diff --git a/packages/firebase_ml_vision/CHANGELOG.md b/packages/firebase_ml_vision/CHANGELOG.md
index dcd92333eb79..b931f55c039e 100644
--- a/packages/firebase_ml_vision/CHANGELOG.md
+++ b/packages/firebase_ml_vision/CHANGELOG.md
@@ -1,3 +1,9 @@
+## 0.2.0
+
+* **Breaking Change** Update TextDetector to TextRecognizer for android mlkit '17.0.0' and
+firebase-ios-sdk '5.6.0'.
+* Added CloudLabelDetector.
+
 ## 0.1.2
 
 * Fix example imports so that publishing will be warning-free.
diff --git a/packages/firebase_ml_vision/README.md b/packages/firebase_ml_vision/README.md
index 0a17d0ac12f7..a06d017e24a6 100644
--- a/packages/firebase_ml_vision/README.md
+++ b/packages/firebase_ml_vision/README.md
@@ -1,8 +1,8 @@
-# Google ML Kit for Firebase
+# ML Kit for Firebase
 
 [![pub package](https://img.shields.io/pub/v/firebase_ml_vision.svg)](https://pub.dartlang.org/packages/firebase_ml_vision)
 
-A Flutter plugin to use the [Google ML Kit for Firebase API](https://firebase.google.com/docs/ml-kit/).
+A Flutter plugin to use the [ML Kit for Firebase API](https://firebase.google.com/docs/ml-kit/).
 
 For Flutter plugins for other Firebase products, see [FlutterFire.md](https://github.com/flutter/plugins/blob/master/FlutterFire.md).
 
@@ -42,12 +42,13 @@ Get an instance of a `FirebaseVisionDetector`.
 
 ```dart
 final BarcodeDetector barcodeDetector = FirebaseVision.instance.barcodeDetector();
+final CloudLabelDetector cloudLabelDetector = FirebaseVision.instance.cloudLabelDetector();
 final FaceDetector faceDetector = FirebaseVision.instance.faceDetector();
 final LabelDetector labelDetector = FirebaseVision.instance.labelDetector();
-final TextDetector textDetector = FirebaseVision.instance.textDetector();
+final TextRecognizer textRecognizer = FirebaseVision.instance.textRecognizer();
 ```
 
-You can also configure all detectors except `TextDetector` with desired options.
+You can also configure all detectors except `TextRecognizer` with desired options.
 
 ```dart
 final LabelDetector detector = FirebaseVision.instance.labelDetector(
@@ -59,9 +60,10 @@ final LabelDetector detector = FirebaseVision.instance.labelDetector(
 
 ```dart
 final List<Barcode> barcodes = await barcodeDetector.detectInImage(visionImage);
+final List<Label> labels = await cloudLabelDetector.detectInImage(visionImage);
 final List<Face> faces = await faceDetector.detectInImage(visionImage);
 final List<Label> labels = await labelDetector.detectInImage(visionImage);
-final List<TextBlock> blocks = await textDetector.detectInImage(visionImage);
+final VisionText visionText = await textRecognizer.detectInImage(visionImage);
 ```
 
 ### 4. Extract data.
@@ -133,16 +135,17 @@ for (Label label in labels) {
 d. Extract text.
 
 ```dart
-for (TextBlock block in blocks) {
+String text = visionText.text;
+for (TextBlock block in visionText.blocks) {
   final Rectangle<int> boundingBox = block.boundingBox;
   final List<Point<int>> cornerPoints = block.cornerPoints;
   final String text = block.text;
+  final List<RecognizedLanguage> languages = block.recognizedLanguages;
 
   for (TextLine line in block.lines) {
-    // ...
-
+    // Same getters as TextBlock
     for (TextElement element in line.elements) {
-      // ...
+      // Same getters as TextBlock
     }
   }
 }
@@ -150,4 +153,4 @@ for (TextBlock block in blocks) {
 
 ## Getting Started
 
-See the `example` directory for a complete sample app using Google ML Kit for Firebase.
+See the `example` directory for a complete sample app using ML Kit for Firebase.
diff --git a/packages/firebase_ml_vision/android/src/main/java/io/flutter/plugins/firebasemlvision/CloudLabelDetector.java b/packages/firebase_ml_vision/android/src/main/java/io/flutter/plugins/firebasemlvision/CloudLabelDetector.java
index 9af32b42335c..ce0c9cfd35af 100644
--- a/packages/firebase_ml_vision/android/src/main/java/io/flutter/plugins/firebasemlvision/CloudLabelDetector.java
+++ b/packages/firebase_ml_vision/android/src/main/java/io/flutter/plugins/firebasemlvision/CloudLabelDetector.java
@@ -55,7 +55,20 @@ public void onFailure(@NonNull Exception e) {
 
   private FirebaseVisionCloudDetectorOptions parseOptions(Map<String, Object> optionsData) {
     final int maxResults = (int) optionsData.get("maxResults");
-    final int modelType = (int) optionsData.get("modelType");
+    final String modelTypeStr = (String) optionsData.get("modelType");
+
+    final int modelType;
+    switch (modelTypeStr) {
+      case "stable":
+        modelType = FirebaseVisionCloudDetectorOptions.STABLE_MODEL;
+        break;
+      case "latest":
+        modelType = FirebaseVisionCloudDetectorOptions.LATEST_MODEL;
+        break;
+      default:
+        throw new IllegalArgumentException(String.format("No type for model: %s", modelTypeStr));
+    }
+
     return new FirebaseVisionCloudDetectorOptions.Builder()
         .setMaxResults(maxResults)
         .setModelType(modelType)
diff --git a/packages/firebase_ml_vision/android/src/main/java/io/flutter/plugins/firebasemlvision/FirebaseMlVisionPlugin.java b/packages/firebase_ml_vision/android/src/main/java/io/flutter/plugins/firebasemlvision/FirebaseMlVisionPlugin.java
index ccc5eae5ecca..45cb19fea3c2 100644
--- a/packages/firebase_ml_vision/android/src/main/java/io/flutter/plugins/firebasemlvision/FirebaseMlVisionPlugin.java
+++ b/packages/firebase_ml_vision/android/src/main/java/io/flutter/plugins/firebasemlvision/FirebaseMlVisionPlugin.java
@@ -37,8 +37,6 @@ public void onMethodCall(MethodCall call, Result result) {
           BarcodeDetector.instance.handleDetection(image, options, result);
         } catch (IOException e) {
           result.error("barcodeDetectorIOError", e.getLocalizedMessage(), null);
-        } catch (Exception e) {
-          result.error("barcodeDetectorError", e.getLocalizedMessage(), null);
         }
         break;
       case "FaceDetector#detectInImage":
@@ -47,8 +45,6 @@ public void onMethodCall(MethodCall call, Result result) {
           FaceDetector.instance.handleDetection(image, options, result);
         } catch (IOException e) {
           result.error("faceDetectorIOError", e.getLocalizedMessage(), null);
-        } catch (Exception e) {
-          result.error("faceDetectorError", e.getLocalizedMessage(), null);
         }
         break;
       case "LabelDetector#detectInImage":
@@ -57,8 +53,6 @@ public void onMethodCall(MethodCall call, Result result) {
           LabelDetector.instance.handleDetection(image, options, result);
         } catch (IOException e) {
           result.error("labelDetectorIOError", e.getLocalizedMessage(), null);
-        } catch (Exception e) {
-          result.error("labelDetectorError", e.getLocalizedMessage(), null);
         }
         break;
       case "CloudLabelDetector#detectInImage":
@@ -66,19 +60,15 @@ public void onMethodCall(MethodCall call, Result result) {
           image = filePathToVisionImage((String) call.argument("path"));
           CloudLabelDetector.instance.handleDetection(image, options, result);
         } catch (IOException e) {
-          result.error("labelDetectorIOError", e.getLocalizedMessage(), null);
-        } catch (Exception e) {
-          result.error("labelDetectorError", e.getLocalizedMessage(), null);
+          result.error("cloudLabelDetectorIOError", e.getLocalizedMessage(), null);
         }
         break;
-      case "TextRecognizer#detectInImage":
+      case "TextRecognizer#processImage":
         try {
           image = filePathToVisionImage((String) call.argument("path"));
           TextRecognizer.instance.handleDetection(image, options, result);
         } catch (IOException e) {
           result.error("textRecognizerIOError", e.getLocalizedMessage(), null);
-        } catch (Exception e) {
-          result.error("textRecognizerError", e.getLocalizedMessage(), null);
         }
         break;
       default:
diff --git a/packages/firebase_ml_vision/example/lib/detector_painters.dart b/packages/firebase_ml_vision/example/lib/detector_painters.dart
index f1953cb3a10f..c9248e1bbb64 100644
--- a/packages/firebase_ml_vision/example/lib/detector_painters.dart
+++ b/packages/firebase_ml_vision/example/lib/detector_painters.dart
@@ -122,10 +122,10 @@ class LabelDetectorPainter extends CustomPainter {
 
