add readme

example/movinet/README.md

@@ -1,16 +1,22 @@
-# movinet
+# Action Recognition Movinet
 
-A new Flutter project.
+|      | Android | iOS | Linux | Mac | Windows | Web |
+|------|---------|-----|-------|-----|---------|-----|
+| live | ✅       | ✅   |       |     |         |     |
 
-## Getting Started
+This project is a sample of how to perform action recognition using
+TensorFlow Lite in Flutter. It includes support for both Android and IOS.
 
-This project is a starting point for a Flutter application.
+## Download model and labels
 
-A few resources to get you started if this is your first Flutter project:
+To build the project, you must first download the Movinet TensorFlow Lite
+model. You can do this by access https://www.kaggle.com/models/google/movinet
+and download movinet model. After downloading the model, you must copy the model
+into the `assets` folder.
 
-- [Lab: Write your first Flutter app](https://docs.flutter.dev/get-started/codelab)
-- [Cookbook: Useful Flutter samples](https://docs.flutter.dev/cookbook)
+## About the sample
 
-For help getting started with Flutter development, view the
-[online documentation](https://docs.flutter.dev/), which offers tutorials,
-samples, guidance on mobile development, and a full API reference.
+- You can use Flutter-supported IDEs such as Android Studio or Visual Studio.
+  This project has been tested on Android Studio Flamingo.
+- Before building, ensure that you have downloaded the model and the labels by
+  following a set of instructions.

example/movinet/ios/Runner/Info.plist

@@ -26,6 +26,8 @@
 	<true/>
 	<key>UILaunchStoryboardName</key>
 	<string>LaunchScreen</string>
+	<key>NSCameraUsageDescription</key>
+    <string>Camera Permission</string>
 	<key>UIMainStoryboardFile</key>
 	<string>Main</string>
 	<key>UISupportedInterfaceOrientations</key>

example/movinet/lib/main.dart

@@ -160,7 +160,10 @@ class _MyHomePageState extends State<MyHomePage> with WidgetsBindingObserver {
   Widget build(BuildContext context) {
     return Scaffold(
       appBar: AppBar(
-        title: Center(child: Text(widget.title)),
+        title: Image.asset(
+          'assets/images/tfl_logo.png',
+          fit: BoxFit.contain,
+        ),
         backgroundColor: Colors.black.withOpacity(0.5),
       ),
       body: resultWidget(context),

example/movinet/pubspec.yaml

@@ -63,8 +63,9 @@ flutter:
 
   # To add assets to your application, add an assets section, like this:
   assets:
-    - assets/movinet_int8.tflite
+    - assets/
     - assets/label/kinetics600_label_map.txt
+    - assets/images/tfl_logo.png
 
   # An image asset can refer to one or more resolution-specific "variants", see
   # https://flutter.dev/assets-and-images/#resolution-aware

lib/src/interpreter.dart

@@ -212,10 +212,14 @@ class Interpreter {
       inputTensors.elementAt(i).setTo(inputs[i]);
     }
 
-    var inferenceStartNanos = DateTime.now().microsecondsSinceEpoch;
+    var inferenceStartNanos = DateTime
+        .now()
+        .microsecondsSinceEpoch;
     invoke();
     _lastNativeInferenceDurationMicroSeconds =
-        DateTime.now().microsecondsSinceEpoch - inferenceStartNanos;
+        DateTime
+            .now()
+            .microsecondsSinceEpoch - inferenceStartNanos;
   }
 
   /// Gets all input tensors associated with the model.
@@ -226,8 +230,9 @@ class Interpreter {
 
     var tensors = List.generate(
         tfliteBinding.TfLiteInterpreterGetInputTensorCount(_interpreter),
-        (i) => Tensor(
-            tfliteBinding.TfLiteInterpreterGetInputTensor(_interpreter, i)),
+            (i) =>
+            Tensor(
+                tfliteBinding.TfLiteInterpreterGetInputTensor(_interpreter, i)),
         growable: false);
 
     return tensors;
@@ -241,8 +246,10 @@ class Interpreter {
 
     var tensors = List.generate(
         tfliteBinding.TfLiteInterpreterGetOutputTensorCount(_interpreter),
-        (i) => Tensor(
-            tfliteBinding.TfLiteInterpreterGetOutputTensor(_interpreter, i)),
+            (i) =>
+            Tensor(
+                tfliteBinding.TfLiteInterpreterGetOutputTensor(
+                    _interpreter, i)),
         growable: false);
 
