Merge pull request #87 from CaptainDario/feature-macos_support

[Desktop] MacOS support

.gitignore

@@ -70,4 +70,12 @@ website/build
 
 npm-debug.log*
 yarn-debug.log*
-yarn-error.log*
+yarn-error.log*
+
+# desktop binaries
+**/blobs/*
+!**/blobs/.gitkeep
+
+# models
+example/object_detection_ssd_mobilenet/assets/models/labelmap.txt
+example/object_detection_ssd_mobilenet/assets/models/ssd_mobilenet.tflite

.metadata

@@ -0,0 +1,36 @@
+# This file tracks properties of this Flutter project.
+# Used by Flutter tool to assess capabilities and perform upgrades etc.
+#
+# This file should be version controlled.
+
+version:
+  revision: 9cd3d0d9ff05768afa249e036acc66e8abe93bff
+  channel: stable
+
+project_type: plugin
+
+# Tracks metadata for the flutter migrate command
+migration:
+  platforms:
+    - platform: root
+      create_revision: 9cd3d0d9ff05768afa249e036acc66e8abe93bff
+      base_revision: 9cd3d0d9ff05768afa249e036acc66e8abe93bff
+    - platform: android
+      create_revision: 9cd3d0d9ff05768afa249e036acc66e8abe93bff
+      base_revision: 9cd3d0d9ff05768afa249e036acc66e8abe93bff
+    - platform: ios
+      create_revision: 9cd3d0d9ff05768afa249e036acc66e8abe93bff
+      base_revision: 9cd3d0d9ff05768afa249e036acc66e8abe93bff
+    - platform: macos
+      create_revision: 9cd3d0d9ff05768afa249e036acc66e8abe93bff
+      base_revision: 9cd3d0d9ff05768afa249e036acc66e8abe93bff
+
+  # User provided section
+
+  # List of Local paths (relative to this file) that should be
+  # ignored by the migrate tool.
+  #
+  # Files that are not part of the templates will be ignored by default.
+  unmanaged_files:
+    - 'lib/main.dart'
+    - 'ios/Runner.xcodeproj/project.pbxproj'

README.md

@@ -72,6 +72,21 @@ When creating a release archive (IPA), the symbols are stripped by Xcode, so the
 1. In Xcode, go to **Target Runner > Build Settings > Strip Style**
 2. Change from **All Symbols** to **Non-Global Symbols**
 
+### MacOS
+
+For MacOS a TensorFlow Lite dynamic library needs to be added to the project manually.
+For this, first a `.dylib` needs to be built. You can follow the [Bazel build guide](https://www.tensorflow.org/lite/guide/build_arm) or the [CMake build guide](https://www.tensorflow.org/lite/guide/build_cmake) to build the libraries.
+
+**CMake Note:**
+
+- cross compiling in CMake can be achieved using:
+`-DCMAKE_OSX_ARCHITECTURES=x86_64|arm64`
+
+- bundling two architectures (arm / x86) using lipo:
+`lipo -create arm64/libtensorflowlite_c.dylib x86/libtensorflowlite_c.dylib -output libtensorflowlite_c.dylib`
+
+As a second step, the library needs to be added to your application's XCode project. For this, you can follow the step 1 and 2 of the [official Flutter guide on adding dynamic libraries](https://docs.flutter.dev/platform-integration/macos/c-interop#compiled-dynamic-library-macos).
+
 ## TFLite Flutter Helper Library
 
 The helper library has been deprecated. New development underway for a replacement at https://github.com/google/flutter-mediapipe. Current timeline is to have wide support by the end of August, 2023.