 // Paints rectangles around all the text in the image.
 class TextDetectorPainter extends CustomPainter {
-  TextDetectorPainter(this.absoluteImageSize, this.textLocations);
+  TextDetectorPainter(this.absoluteImageSize, this.visionText);
 
   final Size absoluteImageSize;
-  final List<TextBlock> textLocations;
+  final VisionText visionText;
 
   @override
   void paint(Canvas canvas, Size size) {
@@ -145,7 +145,7 @@ class TextDetectorPainter extends CustomPainter {
       ..style = PaintingStyle.stroke
       ..strokeWidth = 2.0;
 
-    for (TextBlock block in textLocations) {
+    for (TextBlock block in visionText.blocks) {
       for (TextLine line in block.lines) {
         for (TextElement element in line.elements) {
           paint.color = Colors.green;
@@ -164,6 +164,6 @@ class TextDetectorPainter extends CustomPainter {
   @override
   bool shouldRepaint(TextDetectorPainter oldDelegate) {
     return oldDelegate.absoluteImageSize != absoluteImageSize ||
-        oldDelegate.textLocations != textLocations;
+        oldDelegate.visionText != visionText;
   }
 }
diff --git a/packages/firebase_ml_vision/example/lib/main.dart b/packages/firebase_ml_vision/example/lib/main.dart
index 541fe74212f1..224154bed00a 100644
--- a/packages/firebase_ml_vision/example/lib/main.dart
+++ b/packages/firebase_ml_vision/example/lib/main.dart
@@ -21,7 +21,7 @@ class _MyHomePage extends StatefulWidget {
 class _MyHomePageState extends State<_MyHomePage> {
   File _imageFile;
   Size _imageSize;
-  List<dynamic> _scanResults;
+  dynamic _scanResults;
   Detector _currentDetector = Detector.text;
 
   Future<void> _getAndScanImage() async {
@@ -85,13 +85,13 @@ class _MyHomePageState extends State<_MyHomePage> {
         detector = FirebaseVision.instance.cloudLabelDetector();
         break;
       case Detector.text:
-        detector = FirebaseVision.instance.textDetector();
+        detector = FirebaseVision.instance.textRecognizer();
         break;
       default:
         return;
     }
 
-    final List<dynamic> results =
+    final dynamic results =
         await detector.detectInImage(visionImage) ?? <dynamic>[];
 
     setState(() {
@@ -99,7 +99,7 @@ class _MyHomePageState extends State<_MyHomePage> {
     });
   }
 
-  CustomPaint _buildResults(Size imageSize, List<dynamic> results) {
+  CustomPaint _buildResults(Size imageSize, dynamic results) {
     CustomPainter painter;
 
     switch (_currentDetector) {
diff --git a/packages/firebase_ml_vision/ios/Classes/CloudLabelDetector.m b/packages/firebase_ml_vision/ios/Classes/CloudLabelDetector.m
index d1e1c38daad5..3be3948b4a9f 100644
--- a/packages/firebase_ml_vision/ios/Classes/CloudLabelDetector.m
+++ b/packages/firebase_ml_vision/ios/Classes/CloudLabelDetector.m
@@ -34,14 +34,18 @@ + (void)handleDetection:(FIRVisionImage *)image
 }
 
 + (FIRVisionCloudDetectorOptions *)parseOptions:(NSDictionary *)optionsData {
-  FIRVisionCloudDetectorOptions *detector = [[FIRVisionCloudDetectorOptions alloc] init];
-
-  NSNumber *modelType = optionsData[@"modelType"];
-  detector.modelType = (FIRVisionCloudModelType)[modelType intValue];
+  FIRVisionCloudDetectorOptions *options = [[FIRVisionCloudDetectorOptions alloc] init];
 
   NSNumber *maxResults = optionsData[@"maxResults"];
-  detector.maxResults = [maxResults unsignedIntegerValue];
+  options.maxResults = [maxResults unsignedIntegerValue];
+
+  NSString *modelTypeStr = optionsData[@"modelType"];
+  if ([@"stable" isEqualToString:modelTypeStr]) {
+    options.modelType = FIRVisionCloudModelTypeStable;
+  } else if ([@"latest" isEqualToString:modelTypeStr]) {
+    options.modelType = FIRVisionCloudModelTypeLatest;
+  }
 
-  return detector;
+  return options;
 }
 @end
diff --git a/packages/firebase_ml_vision/ios/Classes/FaceDetector.m b/packages/firebase_ml_vision/ios/Classes/FaceDetector.m
index c1aa9e556964..ed8ab7f0e5c9 100644
--- a/packages/firebase_ml_vision/ios/Classes/FaceDetector.m
+++ b/packages/firebase_ml_vision/ios/Classes/FaceDetector.m
@@ -10,66 +10,66 @@ + (void)handleDetection:(FIRVisionImage *)image
   faceDetector = [vision faceDetectorWithOptions:[FaceDetector parseOptions:options]];
 