     return tensors;
@@ -253,7 +260,7 @@ class Interpreter {
     final dimensionSize = shape.length;
     final dimensions = calloc<Int>(dimensionSize);
     final externalTypedData =
-        dimensions.cast<Int32>().asTypedList(dimensionSize);
+    dimensions.cast<Int32>().asTypedList(dimensionSize);
     externalTypedData.setRange(0, dimensionSize, shape);
     final status = tfliteBinding.TfLiteInterpreterResizeInputTensor(
         _interpreter, tensorIndex, dimensions, dimensionSize);
@@ -341,7 +348,7 @@ class Interpreter {
     // check if signature key exists
     if (!_signatureRunners.containsKey(signatureKey)) {
       Pointer<Char> signatureKeyPointer =
-          signatureKey.toNativeUtf8() as Pointer<Char>;
+      signatureKey.toNativeUtf8() as Pointer<Char>;
       final signatureRunner = tfliteBinding.TfLiteInterpreterGetSignatureRunner(
           _interpreter, signatureKeyPointer);
       _signatureRunners[signatureKey] = signatureRunner;
@@ -355,23 +362,23 @@ class Interpreter {
   int getSignatureInputCount(String signatureKey) {
     final signatureRunner = _getSignatureRunner(signatureKey);
     final subGraphIndex =
-        tfliteBinding.TfLiteSignatureRunnerGetInputCount(signatureRunner);
+    tfliteBinding.TfLiteSignatureRunnerGetInputCount(signatureRunner);
     return subGraphIndex;
   }
 
   /// Get the number of outputs associated with a signature
   int getSignatureOutputCount(String signatureKey) {
     final signatureRunner = _getSignatureRunner(signatureKey);
     final subGraphIndex =
-        tfliteBinding.TfLiteSignatureRunnerGetOutputCount(signatureRunner);
+    tfliteBinding.TfLiteSignatureRunnerGetOutputCount(signatureRunner);
     return subGraphIndex;
   }
 
   /// Get input name by index and signature key.
   String getSignatureInputName(String signatureKey, int index) {
     final signatureRunner = _getSignatureRunner(signatureKey);
     final inputName =
-        tfliteBinding.TfLiteSignatureRunnerGetInputName(signatureRunner, index);
+    tfliteBinding.TfLiteSignatureRunnerGetInputName(signatureRunner, index);
     return inputName.cast<Utf8>().toDartString();
   }
 
@@ -383,8 +390,8 @@ class Interpreter {
     return outputName.cast<Utf8>().toDartString();
   }
 
-  List<int> getSignatureInputTensorShape(
-      String signatureKey, String inputName) {
+  List<int> getSignatureInputTensorShape(String signatureKey,
+      String inputName) {
     final signatureRunner = _getSignatureRunner(signatureKey);
     final inputTensor = Tensor(
         tfliteBinding.TfLiteSignatureRunnerGetInputTensor(
@@ -393,8 +400,8 @@ class Interpreter {
     return shape;
   }
 
-  List<int> getSignatureOutputTensorShape(
-      String signatureKey, String outputName) {
+  List<int> getSignatureOutputTensorShape(String signatureKey,
+      String outputName) {
     final signatureRunner = _getSignatureRunner(signatureKey);
     final outputTensor = Tensor(
         tfliteBinding.TfLiteSignatureRunnerGetOutputTensor(
@@ -403,32 +410,6 @@ class Interpreter {
     return shape;
   }
 
-  /// get signature input tensor
-  Map<String, Tensor> getSignatureInputTensors(
-      String signatureKey, List<String> keys) {
-    final signatureRunner = _getSignatureRunner(signatureKey);
-    Map<String, Tensor> tensors = HashMap();
-    keys.forEach((key) {
-      tensors[key] = Tensor(tfliteBinding.TfLiteSignatureRunnerGetInputTensor(
-          signatureRunner, key.toNativeUtf8().cast<Char>()));
-    });
-
-    return tensors;
-  }
-
-  /// get signature output tensor
-  Map<String, Tensor> getSignatureOutputTensors(
-      String signatureKey, List<String> keys) {
-    final signatureRunner = _getSignatureRunner(signatureKey);
-    Map<String, Tensor> tensors = HashMap();
-    keys.forEach((key) {
-      tensors[key] = Tensor(tfliteBinding.TfLiteSignatureRunnerGetOutputTensor(
-          signatureRunner, key.toNativeUtf8().cast<Char>()));
-    });
-
-    return tensors;
-  }
-
   /// Run for single input and output
   void runSignature(Map<String, Object> inputs, Map<String, Object> outputs,
       String signatureKey) {
@@ -440,21 +421,22 @@ class Interpreter {
     }
 
     final Pointer<TfLiteSignatureRunner> signatureRunner =
-        _getSignatureRunner(signatureKey);
-
-    var inputTensor =
-        getSignatureInputTensors(signatureKey, inputs.keys.toList());
+    _getSignatureRunner(signatureKey);
 
     inputs.forEach((key, value) {
-      inputTensor[key]?.setTo(value);
+      Tensor inputTensor = Tensor(
+          tfliteBinding.TfLiteSignatureRunnerGetInputTensor(
+              signatureRunner, key.toNativeUtf8().cast<Char>()));
+      inputTensor.setTo(value);
     });
 
     tfliteBinding.TfLiteSignatureRunnerInvoke(signatureRunner);
 
-    var outputTensor =
-        getSignatureOutputTensors(signatureKey, outputs.keys.toList());
     outputs.forEach((key, value) {
-      outputTensor[key]?.copyTo(value);
+      Tensor outputTensor = Tensor(
+          tfliteBinding.TfLiteSignatureRunnerGetOutputTensor(
+              signatureRunner, key.toNativeUtf8().cast<Char>()));
+      outputTensor.copyTo(value);
     });
   }