf) strongSelf = weakSelf; if (strongSelf == nil) { return; } NSString *alertTitle = nil; NSString *alertText = nil; if (result.candidates.count > 0) { alertTitle = @"I recognized this:"; alertText = result.candidates[0].text; } else { alertTitle = @"I hit an error:"; alertText = [error localizedDescription]; } UIAlertController *alert = [UIAlertController alertControllerWithTitle:alertTitle message:alertText preferredStyle:UIAlertControllerStyleAlert]; [alert addAction:[UIAlertAction actionWithTitle:@"OK" style:UIAlertActionStyleDefault handler:nil]]; [strongSelf presentViewController:alert animated:YES completion:nil]; }]; }
管理模型下載作業
我們已瞭解如何下載辨識模型。下列程式碼片段說明如何檢查模型是否已下載,或在不再需要模型時刪除模型,以回收儲存空間。
檢查是否已下載模型
Swift
let model : DigitalInkRecognitionModel = ... let modelManager = ModelManager.modelManager() modelManager.isModelDownloaded(model)
Objective-C
MLKDigitalInkRecognitionModel *model = ...; MLKModelManager *modelManager = [MLKModelManager modelManager]; [modelManager isModelDownloaded:model];
刪除已下載的模型
Swift
let model : DigitalInkRecognitionModel = ... let modelManager = ModelManager.modelManager() if modelManager.isModelDownloaded(model) { modelManager.deleteDownloadedModel( model!, completion: { error in if error != nil { // Handle error return } NSLog(@"Model deleted."); }) }
Objective-C
MLKDigitalInkRecognitionModel *model = ...; MLKModelManager *modelManager = [MLKModelManager modelManager]; if ([self.modelManager isModelDownloaded:model]) { [self.modelManager deleteDownloadedModel:model completion:^(NSError *_Nullable error) { if (error) { // Handle error. return; } NSLog(@"Model deleted."); }]; }
提升文字辨識準確度的訣竅
文字辨識準確度可能因語言而異。準確度也取決於寫作風格。雖然數位墨水辨識功能經過訓練,可處理多種書寫風格,但結果可能因人而異。
以下提供幾種提升文字辨識器準確度的方法。請注意,這些技術不適用於表情符號、自動繪圖和形狀的繪圖分類器。
書寫區
許多應用程式都有明確定義的寫作區,供使用者輸入內容。符號的意義部分取決於符號相對於所含書寫區域的大小。例如,大小寫字母「o」或「c」的差異,以及逗號與正斜線的差異。
告知辨識器書寫區域的寬度和高度,有助於提高準確度。不過,辨識器會假設書寫區域只包含一行文字。如果實體書寫區夠大,可讓使用者書寫兩行以上的文字,您可以傳遞 WritingArea,並將高度設為單行文字高度的最佳估計值,這樣可能會獲得更準確的結果。傳遞至辨識器的 WritingArea 物件不必與螢幕上的實際書寫區域完全對應。以這種方式變更 WritingArea 高度,在某些語言中會比其他語言更有效。
指定書寫區域時,請以與筆劃座標相同的單位指定寬度和高度。x 和 y 座標引數沒有單位規定,因為 API 會將所有單位標準化,因此筆劃的相對大小和位置才是重點。您可以自由傳遞座標,並選擇適合系統的比例。
前文
前文是指您嘗試辨識的 Ink
中,筆劃前方的文字。你可以提供前文內容,協助辨識器辨識語音。
舉例來說,手寫體字母「n」和「u」經常會混淆。如果使用者已輸入部分字詞「arg」,他們可能會繼續輸入可辨識為「ument」或「nment」的筆劃。指定前文脈絡「arg」可解決模稜兩可的情況,因為「argument」比「argnment」更可能出現。
前文脈絡也能協助辨識器找出斷字位置,也就是字與字之間的空格。你可以輸入空格字元,但無法繪製空格字元,因此辨識器如何判斷一個字何時結束,下一個字何時開始?如果使用者已寫下「hello」,並繼續寫下「world」,在沒有前文的情況下,辨識器會傳回「world」字串。不過,如果您指定前文「hello」,模型會傳回「 world」字串 (開頭有空格),因為「hello world」比「helloword」更有意義。
您應盡可能提供最長的預先脈絡字串,最多 20 個字元,包括空格。如果字串較長,辨識器只會使用最後 20 個字元。
以下程式碼範例說明如何定義撰寫區域,並使用 RecognitionContext
物件指定前文。
Swift
let ink: Ink = ...; let recognizer: DigitalInkRecognizer = ...; let preContext: String = ...; let writingArea = WritingArea.init(width: ..., height: ...); let context: DigitalInkRecognitionContext.init( preContext: preContext, writingArea: writingArea); recognizer.recognizeHandwriting( from: ink, context: context, completion: { (result: DigitalInkRecognitionResult?, error: Error?) in if let result = result, let candidate = result.candidates.first { NSLog("Recognized \(candidate.text)") } else { NSLog("Recognition error \(error)") } })
Objective-C
MLKInk *ink = ...; MLKDigitalInkRecognizer *recognizer = ...; NSString *preContext = ...; MLKWritingArea *writingArea = [MLKWritingArea initWithWidth:... height:...]; MLKDigitalInkRecognitionContext *context = [MLKDigitalInkRecognitionContext initWithPreContext:preContext writingArea:writingArea]; [recognizer recognizeHandwritingFromInk:ink context:context completion:^(MLKDigitalInkRecognitionResult *_Nullable result, NSError *_Nullable error) { NSLog(@"Recognition result %@", result.candidates[0].text); }];
筆劃順序
辨識準確度會受到筆劃順序影響。辨識器會預期筆劃順序符合一般書寫習慣,例如英文的筆劃順序為從左到右。如果不是這種情況 (例如以最後一個字開頭撰寫英文句子),結果的準確度就會降低。
另一個例子是移除 Ink
中間的字,並換成另一個字。修訂內容可能位於句子中間,但修訂內容的筆劃位於筆劃序列結尾。在這種情況下,建議您將新寫的字詞分別傳送至 API,並使用自己的邏輯將結果與先前的辨識結果合併。
處理模稜兩可的形狀
有時辨識器收到的形狀意義不明確,舉例來說,邊緣非常圓潤的矩形可能被視為矩形或橢圓。
如有這類不明確的案例,可使用辨識分數 (如有) 處理。只有形狀分類器會提供分數。如果模型非常確定,最佳結果的分數會遠高於第二佳結果。如果存在不確定性,前兩項結果的分數會很接近。此外,請注意形狀分類器會將整個 Ink
解讀為單一形狀。舉例來說,如果 Ink
包含一個矩形和一個相鄰的橢圓形,辨識器可能會傳回其中一個 (或完全不同的項目) 做為結果,因為單一辨識候選項目無法代表兩個形狀。