   [faceDetector
-      detectInImage:image
-         completion:^(NSArray<FIRVisionFace *> *_Nullable faces, NSError *_Nullable error) {
-           if (error) {
-             [FLTFirebaseMlVisionPlugin handleError:error result:result];
-             return;
-           } else if (!faces) {
-             result(@[]);
-             return;
-           }
-
-           NSMutableArray *faceData = [NSMutableArray array];
-           for (FIRVisionFace *face in faces) {
-             id smileProb = face.hasSmilingProbability ? @(face.smilingProbability) : [NSNull null];
-             id leftProb =
-                 face.hasLeftEyeOpenProbability ? @(face.leftEyeOpenProbability) : [NSNull null];
-             id rightProb =
-                 face.hasRightEyeOpenProbability ? @(face.rightEyeOpenProbability) : [NSNull null];
-
-             NSDictionary *data = @{
-               @"left" : @((int)face.frame.origin.x),
-               @"top" : @((int)face.frame.origin.y),
-               @"width" : @((int)face.frame.size.width),
-               @"height" : @((int)face.frame.size.height),
-               @"headEulerAngleY" : face.hasHeadEulerAngleY ? @(face.headEulerAngleY)
-                                                            : [NSNull null],
-               @"headEulerAngleZ" : face.hasHeadEulerAngleZ ? @(face.headEulerAngleZ)
-                                                            : [NSNull null],
-               @"smilingProbability" : smileProb,
-               @"leftEyeOpenProbability" : leftProb,
-               @"rightEyeOpenProbability" : rightProb,
-               @"trackingId" : face.hasTrackingID ? @(face.trackingID) : [NSNull null],
-               @"landmarks" : @{
-                 @"bottomMouth" : [FaceDetector getLandmarkPosition:face
-                                                           landmark:FIRFaceLandmarkTypeMouthBottom],
-                 @"leftCheek" :
-                     [FaceDetector getLandmarkPosition:face landmark:FIRFaceLandmarkTypeLeftCheek],
-                 @"leftEar" :
-                     [FaceDetector getLandmarkPosition:face landmark:FIRFaceLandmarkTypeLeftEar],
-                 @"leftEye" :
-                     [FaceDetector getLandmarkPosition:face landmark:FIRFaceLandmarkTypeLeftEye],
-                 @"leftMouth" :
-                     [FaceDetector getLandmarkPosition:face landmark:FIRFaceLandmarkTypeMouthLeft],
-                 @"noseBase" :
-                     [FaceDetector getLandmarkPosition:face landmark:FIRFaceLandmarkTypeNoseBase],
-                 @"rightCheek" :
-                     [FaceDetector getLandmarkPosition:face landmark:FIRFaceLandmarkTypeRightCheek],
-                 @"rightEar" :
-                     [FaceDetector getLandmarkPosition:face landmark:FIRFaceLandmarkTypeRightEar],
-                 @"rightEye" :
-                     [FaceDetector getLandmarkPosition:face landmark:FIRFaceLandmarkTypeRightEye],
-                 @"rightMouth" :
-                     [FaceDetector getLandmarkPosition:face landmark:FIRFaceLandmarkTypeMouthRight],
-               },
-             };
-
-             [faceData addObject:data];
-           }
-
-           result(faceData);
-         }];
+      processImage:image
+        completion:^(NSArray<FIRVisionFace *> *_Nullable faces, NSError *_Nullable error) {
+          if (error) {
+            [FLTFirebaseMlVisionPlugin handleError:error result:result];
+            return;
+          } else if (!faces) {
+            result(@[]);
+            return;
+          }
+
+          NSMutableArray *faceData = [NSMutableArray array];
+          for (FIRVisionFace *face in faces) {
+            id smileProb = face.hasSmilingProbability ? @(face.smilingProbability) : [NSNull null];
+            id leftProb =
+                face.hasLeftEyeOpenProbability ? @(face.leftEyeOpenProbability) : [NSNull null];
+            id rightProb =
+                face.hasRightEyeOpenProbability ? @(face.rightEyeOpenProbability) : [NSNull null];
+
+            NSDictionary *data = @{
+              @"left" : @((int)face.frame.origin.x),
+              @"top" : @((int)face.frame.origin.y),
+              @"width" : @((int)face.frame.size.width),
+              @"height" : @((int)face.frame.size.height),
+              @"headEulerAngleY" : face.hasHeadEulerAngleY ? @(face.headEulerAngleY)
+                                                           : [NSNull null],
+              @"headEulerAngleZ" : face.hasHeadEulerAngleZ ? @(face.headEulerAngleZ)
+                                                           : [NSNull null],
+              @"smilingProbability" : smileProb,
+              @"leftEyeOpenProbability" : leftProb,
+              @"rightEyeOpenProbability" : rightProb,
+              @"trackingId" : face.hasTrackingID ? @(face.trackingID) : [NSNull null],
+              @"landmarks" : @{
+                @"bottomMouth" :
+                    [FaceDetector getLandmarkPosition:face landmark:FIRFaceLandmarkTypeMouthBottom],
+                @"leftCheek" :
+                    [FaceDetector getLandmarkPosition:face landmark:FIRFaceLandmarkTypeLeftCheek],
+                @"leftEar" :
+                    [FaceDetector getLandmarkPosition:face landmark:FIRFaceLandmarkTypeLeftEar],
+                @"leftEye" :
+                    [FaceDetector getLandmarkPosition:face landmark:FIRFaceLandmarkTypeLeftEye],
+                @"leftMouth" :
+                    [FaceDetector getLandmarkPosition:face landmark:FIRFaceLandmarkTypeMouthLeft],
+                @"noseBase" :
+                    [FaceDetector getLandmarkPosition:face landmark:FIRFaceLandmarkTypeNoseBase],
+                @"rightCheek" :
+                    [FaceDetector getLandmarkPosition:face landmark:FIRFaceLandmarkTypeRightCheek],
+                @"rightEar" :
+                    [FaceDetector getLandmarkPosition:face landmark:FIRFaceLandmarkTypeRightEar],
+                @"rightEye" :
+                    [FaceDetector getLandmarkPosition:face landmark:FIRFaceLandmarkTypeRightEye],
+                @"rightMouth" :
+                    [FaceDetector getLandmarkPosition:face landmark:FIRFaceLandmarkTypeMouthRight],
+              },
+            };
+
+            [faceData addObject:data];
+          }
+
+          result(faceData);
+        }];
 }
 
 + (id)getLandmarkPosition:(FIRVisionFace *)face landmark:(FIRFaceLandmarkType)landmarkType {
@@ -86,29 +86,29 @@ + (FIRVisionFaceDetectorOptions *)parseOptions:(NSDictionary *)optionsData {
 
   NSNumber *enableClassification = optionsData[@"enableClassification"];
   if (enableClassification.boolValue) {
-    options.classificationType = FIRVisionFaceDetectorClassificationAll;
+    options.classificationMode = FIRVisionFaceDetectorClassificationModeAll;
   } else {
-    options.classificationType = FIRVisionFaceDetectorClassificationNone;
+    options.classificationMode = FIRVisionFaceDetectorClassificationModeNone;
   }
 