android/src/main/kotlin/org/tensorflow/tflite_flutter/TfliteFlutterPlugin.kt

@@ -0,0 +1,35 @@
+package org.tensorflow.tflite_flutter
+
+import androidx.annotation.NonNull
+
+import io.flutter.embedding.engine.plugins.FlutterPlugin
+import io.flutter.plugin.common.MethodCall
+import io.flutter.plugin.common.MethodChannel
+import io.flutter.plugin.common.MethodChannel.MethodCallHandler
+import io.flutter.plugin.common.MethodChannel.Result
+
+/** TfliteFlutterPlugin */
+class TfliteFlutterPlugin: FlutterPlugin, MethodCallHandler {
+  /// The MethodChannel that will the communication between Flutter and native Android
+  ///
+  /// This local reference serves to register the plugin with the Flutter Engine and unregister it
+  /// when the Flutter Engine is detached from the Activity
+  private lateinit var channel : MethodChannel
+
+  override fun onAttachedToEngine(@NonNull flutterPluginBinding: FlutterPlugin.FlutterPluginBinding) {
+    channel = MethodChannel(flutterPluginBinding.binaryMessenger, "tflite_flutter")
+    channel.setMethodCallHandler(this)
+  }
+
+  override fun onMethodCall(@NonNull call: MethodCall, @NonNull result: Result) {
+    if (call.method == "getPlatformVersion") {
+      result.success("Android ${android.os.Build.VERSION.RELEASE}")
+    } else {
+      result.notImplemented()
+    }
+  }
+
+  override fun onDetachedFromEngine(@NonNull binding: FlutterPlugin.FlutterPluginBinding) {
+    channel.setMethodCallHandler(null)
+  }
+}

android/src/test/kotlin/org/tensorflow/tflite_flutter/TfliteFlutterPluginTest.kt

@@ -0,0 +1,27 @@
+package org.tensorflow.tflite_flutter
+
+import io.flutter.plugin.common.MethodCall
+import io.flutter.plugin.common.MethodChannel
+import kotlin.test.Test
+import org.mockito.Mockito
+
+/*
+ * This demonstrates a simple unit test of the Kotlin portion of this plugin's implementation.
+ *
+ * Once you have built the plugin's example app, you can run these tests from the command
+ * line by running `./gradlew testDebugUnitTest` in the `example/android/` directory, or
+ * you can run them directly from IDEs that support JUnit such as Android Studio.
+ */
+
+internal class TfliteFlutterPluginTest {
+  @Test
+  fun onMethodCall_getPlatformVersion_returnsExpectedValue() {
+    val plugin = TfliteFlutterPlugin()
+
+    val call = MethodCall("getPlatformVersion", null)
+    val mockResult: MethodChannel.Result = Mockito.mock(MethodChannel.Result::class.java)
+    plugin.onMethodCall(call, mockResult)
+
+    Mockito.verify(mockResult).success("Android " + android.os.Build.VERSION.RELEASE)
+  }
+}

example/audio_classification/.metadata

@@ -4,7 +4,7 @@
 # This file should be version controlled.
 
 version:
-  revision: 796c8ef79279f9c774545b3771238c3098dbefab
+  revision: f468f3366c26a5092eb964a230ce7892fda8f2f8
   channel: stable
 
 project_type: app
@@ -13,14 +13,11 @@ project_type: app
 migration:
   platforms:
     - platform: root
-      create_revision: 796c8ef79279f9c774545b3771238c3098dbefab
-      base_revision: 796c8ef79279f9c774545b3771238c3098dbefab
-    - platform: android
-      create_revision: 796c8ef79279f9c774545b3771238c3098dbefab
-      base_revision: 796c8ef79279f9c774545b3771238c3098dbefab
-    - platform: ios
-      create_revision: 796c8ef79279f9c774545b3771238c3098dbefab
-      base_revision: 796c8ef79279f9c774545b3771238c3098dbefab
+      create_revision: f468f3366c26a5092eb964a230ce7892fda8f2f8
+      base_revision: f468f3366c26a5092eb964a230ce7892fda8f2f8
+    - platform: macos
+      create_revision: f468f3366c26a5092eb964a230ce7892fda8f2f8
+      base_revision: f468f3366c26a5092eb964a230ce7892fda8f2f8
 
   # User provided section
 

example/audio_classification/README.md

@@ -1,5 +1,9 @@
 # Audio classification Yamnet
 
+|      | Android | iOS | Linux | Mac | Windows | Web |
+|------|---------|-----|-------|-----|---------|-----|
+| live | ✅       | ✅   |       |    |         |     |
+
 This project is a sample of how to perform Audio Classification using
 TensorFlow Lite in Flutter. It includes support for both Android and IOS.
 
@@ -16,7 +20,7 @@ running `sh ./scripts/download_model.sh` from the root folder of the repository.
 - Before building, ensure that you have downloaded the model and the labels by
   following a set of instructions.
 
-#### Screenshot
+## Screenshots
 
 ![Android](screenshots/android_screenshot.png)