├── .gitattributes
├── windows
    ├── .npmignore
    ├── RNTensorflowLite
    │   ├── project.json
    │   ├── RNTensorflowLiteModule.cs
    │   ├── Properties
    │   │   ├── AssemblyInfo.cs
    │   │   └── RNTensorflowLite.rd.xml
    │   ├── RNTensorflowLitePackage.cs
    │   └── RNTensorflowLite.csproj
    ├── .gitignore
    └── RNTensorflowLite.sln
├── android
    ├── src
    │   └── main
    │   │   ├── AndroidManifest.xml
    │   │   └── java
    │   │       └── com
    │   │           └── rntensorflowlite
    │   │               ├── RNTensorflowLitePackage.java
    │   │               ├── Classifier.java
    │   │               ├── RNTFLiteImageRecognizerModule.java
    │   │               └── TFLiteImageRecognizer.java
    └── build.gradle
├── ios
    ├── RNTensorflowLite.m
    ├── RNTensorflowLite.h
    ├── RNTensorflowLite.xcworkspace
    │   └── contents.xcworkspacedata
    ├── RNTensorflowLite.podspec
    └── RNTensorflowLite.xcodeproj
    │   └── project.pbxproj
├── package.json
├── .gitignore
├── index.js
└── README.md


/.gitattributes:
--------------------------------------------------------------------------------
1 | *.pbxproj -text


--------------------------------------------------------------------------------
/windows/.npmignore:
--------------------------------------------------------------------------------
 1 | 
 2 | # Make sure we don't publish build artifacts to NPM
 3 | ARM/
 4 | Debug/
 5 | x64/
 6 | x86/
 7 | bin/
 8 | obj/
 9 | .vs/
10 | 


--------------------------------------------------------------------------------
/android/src/main/AndroidManifest.xml:
--------------------------------------------------------------------------------
1 | 
2 | <manifest xmlns:android="http://schemas.android.com/apk/res/android"
3 |           package="com.rntensorflowlite">
4 | 
5 | </manifest>
6 |   


--------------------------------------------------------------------------------
/ios/RNTensorflowLite.m:
--------------------------------------------------------------------------------
 1 | 
 2 | #import "RNTensorflowLite.h"
 3 | 
 4 | @implementation RNTensorflowLite
 5 | 
 6 | - (dispatch_queue_t)methodQueue
 7 | {
 8 |     return dispatch_get_main_queue();
 9 | }
10 | RCT_EXPORT_MODULE()
11 | 
12 | @end
13 |   


--------------------------------------------------------------------------------
/ios/RNTensorflowLite.h:
--------------------------------------------------------------------------------
 1 | 
 2 | #if __has_include("RCTBridgeModule.h")
 3 | #import "RCTBridgeModule.h"
 4 | #else
 5 | #import <React/RCTBridgeModule.h>
 6 | #endif
 7 | 
 8 | @interface RNTensorflowLite : NSObject <RCTBridgeModule>
 9 | 
10 | @end
11 |   


--------------------------------------------------------------------------------
/ios/RNTensorflowLite.xcworkspace/contents.xcworkspacedata:
--------------------------------------------------------------------------------
1 | // !$*UTF8*$!
2 | <?xml version="1.0" encoding="UTF-8"?>
3 | <Workspace
4 |    version = "1.0">
5 |    <FileRef
6 |       location = "group:RNTensorflowLite.xcodeproj">
7 |    </FileRef>
8 | </Workspace>
9 |   


--------------------------------------------------------------------------------
/windows/RNTensorflowLite/project.json:
--------------------------------------------------------------------------------
 1 | {
 2 |   "dependencies": {
 3 |     "Microsoft.NETCore.UniversalWindowsPlatform": "5.2.2"
 4 |   },
 5 |   "frameworks": {
 6 |     "uap10.0": {}
 7 |   },
 8 |   "runtimes": {
 9 |     "win10-arm": {},
10 |     "win10-arm-aot": {},
11 |     "win10-x86": {},
12 |     "win10-x86-aot": {},
13 |     "win10-x64": {},
14 |     "win10-x64-aot": {}
15 |   }
16 | }
17 | 