   NSNumber *enableLandmarks = optionsData[@"enableLandmarks"];
   if (enableLandmarks.boolValue) {
-    options.landmarkType = FIRVisionFaceDetectorLandmarkAll;
+    options.landmarkMode = FIRVisionFaceDetectorLandmarkModeAll;
   } else {
-    options.landmarkType = FIRVisionFaceDetectorLandmarkNone;
+    options.landmarkMode = FIRVisionFaceDetectorLandmarkModeNone;
   }
 
   NSNumber *enableTracking = optionsData[@"enableTracking"];
-  options.isTrackingEnabled = enableTracking.boolValue;
+  options.trackingEnabled = enableTracking.boolValue;
 
   NSNumber *minFaceSize = optionsData[@"minFaceSize"];
   options.minFaceSize = [minFaceSize doubleValue];
 
   NSString *mode = optionsData[@"mode"];
   if ([mode isEqualToString:@"accurate"]) {
-    options.modeType = FIRVisionFaceDetectorModeAccurate;
+    options.performanceMode = FIRVisionFaceDetectorPerformanceModeAccurate;
   } else if ([mode isEqualToString:@"fast"]) {
-    options.modeType = FIRVisionFaceDetectorModeFast;
+    options.performanceMode = FIRVisionFaceDetectorPerformanceModeFast;
   }
 
   return options;
diff --git a/packages/firebase_ml_vision/ios/Classes/FirebaseMlVisionPlugin.m b/packages/firebase_ml_vision/ios/Classes/FirebaseMlVisionPlugin.m
index 2935e3985fb3..2b51f3d6a0ff 100644
--- a/packages/firebase_ml_vision/ios/Classes/FirebaseMlVisionPlugin.m
+++ b/packages/firebase_ml_vision/ios/Classes/FirebaseMlVisionPlugin.m
@@ -46,7 +46,7 @@ - (void)handleMethodCall:(FlutterMethodCall *)call result:(FlutterResult)result
     [LabelDetector handleDetection:image options:options result:result];
   } else if ([@"CloudLabelDetector#detectInImage" isEqualToString:call.method]) {
     [CloudLabelDetector handleDetection:image options:options result:result];
-  } else if ([@"TextRecognizer#detectInImage" isEqualToString:call.method]) {
+  } else if ([@"TextRecognizer#processImage" isEqualToString:call.method]) {
     [TextRecognizer handleDetection:image options:options result:result];
   } else {
     result(FlutterMethodNotImplemented);
diff --git a/packages/firebase_ml_vision/ios/Classes/TextRecognizer.m b/packages/firebase_ml_vision/ios/Classes/TextRecognizer.m
index f8683b7ddbeb..588666ba069a 100644
--- a/packages/firebase_ml_vision/ios/Classes/TextRecognizer.m
+++ b/packages/firebase_ml_vision/ios/Classes/TextRecognizer.m
@@ -89,7 +89,7 @@ + (void)addData:(NSMutableDictionary *)addTo
   }
 
   [addTo addEntriesFromDictionary:@{
-    @"confidence" : confidence,
+    @"confidence" : confidence ? confidence : [NSNull null],
     @"points" : points,
     @"left" : @((int)frame.origin.x),
     @"top" : @((int)frame.origin.y),
diff --git a/packages/firebase_ml_vision/lib/firebase_ml_vision.dart b/packages/firebase_ml_vision/lib/firebase_ml_vision.dart
index 406f5b3c4180..8e228bb65229 100644
--- a/packages/firebase_ml_vision/lib/firebase_ml_vision.dart
+++ b/packages/firebase_ml_vision/lib/firebase_ml_vision.dart
@@ -15,5 +15,5 @@ part 'src/barcode_detector.dart';
 part 'src/face_detector.dart';
 part 'src/firebase_vision.dart';
 part 'src/label_detector.dart';
-part 'src/text_detector.dart';
-part 'src/vision_cloud_detector_options.dart';
+part 'src/text_recognizer.dart';
+part 'src/cloud_detector_options.dart';
diff --git a/packages/firebase_ml_vision/lib/src/cloud_detector_options.dart b/packages/firebase_ml_vision/lib/src/cloud_detector_options.dart
new file mode 100644
index 000000000000..4a4144ecd014
--- /dev/null
+++ b/packages/firebase_ml_vision/lib/src/cloud_detector_options.dart
@@ -0,0 +1,36 @@
+// Copyright 2018 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+part of firebase_ml_vision;
+
+/// Model types for cloud vision APIs.
+enum CloudModelType { stable, latest }
+
+/// Options for cloud vision detectors.
+class CloudDetectorOptions {
+  /// Constructor for [CloudDetectorOptions].
+  ///
+  /// [maxResults] must be greater than 0, otherwise AssertionError is thrown.
+  /// Default is 10.
+  ///
+  /// [modelType] has default [CloudModelType.stable].
+  const CloudDetectorOptions(
+      {this.maxResults = 10, this.modelType = CloudModelType.stable})
+      : assert(maxResults > 0),
+        assert(modelType != null);
+
+  /// The number of results to be returned.
+  ///
+  /// Defaults to 10.
+  /// Required to be greater than zero.
+  final int maxResults;
+
+  /// The type of model to use for the detection.
+  final CloudModelType modelType;
+
+  Map<String, dynamic> _toMap() => <String, dynamic>{
+        'maxResults': maxResults,
+        'modelType': _enumToString(modelType),
+      };
+}
diff --git a/packages/firebase_ml_vision/lib/src/firebase_vision.dart b/packages/firebase_ml_vision/lib/src/firebase_vision.dart
index 42e9e07ea3aa..31bd400494b4 100644
--- a/packages/firebase_ml_vision/lib/src/firebase_vision.dart
+++ b/packages/firebase_ml_vision/lib/src/firebase_vision.dart
@@ -10,7 +10,7 @@ part of firebase_ml_vision;
 /// a detector from the instance:
 ///
 /// ```dart
-/// TextDetector textDetector = FirebaseVision.instance.getTextDetector();
+/// TextRecognizer textRecognizer = FirebaseVision.instance.textRecognizer();
 /// ```
 class FirebaseVision {
   FirebaseVision._();
@@ -24,7 +24,7 @@ class FirebaseVision {
   /// Use this get an instance of a detector:
   ///
   /// ```dart
-  /// TextDetector textDetector = FirebaseVision.instance.textDetector();
+  /// TextRecognizer textRecognizer = FirebaseVision.instance.textRecognizer();
   /// ```
   static final FirebaseVision instance = FirebaseVision._();
 
@@ -43,13 +43,13 @@ class FirebaseVision {
     return LabelDetector._(options ?? const LabelDetectorOptions());
   }
 
-  /// Creates an instance of [LabelDetector].
-  CloudLabelDetector cloudLabelDetector([VisionCloudDetectorOptions options]) {
-    return CloudLabelDetector._(options ?? const VisionCloudDetectorOptions());
-  }
+  /// Creates an instance of [TextRecognizer].
+  TextRecognizer textRecognizer() => TextRecognizer._();
 
