您可以透過 ML Kit 的數位墨水辨識功能,辨識數百種語言在數位表面上手寫的文字,還可以對草圖分類。
立即體驗
- 請試用範例應用程式,查看這個 API 的使用範例。
事前準備
在 Podfile 中加入下列機器學習套件程式庫:
pod 'GoogleMLKit/DigitalInkRecognition', '3.2.0'
安裝或更新專案的 Pod 後,使用
.xcworkspace
開啟 Xcode 專案。Xcode 13.2.1 以上版本支援機器學習套件。
您現在可以開始辨識 Ink
物件中的文字。
建構 Ink
物件
建構 Ink
物件的主要方法是在觸控螢幕上繪圖。在 iOS 裝置上,您可以使用 UIImageView 和觸控事件處理常式,藉此繪製螢幕上的筆觸,以及儲存筆劃點以建構 Ink
物件。下列程式碼片段將說明這個一般模式。如需更完整的觸控事件處理、螢幕畫面繪圖和筆劃資料管理等功能的範例,請參閱快速入門導覽課程應用程式。
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,程式碼片段包含範例函式,可將筆劃繪製至 UIImageView 中,應根據應用程式進行調整。建議您在繪製線段時使用圓頂,讓零長度的片段被繪製為點 (請想以小寫字母 i 為點)。每個筆劃寫入完畢之後,系統都會呼叫 doRecognition()
函式,並將於下方定義。
取得 DigitalInkRecognizer
的執行個體
如要執行辨識,我們必須將 Ink
物件傳遞至 DigitalInkRecognizer
執行個體。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,並將模型載入 RAM。您可以使用以下程式碼片段完成這項作業。為求簡化,請將程式碼片段放在 viewDidLoad()
方法中,並使用硬式編碼的語言名稱。請參閱快速入門導覽課程應用程式的範例,瞭解如何向使用者顯示可用的語言清單及下載所選語言。
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]; }
快速入門導覽課程應用程式提供額外的程式碼,說明如何同時處理多個下載,以及如何透過處理完成通知來判斷下載成功。
辨識 Ink
物件
接下來是 doRecognition()
函式,為了方便起見,我們會從 touchesEnded()
呼叫該函式。在其他應用程式中,可能只有逾時後或使用者按下按鈕觸發辨識時,才會叫用辨識。
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
我們已經知道如何下載辨識模型。下列程式碼片段說明如何檢查是否已下載模型,或者在不再需要儲存空間時刪除模型。
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."); }]; }
改善文字辨識準確度的訣竅
文字辨識的準確度可能因語言而異。準確率也取決於寫入樣式。雖然 Digital Ink Recognition 經過訓練,可處理各種類型的寫入樣式,但結果可能因使用者而異。
以下提供一些方法,可協助提高文字辨識器的準確度。請注意,這些技巧不適用於表情符號、自動繪圖及形狀的繪圖分類器。
書寫區域
許多應用程式都有使用者定義的寫入區域。符號的含義部分取決於其大小與包含該符號的寫入區域大小相比。例如,小寫英文字母「o」或「c」與半形逗號與正斜線的差異。
告訴辨識器寫入區域的寬度和高度,可以提高準確度。不過,辨識器會假設寫入區域只包含一行文字。如果實體寫入區域夠大,且使用者能夠編寫兩行或更多行,您可以傳入 WriteArea,其高度是您單行文字的高度估計值,進而獲得更好的結果。您傳送給辨識器的 WriteArea 物件不一定要與螢幕上的實體寫入區域完全一致。以這種方式變更 WriteArea 高度,在部分語言上效果會更好。
指定寫入區域時,請在和筆劃座標相同的單位中指定寬度和高度。x、y 座標引數沒有單位要求,API 會將所有單位正規化,因此最重要的是筆劃的相對大小和位置。您可以自由輸入任何適合您的系統的座標,
前後脈絡
預先結構定義是您嘗試辨識的 Ink
中筆觸之前的文字。建議你告訴他們,該前一部將說明背景資訊。
例如,「n」和「u」之類的草字經常被誤認。如果使用者已輸入部分字詞「arg」,他們可能會繼續系統判定為「ument」或「nment」的筆劃。指定前內容「arg」可解決混淆,因為「argument」這個字詞比「argnment」更有可能。
預先背景資訊也有助於辨識者辨識字詞換行,以及字詞之間的空格。您可以輸入空格字元,但無法畫出字元,該如何辨識內容是否能夠判斷某個字詞何時結束?如果使用者已寫入「hello」並繼續寫入「world」,則不需預先背景資訊,辨識器會傳回「world」字串。不過,如果您指定預先內容,「hello」則會傳回模型「亦即」字串 (亦即開頭的空格),因為「hello world」比「helloword」更合理。
您應提供最長的預先內容字串,長度上限為 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寫入區域,並使用 RecognitionContext
物件指定預先背景資訊。
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); }];
筆觸排序
辨識準確度對筆觸順序的影響很敏感。辨識器會預期中生的筆劃順序會自然而然,例如由左到右書寫的英文。任何從這個模式下出現的案件 (例如從最後一個字詞開始編寫英文句子) 都會產生較不準確的結果。
再舉一例,移除 Ink
中間的文字後,替換成其他字詞。修訂版本可能位於句子中間,但修訂版本的筆劃可能出現在筆劃序列結尾。在這種情況下,我們建議您將新撰寫的字詞分別傳送到 API,並透過自己的邏輯將結果與之前的辨識結果合併。
處理模稜兩可的形狀
在某些情況下,提供給辨識器的形狀含義並不明確。舉例來說,矩形的極圓角可以視為矩形或刪節號。
當有這類不明確的案例時,使用分數 (如有) 即可加以處理。只有形狀分類器會提供分數。如果模型非常有信心,結果的分數會遠高於第二名。如果不確定,前兩名結果的分數將會很接近。另請注意,形狀分類器會將整個 Ink
解譯為單一形狀。舉例來說,如果 Ink
包含彼此相鄰的矩形和刪節號,由於辨識器無法表示兩個形狀,因此辨識器可能會傳回其中一個 (或完全不同的) 作為結果。