--------------------------------------------------------------------------------
/package.json:
--------------------------------------------------------------------------------
 1 | {
 2 |   "name": "react-native-tensorflow-lite",
 3 |   "version": "1.0.5",
 4 |   "description": "A react native library for running Tensorflow Lite on Android",
 5 |   "main": "index.js",
 6 |   "scripts": {
 7 |     "test": "echo \"Error: no test specified\" && exit 1"
 8 |   },
 9 |   "keywords": [
10 |     "react-native",
11 |     "tensorflow lite",
12 |     "tensorflow"
13 |   ],
14 |   "author": "",
15 |   "license": "",
16 |   "peerDependencies": {
17 |     "react-native": "^0.41.2",
18 |     "react-native-windows": "0.41.0-rc.1"
19 |   }
20 | }
21 | 


--------------------------------------------------------------------------------
/.gitignore:
--------------------------------------------------------------------------------
 1 | 
 2 | # OSX
 3 | #
 4 | .DS_Store
 5 | 
 6 | # node.js
 7 | #
 8 | node_modules/
 9 | npm-debug.log
10 | yarn-error.log
11 |   
12 | 
13 | # Xcode
14 | #
15 | build/
16 | *.pbxuser
17 | !default.pbxuser
18 | *.mode1v3
19 | !default.mode1v3
20 | *.mode2v3
21 | !default.mode2v3
22 | *.perspectivev3
23 | !default.perspectivev3
24 | xcuserdata
25 | *.xccheckout
26 | *.moved-aside
27 | DerivedData
28 | *.hmap
29 | *.ipa
30 | *.xcuserstate
31 | project.xcworkspace
32 |       
33 | 
34 | # Android/IntelliJ
35 | #
36 | build/
37 | .idea
38 | .gradle
39 | local.properties
40 | *.iml
41 | 
42 | # BUCK
43 | buck-out/
44 | \.buckd/
45 | *.keystore
46 |       


--------------------------------------------------------------------------------
/android/build.gradle:
--------------------------------------------------------------------------------
 1 | 
 2 | buildscript {
 3 |     repositories {
 4 |         jcenter()
 5 |     }
 6 | 
 7 |     dependencies {
 8 |         classpath 'com.android.tools.build:gradle:2.2.3'
 9 |     }
10 | }
11 | 
12 | apply plugin: 'com.android.library'
13 | 
14 | android {
15 |     compileSdkVersion 23
16 |     buildToolsVersion "23.0.1"
17 | 
18 |     defaultConfig {
19 |         minSdkVersion 16
20 |         targetSdkVersion 23
21 |         versionCode 1
22 |         versionName "1.0"
23 |     }
24 |     lintOptions {
25 |         abortOnError false
26 |     }
27 | 	
28 | }
29 | 
30 | repositories {
31 |     mavenCentral()
32 | }
33 | 
34 | dependencies {
35 |     compile 'com.facebook.react:react-native:+'
36 | 	compile 'org.tensorflow:tensorflow-lite:+'
37 | }
38 |   


--------------------------------------------------------------------------------
/ios/RNTensorflowLite.podspec:
--------------------------------------------------------------------------------
 1 | 
 2 | Pod::Spec.new do |s|
 3 |   s.name         = "RNTensorflowLite"
 4 |   s.version      = "1.0.0"
 5 |   s.summary      = "RNTensorflowLite"
 6 |   s.description  = <<-DESC
 7 |                   RNTensorflowLite
 8 |                    DESC
 9 |   s.homepage     = ""
10 |   s.license      = "MIT"
11 |   # s.license      = { :type => "MIT", :file => "FILE_LICENSE" }
12 |   s.author             = { "author" => "author@domain.cn" }
13 |   s.platform     = :ios, "7.0"
14 |   s.source       = { :git => "https://github.com/author/RNTensorflowLite.git", :tag => "master" }
15 |   s.source_files  = "RNTensorflowLite/**/*.{h,m}"
16 |   s.requires_arc = true
17 | 
18 | 
19 |   s.dependency "React"
20 |   #s.dependency "others"
21 | 
22 | end
23 | 
24 |   