-  /// Creates an instance of [TextDetector].
-  TextDetector textDetector() => TextDetector._();
+  /// Creates an instance of [CloudLabelDetector].
+  CloudLabelDetector cloudLabelDetector([CloudDetectorOptions options]) {
+    return CloudLabelDetector._(options ?? const CloudDetectorOptions());
+  }
 }
 
 /// Represents an image object used for both on-device and cloud API detectors.
diff --git a/packages/firebase_ml_vision/lib/src/label_detector.dart b/packages/firebase_ml_vision/lib/src/label_detector.dart
index e5074ab9c932..8511724406d0 100644
--- a/packages/firebase_ml_vision/lib/src/label_detector.dart
+++ b/packages/firebase_ml_vision/lib/src/label_detector.dart
@@ -50,29 +50,38 @@ class LabelDetector extends FirebaseVisionDetector {
   }
 }
 
+/// Detector for detecting and labeling entities in an input image.
+///
+/// Uses cloud machine learning models and will require enabling Cloud API.
+///
+/// When you use the API, you get a list of the entities that were recognized:
+/// people, things, places, activities, and so on. Each label found comes with a
+/// score that indicates the confidence the ML model has in its relevance. With
+/// this information, you can perform tasks such as automatic metadata
+/// generation and content moderation.
+///
+/// A cloud label detector is created via cloudLabelDetector(CloudDetectorOptions options)
+/// in [FirebaseVision]:
+///
+/// ```dart
+/// CloudLabelDetector cloudLabelDetector = FirebaseVision.instance.cloudLabelDetector(options);
+/// ```
 class CloudLabelDetector extends FirebaseVisionDetector {
   CloudLabelDetector._(this.options) : assert(options != null);
 
-  /// The options for the detector.
-  ///
-  /// Sets the confidence threshold for detecting entities.
-  final VisionCloudDetectorOptions options;
+  /// Options used to configure this cloud detector.
+  final CloudDetectorOptions options;
 
   /// Detects entities in the input image.
   ///
   /// Performed asynchronously.
   @override
   Future<List<Label>> detectInImage(FirebaseVisionImage visionImage) async {
-    debugPrint(
-        'Options: modelType=${options.modelType}, maxResults=${options.maxResults}');
     final List<dynamic> reply = await FirebaseVision.channel.invokeMethod(
       'CloudLabelDetector#detectInImage',
       <String, dynamic>{
         'path': visionImage.imageFile.path,
-        'options': <String, dynamic>{
-          'maxResults': options.maxResults,
-          'modelType': options.modelType,
-        },
+        'options': options._toMap(),
       },
     );
 
diff --git a/packages/firebase_ml_vision/lib/src/text_detector.dart b/packages/firebase_ml_vision/lib/src/text_detector.dart
deleted file mode 100644
index 9ea90bba713c..000000000000
--- a/packages/firebase_ml_vision/lib/src/text_detector.dart
+++ /dev/null
@@ -1,119 +0,0 @@
-// Copyright 2018 The Chromium Authors. All rights reserved.
-// Use of this source code is governed by a BSD-style license that can be
-// found in the LICENSE file.
-
-part of firebase_ml_vision;
-
-/// Detector for performing optical character recognition(OCR) on an input image.
-///
-/// A text detector is created via `textDetector()` in [FirebaseVision]:
-///
-/// ```dart
-/// TextDetector textDetector = FirebaseVision.instance.textDetector();
-/// ```
-class TextDetector implements FirebaseVisionDetector {
-  TextDetector._();
-
-  /// Detects text in the input image.
-  ///
-  /// The OCR is performed asynchronously.
-  @override
-  Future<List<TextBlock>> detectInImage(FirebaseVisionImage visionImage) async {
-    final List<dynamic> reply = await FirebaseVision.channel.invokeMethod(
-      'TextDetector#detectInImage',
-      <String, dynamic>{
-        'path': visionImage.imageFile.path,
-        'options': <String, dynamic>{},
-      },
-    );
-
-    final List<TextBlock> blocks = <TextBlock>[];
-    reply.forEach((dynamic block) {
-      blocks.add(TextBlock._(block));
-    });
-
-    return blocks;
-  }
-}
-
-/// Abstract class representing dimensions of recognized text in an image.
-abstract class TextContainer {
-  TextContainer._(Map<dynamic, dynamic> data)
-      : boundingBox = data['left'] != null
-            ? Rectangle<int>(
-                data['left'],
-                data['top'],
-                data['width'],
-                data['height'],
-              )
-            : null,
-        _cornerPoints = data['points']
-            .map<Point<int>>((dynamic item) => Point<int>(
-                  item[0],
-                  item[1],
-                ))
-            .toList(),
-        text = data['text'];
-
-  final List<Point<int>> _cornerPoints;
-
-  /// Axis-aligned bounding rectangle of the detected text.
-  ///
-  /// The point (0, 0) is defined as the upper-left corner of the image.
-  ///
-  /// Could be null even if text is found.
-  final Rectangle<int> boundingBox;
-
-  /// The recognized text as a string.
-  ///
-  /// Returned in reading order for the language. For Latin, this is top to
-  /// bottom within a Block, and left-to-right within a Line.
-  final String text;
-
-  /// The four corner points in clockwise direction starting with top-left.
-  ///
-  /// Due to the possible perspective distortions, this is not necessarily a
-  /// rectangle. Parts of the region could be outside of the image.
-  ///
-  /// Could be empty even if text is found.
-  List<Point<int>> get cornerPoints => List<Point<int>>.from(_cornerPoints);
-}
-
-/// A block of text (think of it as a paragraph) as deemed by the OCR engine.
-class TextBlock extends TextContainer {
-  TextBlock._(Map<dynamic, dynamic> block)
-      : _lines = block['lines']
-            .map<TextLine>((dynamic line) => TextLine._(line))
-            .toList(),
-        super._(block);
-
-  final List<TextLine> _lines;
-
-  /// The contents of the text block, broken down into individual lines.
-  List<TextLine> get lines => List<TextLine>.from(_lines);
-}
-
-/// Represents a line of text.
-class TextLine extends TextContainer {
-  TextLine._(Map<dynamic, dynamic> line)
-      : _elements = line['elements']
-            .map<TextElement>((dynamic element) => TextElement._(element))
-            .toList(),
-        super._(line);
-
-  final List<TextElement> _elements;
-
-  /// The contents of this line, broken down into individual elements.
-  List<TextElement> get elements => List<TextElement>.from(_elements);
-}
-
-/// Roughly equivalent to a space-separated "word."
-///
-/// The API separates elements into words in most Latin languages, but could
-/// separate by characters in others.
-///
-/// If a word is split between two lines by a hyphen, each part is encoded as a
-/// separate element.
-class TextElement extends TextContainer {
-  TextElement._(Map<dynamic, dynamic> element) : super._(element);
-}
diff --git a/packages/firebase_ml_vision/lib/src/text_recognizer.dart b/packages/firebase_ml_vision/lib/src/text_recognizer.dart
new file mode 100644
index 000000000000..b65aa95fec09
--- /dev/null
+++ b/packages/firebase_ml_vision/lib/src/text_recognizer.dart
@@ -0,0 +1,154 @@
+// Copyright 2018 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+part of firebase_ml_vision;
+
+/// Detector for performing optical character recognition(OCR) on an input image.
+///
+/// A text recognizer is created via `textRecognizer()` in [FirebaseVision]:
+///
+/// ```dart
+/// TextRecognizer textRecognizer = FirebaseVision.instance.textRecognizer();
+/// ```
+class TextRecognizer implements FirebaseVisionDetector {
+  TextRecognizer._();
+
+  /// Detects [VisionText] from a [FirebaseVisionImage].
+  ///
+  /// The OCR is performed asynchronously.
+  Future<VisionText> processImage(FirebaseVisionImage visionImage) async {
+    final Map<dynamic, dynamic> reply =
+        await FirebaseVision.channel.invokeMethod(
+      'TextRecognizer#processImage',
+      <String, dynamic>{
+        'path': visionImage.imageFile.path,
+        'options': <String, dynamic>{},
+      },
+    );
+
+    return VisionText._(reply);
+  }
+
+  /// Detects [VisionText] from a [FirebaseVisionImage].
+  ///
+  /// The OCR is performed asynchronously.
+  @Deprecated('Please use `processImage`')
+  @override
+  Future<VisionText> detectInImage(FirebaseVisionImage visionImage) async {
+    return processImage(visionImage);
+  }
+}
+
+/// Recognized text in an image.
+class VisionText {
+  VisionText._(Map<dynamic, dynamic> data)
+      : text = data['text'],
+        blocks = List<TextBlock>.unmodifiable(data['blocks']
+            .map<TextBlock>((dynamic block) => TextBlock._(block)));
+
+  /// String representation of the recognized text.
+  final String text;
+
+  /// All recognized text broken down into individual blocks/paragraphs.
+  final List<TextBlock> blocks;
+}
+
+/// Detected language from text recognition.
+class RecognizedLanguage {
+  RecognizedLanguage._(dynamic data) : languageCode = data['languageCode'];
+
+  /// The BCP-47 language code, such as, en-US or sr-Latn. For more information,
+  /// see http://www.unicode.org/reports/tr35/#Unicode_locale_identifier.
+  final String languageCode;
+}
+
+/// Abstract class representing dimensions of recognized text in an image.
+abstract class TextContainer {
+  TextContainer._(Map<dynamic, dynamic> data)
+      : boundingBox = data['left'] != null
+            ? Rectangle<int>(
+                data['left'],
+                data['top'],
+                data['width'],
+                data['height'],
+              )
+            : null,
+        confidence = data['confidence'],
+        cornerPoints = List<Point<int>>.unmodifiable(
+            data['points'].map<Point<int>>((dynamic point) => Point<int>(
+                  point[0],
+                  point[1],
+                ))),
+        recognizedLanguages = List<RecognizedLanguage>.unmodifiable(
+            data['recognizedLanguages'].map<RecognizedLanguage>(
+                (dynamic language) => RecognizedLanguage._(language))),
+        text = data['text'];
+
+  /// Axis-aligned bounding rectangle of the detected text.
+  ///
+  /// The point (0, 0) is defined as the upper-left corner of the image.
+  ///
+  /// Could be null even if text is found.
+  final Rectangle<int> boundingBox;
+
+  /// The confidence of the recognized text block.
+  ///
+  /// The value is null for all text recognizers except for cloud text
+  /// recognizers.
+  final double confidence;
+
+  /// The four corner points in clockwise direction starting with top-left.
+  ///
+  /// Due to the possible perspective distortions, this is not necessarily a
+  /// rectangle. Parts of the region could be outside of the image.
+  ///
+  /// Could be empty even if text is found.
+  final List<Point<int>> cornerPoints;
+
+  /// All detected languages from recognized text.
+  ///
+  /// On-device text recognizers only detect Latin-based languages, while cloud
+  /// text recognizers can detect multiple languages. If no languages are
+  /// recognized, the list is empty.
+  final List<RecognizedLanguage> recognizedLanguages;
+
+  /// The recognized text as a string.
+  ///
+  /// Returned in reading order for the language. For Latin, this is top to
+  /// bottom within a Block, and left-to-right within a Line.
+  final String text;
+}
+
+/// A block of text (think of it as a paragraph) as deemed by the OCR engine.
+class TextBlock extends TextContainer {
+  TextBlock._(Map<dynamic, dynamic> block)
+      : lines = List<TextLine>.unmodifiable(
+            block['lines'].map<TextLine>((dynamic line) => TextLine._(line))),
+        super._(block);
+
+  /// The contents of the text block, broken down into individual lines.
+  final List<TextLine> lines;
+}
+
+/// Represents a line of text.
+class TextLine extends TextContainer {
+  TextLine._(Map<dynamic, dynamic> line)
+      : elements = List<TextElement>.unmodifiable(line['elements']
+            .map<TextElement>((dynamic element) => TextElement._(element))),
+        super._(line);
+
+  /// The contents of this line, broken down into individual elements.
+  final List<TextElement> elements;
+}
+
+/// Roughly equivalent to a space-separated "word."
+///
+/// The API separates elements into words in most Latin languages, but could
+/// separate by characters in others.
+///
+/// If a word is split between two lines by a hyphen, each part is encoded as a
+/// separate element.
+class TextElement extends TextContainer {
+  TextElement._(Map<dynamic, dynamic> element) : super._(element);
+}
diff --git a/packages/firebase_ml_vision/lib/src/vision_cloud_detector_options.dart b/packages/firebase_ml_vision/lib/src/vision_cloud_detector_options.dart
deleted file mode 100644
index b410a9081f2d..000000000000
--- a/packages/firebase_ml_vision/lib/src/vision_cloud_detector_options.dart
+++ /dev/null
@@ -1,31 +0,0 @@
-// Copyright 2018 The Chromium Authors. All rights reserved.
-// Use of this source code is governed by a BSD-style license that can be
-// found in the LICENSE file.
-
-part of firebase_ml_vision;
-
-/// Options for cloud vision detectors.
-///
-class VisionCloudDetectorOptions {
-  /// Constructor for [VisionCloudDetectorOptions].
-  ///
-  const VisionCloudDetectorOptions(
-      {this.maxResults = 10, this.modelType = modelTypeStable})
-      : assert(maxResults > 0),
-        assert(modelType == modelTypeLatest || modelType == modelTypeStable);
-
-  static const int modelTypeStable = 1;
-  static const int modelTypeLatest = 2;
-
-  /// The number of results to be returned.
-  ///
-  /// Defaults to 10.
-  /// Required to be greater than zero.
-  final int maxResults;
-
-  /// The type of model to use for the detection..
-  ///
-  /// Defaults to [modelTypeStable]
-  /// Required to be [modelTypeStable] or [modelTypeLatest].
-  final int modelType;
-}
diff --git a/packages/firebase_ml_vision/pubspec.yaml b/packages/firebase_ml_vision/pubspec.yaml
index 733097ef4ca7..89fca642908e 100644
--- a/packages/firebase_ml_vision/pubspec.yaml
+++ b/packages/firebase_ml_vision/pubspec.yaml
@@ -3,7 +3,7 @@ description: Flutter plugin for Google ML Vision for Firebase, an SDK that bring
   learning expertise to Android and iOS apps in a powerful yet easy-to-use package.
 author: Flutter Team <flutter-dev@googlegroups.com>
 homepage: https://github.com/flutter/plugins/tree/master/packages/firebase_ml_vision
-version: 0.1.2
+version: 0.2.0
 