--------------------------------------------------------------------------------
/windows/RNTensorflowLite/RNTensorflowLiteModule.cs:
--------------------------------------------------------------------------------
 1 | using ReactNative.Bridge;
 2 | using System;
 3 | using System.Collections.Generic;
 4 | using Windows.ApplicationModel.Core;
 5 | using Windows.UI.Core;
 6 | 
 7 | namespace Tensorflow.Lite.RNTensorflowLite
 8 | {
 9 |     /// <summary>
10 |     /// A module that allows JS to share data.
11 |     /// </summary>
12 |     class RNTensorflowLiteModule : NativeModuleBase
13 |     {
14 |         /// <summary>
15 |         /// Instantiates the <see cref="RNTensorflowLiteModule"/>.
16 |         /// </summary>
17 |         internal RNTensorflowLiteModule()
18 |         {
19 | 
20 |         }
21 | 
22 |         /// <summary>
23 |         /// The name of the native module.
24 |         /// </summary>
25 |         public override string Name
26 |         {
27 |             get
28 |             {
29 |                 return "RNTensorflowLite";
30 |             }
31 |         }
32 |     }
33 | }
34 | 


--------------------------------------------------------------------------------
/index.js:
--------------------------------------------------------------------------------
 1 | import { NativeModules, Image } from 'react-native';
 2 | 
 3 | const { RNTFLiteImageRecognition } = NativeModules;
 4 | 
 5 | class TFLiteImageRecognition {
 6 | 	constructor(data) {
 7 | 		data['model'] = Image.resolveAssetSource(data['model']) != null
 8 | 		  ? Image.resolveAssetSource(data['model']).uri
 9 | 		  : data['model']
10 | 
11 | 		data['labels'] = Image.resolveAssetSource(data['labels']) != null
12 | 		  ? Image.resolveAssetSource(data['labels']).uri
13 | 		  : data['labels']  
14 | 		
15 | 		this.state = RNTFLiteImageRecognition.createImageRecognizer(data);
16 | 	}
17 | 	
18 | 	async recognize(data) {
19 | 		await this.state;
20 | 		
21 | 		data['image'] = Image.resolveAssetSource(data['image']) != null
22 | 		  ? Image.resolveAssetSource(data['image']).uri
23 | 		  : data['image']
24 | 		  
25 | 		return RNTFLiteImageRecognition.recognize(data);
26 | 	}
27 | 	
28 | 	async close() {
29 | 		await this.state;
30 | 		
31 | 		RNTFLiteImageRecognition.close();
32 | 	}
33 | 	
34 | }
35 | 
36 | export { TFLiteImageRecognition };
37 | 


--------------------------------------------------------------------------------
/windows/.gitignore:
--------------------------------------------------------------------------------
 1 | *AppPackages*
 2 | *BundleArtifacts*
 3 | *ReactAssets*
 4 | 
 5 | #OS junk files
 6 | [Tt]humbs.db
 7 | *.DS_Store
 8 | 
 9 | #Visual Studio files
10 | *.[Oo]bj
11 | *.user
12 | *.aps
13 | *.pch
14 | *.vspscc
15 | *.vssscc
16 | *_i.c
17 | *_p.c
18 | *.ncb
19 | *.suo
20 | *.tlb
21 | *.tlh
22 | *.bak
23 | *.[Cc]ache
24 | *.ilk
25 | *.log
26 | *.lib
27 | *.sbr
28 | *.sdf
29 | *.opensdf
30 | *.opendb
31 | *.unsuccessfulbuild
32 | ipch/
33 | [Oo]bj/
34 | [Bb]in
35 | [Dd]ebug*/
36 | [Rr]elease*/
37 | Ankh.NoLoad
38 | 
39 | #MonoDevelop
40 | *.pidb
41 | *.userprefs
42 | 
43 | #Tooling
44 | _ReSharper*/
45 | *.resharper
46 | [Tt]est[Rr]esult*
47 | *.sass-cache
48 | 
49 | #Project files
50 | [Bb]uild/
51 | 
52 | #Subversion files
53 | .svn
54 | 
55 | # Office Temp Files
56 | ~$*
57 | 
58 | # vim Temp Files
59 | *~
60 | 
61 | #NuGet
62 | packages/
63 | *.nupkg
64 | 
65 | #ncrunch
66 | *ncrunch*
67 | *crunch*.local.xml
68 | 
69 | # visual studio database projects
70 | *.dbmdl
71 | 
72 | #Test files
73 | *.testsettings
74 | 
75 | #Other files
76 | *.DotSettings
77 | .vs/
78 | *project.lock.json
79 | 