 dependencies:
   flutter:
diff --git a/packages/firebase_ml_vision/test/firebase_ml_vision_test.dart b/packages/firebase_ml_vision/test/firebase_ml_vision_test.dart
index e520fdc44018..492abac41466 100644
--- a/packages/firebase_ml_vision/test/firebase_ml_vision_test.dart
+++ b/packages/firebase_ml_vision/test/firebase_ml_vision_test.dart
@@ -25,9 +25,9 @@ void main() {
             return returnValue;
           case 'LabelDetector#detectInImage':
             return returnValue;
-          case 'CloudLabelDetector#detectInImage':
+          case 'TextRecognizer#processImage':
             return returnValue;
-          case 'TextDetector#detectInImage':
+          case 'CloudLabelDetector#detectInImage':
             return returnValue;
           default:
             return null;
@@ -654,9 +654,10 @@ void main() {
 
         final CloudLabelDetector detector =
             FirebaseVision.instance.cloudLabelDetector(
-          const VisionCloudDetectorOptions(
-              maxResults: 5,
-              modelType: VisionCloudDetectorOptions.modelTypeLatest),
+          const CloudDetectorOptions(
+            maxResults: 5,
+            modelType: CloudModelType.latest,
+          ),
         );
 
         final FirebaseVisionImage image = FirebaseVisionImage.fromFilePath(
@@ -672,7 +673,7 @@ void main() {
               'path': 'empty',
               'options': <String, dynamic>{
                 'maxResults': 5,
-                'modelType': VisionCloudDetectorOptions.modelTypeLatest,
+                'modelType': 'latest',
               },
             },
           ),
@@ -692,7 +693,7 @@ void main() {
 
         final CloudLabelDetector detector =
             FirebaseVision.instance.cloudLabelDetector(
-          const VisionCloudDetectorOptions(),
+          const CloudDetectorOptions(),
         );
         final FirebaseVisionImage image =
             FirebaseVisionImage.fromFilePath('empty');
@@ -706,7 +707,7 @@ void main() {
               'path': 'empty',
               'options': <String, dynamic>{
                 'maxResults': 10,
-                'modelType': VisionCloudDetectorOptions.modelTypeStable,
+                'modelType': 'stable',
               },
             },
           ),
@@ -716,36 +717,89 @@ void main() {
       });
     });
 
-    group('$TextDetector', () {
-      test('detectInImage', () async {
-        final Map<dynamic, dynamic> textElement = <dynamic, dynamic>{
-          'text': 'hello',
-          'left': 1,
-          'top': 2,
-          'width': 3,
-          'height': 4,
-          'points': <dynamic>[
-            <dynamic>[5, 6],
-            <dynamic>[7, 8],
-          ],
-        };
+    group('$TextRecognizer', () {
+      final TextRecognizer recognizer =
+          FirebaseVision.instance.textRecognizer();
+      final FirebaseVisionImage image = FirebaseVisionImage.fromFilePath(
+        'empty',
+      );
 
-        final Map<dynamic, dynamic> textLine = <dynamic, dynamic>{
-          'text': 'my',
-          'left': 5,
-          'top': 6,
-          'width': 7,
-          'height': 8,
-          'points': <dynamic>[
-            <dynamic>[9, 10],
-            <dynamic>[11, 12],
-          ],
-          'elements': <dynamic>[
-            textElement,
-          ],
-        };
+      setUp(() {
+        final List<dynamic> elements = <dynamic>[
+          <dynamic, dynamic>{
+            'text': 'hello',
+            'left': 1,
+            'top': 2,
+            'width': 3,
+            'height': 4,
+            'points': <dynamic>[
+              <dynamic>[5, 6],
+              <dynamic>[7, 8],
+            ],
+            'recognizedLanguages': <dynamic>[
+              <dynamic, dynamic>{
+                'languageCode': 'ab',
+              },
+              <dynamic, dynamic>{
+                'languageCode': 'cd',
+              }
+            ],
+            'confidence': 0.1,
+          },
+          <dynamic, dynamic>{
+            'text': 'my',
+            'left': 4,
+            'top': 3,
+            'width': 2,
+            'height': 1,
+            'points': <dynamic>[
+              <dynamic>[6, 5],
+              <dynamic>[8, 7],
+            ],
+            'recognizedLanguages': <dynamic>[],
+            'confidence': 0.2,
+          },
+        ];
 
-        final List<dynamic> textBlocks = <dynamic>[
+        final List<dynamic> lines = <dynamic>[
+          <dynamic, dynamic>{
+            'text': 'friend',
+            'left': 5,
+            'top': 6,
+            'width': 7,
+            'height': 8,
+            'points': <dynamic>[
+              <dynamic>[9, 10],
+              <dynamic>[11, 12],
+            ],
+            'recognizedLanguages': <dynamic>[
+              <dynamic, dynamic>{
+                'languageCode': 'ef',
+              },
+              <dynamic, dynamic>{
+                'languageCode': 'gh',
+              }
+            ],
+            'elements': elements,
+            'confidence': 0.3,
+          },
+          <dynamic, dynamic>{
+            'text': 'how',
+            'left': 8,
+            'top': 7,
+            'width': 4,
+            'height': 5,
+            'points': <dynamic>[
+              <dynamic>[10, 9],
+              <dynamic>[12, 11],
+            ],
+            'recognizedLanguages': <dynamic>[],
+            'elements': <dynamic>[],
+            'confidence': 0.4,
+          },
+        ];
+
+        final List<dynamic> blocks = <dynamic>[
           <dynamic, dynamic>{
             'text': 'friend',
             'left': 13,
@@ -756,112 +810,155 @@ void main() {
               <dynamic>[17, 18],
               <dynamic>[19, 20],
             ],
-            'lines': <dynamic>[
-              textLine,
+            'recognizedLanguages': <dynamic>[
+              <dynamic, dynamic>{
+                'languageCode': 'ij',
+              },
+              <dynamic, dynamic>{
+                'languageCode': 'kl',
+              }
+            ],
+            'lines': lines,
+            'confidence': 0.5,
+          },
+          <dynamic, dynamic>{
+            'text': 'hello',
+            'left': 14,
+            'top': 13,
+            'width': 16,
+            'height': 15,
+            'points': <dynamic>[
+              <dynamic>[18, 17],
+              <dynamic>[20, 19],
             ],
+            'recognizedLanguages': <dynamic>[],
+            'lines': <dynamic>[],
+            'confidence': 0.6,
           },
         ];
 
-        returnValue = textBlocks;
-
-        final TextDetector detector = FirebaseVision.instance.textDetector();
-        final FirebaseVisionImage image =
-            FirebaseVisionImage.fromFilePath('empty');
-
-        final List<TextBlock> blocks = await detector.detectInImage(image);
-
-        expect(log, <Matcher>[
-          isMethodCall(
-            'TextDetector#detectInImage',
-            arguments: <String, dynamic>{
-              'path': 'empty',
-              'options': <String, dynamic>{},
-            },
-          ),
-        ]);
-
-        final TextBlock block = blocks[0];
-        expect(block.boundingBox, const Rectangle<int>(13, 14, 15, 16));
-        expect(block.text, 'friend');
-        expect(block.cornerPoints, const <Point<int>>[
-          Point<int>(17, 18),
-          Point<int>(19, 20),
-        ]);
+        final dynamic visionText = <dynamic, dynamic>{
+          'text': 'testext',
+          'blocks': blocks,
+        };
 
-        final TextLine line = block.lines[0];
-        expect(line.boundingBox, const Rectangle<int>(5, 6, 7, 8));
-        expect(line.text, 'my');
-        expect(line.cornerPoints, const <Point<int>>[
-          Point<int>(9, 10),
-          Point<int>(11, 12),
-        ]);
+        returnValue = visionText;
+      });
 
-        final TextElement element = line.elements[0];
-        expect(element.boundingBox, const Rectangle<int>(1, 2, 3, 4));
-        expect(element.text, 'hello');
-        expect(element.cornerPoints, const <Point<int>>[
-          Point<int>(5, 6),
-          Point<int>(7, 8),
-        ]);
+      group('$TextBlock', () {
+        test('processImage', () async {
+          final VisionText text = await recognizer.processImage(image);
+
+          expect(text.blocks, hasLength(2));
+
+          TextBlock block = text.blocks[0];
+          expect(block.boundingBox, const Rectangle<int>(13, 14, 15, 16));
+          expect(block.text, 'friend');
+          expect(block.cornerPoints, const <Point<int>>[
+            Point<int>(17, 18),
+            Point<int>(19, 20),
+          ]);
+          expect(block.recognizedLanguages, hasLength(2));
+          expect(block.recognizedLanguages[0].languageCode, 'ij');
+          expect(block.recognizedLanguages[1].languageCode, 'kl');
+          expect(block.confidence, 0.5);
+
+          block = text.blocks[1];
+          expect(block.boundingBox, const Rectangle<int>(14, 13, 16, 15));
+          expect(block.text, 'hello');
+          expect(block.cornerPoints, const <Point<int>>[
+            Point<int>(18, 17),
+            Point<int>(20, 19),
+          ]);
+          expect(block.confidence, 0.6);
+        });
       });
 
-      test('detectInImage no blocks', () async {
-        returnValue = <dynamic>[];
+      group('$TextLine', () {
+        test('processImage', () async {
+          final VisionText text = await recognizer.processImage(image);
+
+          TextLine line = text.blocks[0].lines[0];
+          expect(line.boundingBox, const Rectangle<int>(5, 6, 7, 8));
+          expect(line.text, 'friend');
+          expect(line.cornerPoints, const <Point<int>>[
+            Point<int>(9, 10),
+            Point<int>(11, 12),
+          ]);
+          expect(line.recognizedLanguages, hasLength(2));
+          expect(line.recognizedLanguages[0].languageCode, 'ef');
+          expect(line.recognizedLanguages[1].languageCode, 'gh');
+          expect(line.confidence, 0.3);
+
+          line = text.blocks[0].lines[1];
+          expect(line.boundingBox, const Rectangle<int>(8, 7, 4, 5));
+          expect(line.text, 'how');
+          expect(line.cornerPoints, const <Point<int>>[
+            Point<int>(10, 9),
+            Point<int>(12, 11),
+          ]);
+          expect(line.confidence, 0.4);
+        });
+      });
 
-        final TextDetector detector = FirebaseVision.instance.textDetector();
-        final FirebaseVisionImage image =
-            FirebaseVisionImage.fromFilePath('empty');
+      group('$TextElement', () {
+        test('processImage', () async {
+          final VisionText text = await recognizer.processImage(image);
+
+          TextElement element = text.blocks[0].lines[0].elements[0];
+          expect(element.boundingBox, const Rectangle<int>(1, 2, 3, 4));
+          expect(element.text, 'hello');
+          expect(element.cornerPoints, const <Point<int>>[
+            Point<int>(5, 6),
+            Point<int>(7, 8),
+          ]);
+          expect(element.recognizedLanguages, hasLength(2));
+          expect(element.recognizedLanguages[0].languageCode, 'ab');
+          expect(element.recognizedLanguages[1].languageCode, 'cd');
+          expect(element.confidence, 0.1);
+
+          element = text.blocks[0].lines[0].elements[1];
+          expect(element.boundingBox, const Rectangle<int>(4, 3, 2, 1));
+          expect(element.text, 'my');
+          expect(element.cornerPoints, const <Point<int>>[
+            Point<int>(6, 5),
+            Point<int>(8, 7),
+          ]);
+          expect(element.confidence, 0.2);
+        });
+      });
 
-        final List<TextBlock> blocks = await detector.detectInImage(image);
+      test('processImage', () async {
+        final VisionText text = await recognizer.processImage(image);
 
+        expect(text.text, 'testext');
         expect(log, <Matcher>[
           isMethodCall(
-            'TextDetector#detectInImage',
+            'TextRecognizer#processImage',
             arguments: <String, dynamic>{
               'path': 'empty',
               'options': <String, dynamic>{},
             },
           ),
         ]);
-
-        expect(blocks, isEmpty);
       });
 
-      test('detectInImage no bounding box', () async {
-        returnValue = <dynamic>[
-          <dynamic, dynamic>{
-            'text': 'potato',
-            'points': <dynamic>[
-              <dynamic>[17, 18],
-              <dynamic>[19, 20],
-            ],
-            'lines': <dynamic>[],
-          },
-        ];
-
-        final TextDetector detector = FirebaseVision.instance.textDetector();
-        final FirebaseVisionImage image =
-            FirebaseVisionImage.fromFilePath('empty');
-
-        final List<TextBlock> blocks = await detector.detectInImage(image);
-
-        expect(log, <Matcher>[
-          isMethodCall(
-            'TextDetector#detectInImage',
-            arguments: <String, dynamic>{
-              'path': 'empty',
-              'options': <String, dynamic>{},
+      test('processImage no bounding box', () async {
+        returnValue = <dynamic, dynamic>{
+          'blocks': <dynamic>[
+            <dynamic, dynamic>{
+              'text': '',
+              'points': <dynamic>[],
+              'recognizedLanguages': <dynamic>[],
+              'lines': <dynamic>[],
             },
-          ),
-        ]);
+          ],
+        };
+
+        final VisionText text = await recognizer.processImage(image);
 
-        final TextBlock block = blocks[0];
+        final TextBlock block = text.blocks[0];
         expect(block.boundingBox, null);
-        expect(block.text, 'potato');
-        expect(block.cornerPoints, const <Point<int>>[
-          Point<int>(17, 18),
-          Point<int>(19, 20),
-        ]);
       });
     });
   });