--------------------------------------------------------------------------------
/windows/RNTensorflowLite/Properties/AssemblyInfo.cs:
--------------------------------------------------------------------------------
 1 | using System.Reflection;
 2 | using System.Runtime.CompilerServices;
 3 | using System.Runtime.InteropServices;
 4 | 
 5 | // General Information about an assembly is controlled through the following
 6 | // set of attributes. Change these attribute values to modify the information
 7 | // associated with an assembly.
 8 | [assembly: AssemblyTitle("RNTensorflowLite")]
 9 | [assembly: AssemblyDescription("")]
10 | [assembly: AssemblyConfiguration("")]
11 | [assembly: AssemblyCompany("")]
12 | [assembly: AssemblyProduct("RNTensorflowLite")]
13 | [assembly: AssemblyCopyright("Copyright ©  2016")]
14 | [assembly: AssemblyTrademark("")]
15 | [assembly: AssemblyCulture("")]
16 | 
17 | // Version information for an assembly consists of the following four values:
18 | //
19 | //      Major Version
20 | //      Minor Version
21 | //      Build Number
22 | //      Revision
23 | //
24 | // You can specify all the values or you can default the Build and Revision Numbers
25 | // by using the '*' as shown below:
26 | // [assembly: AssemblyVersion("1.0.*")]
27 | [assembly: AssemblyVersion("1.0.0.0")]
28 | [assembly: AssemblyFileVersion("1.0.0.0")]
29 | [assembly: ComVisible(false)]
30 |   


--------------------------------------------------------------------------------
/android/src/main/java/com/rntensorflowlite/RNTensorflowLitePackage.java:
--------------------------------------------------------------------------------
 1 | package com.rntensorflowlite;
 2 | 
 3 | import java.util.Arrays;
 4 | import java.util.Collections;
 5 | import java.util.List;
 6 | 
 7 | import com.facebook.react.ReactPackage;
 8 | import com.facebook.react.bridge.NativeModule;
 9 | import com.facebook.react.bridge.ReactApplicationContext;
10 | import com.facebook.react.uimanager.ViewManager;
11 | import com.facebook.react.bridge.JavaScriptModule;
12 | import com.rntensorflowlite.imagerecognition.RNTFLiteImageRecognizerModule;
13 | 
14 | public class RNTensorflowLitePackage implements ReactPackage {
15 |     @Override
16 |     public List < NativeModule > createNativeModules(ReactApplicationContext reactContext) {
17 |         return Arrays. < NativeModule > asList(
18 |             new RNTFLiteImageRecognizerModule(reactContext)
19 |         );
20 |     }
21 | 
22 |     // Deprecated from RN 0.47
23 |     public List < Class << ? extends JavaScriptModule >> createJSModules() {
24 |         return Collections.emptyList();
25 |     }
26 | 
27 |     @Override
28 |     public List < ViewManager > createViewManagers(ReactApplicationContext reactContext) {
29 |         return Collections.emptyList();
30 |     }
31 | }
32 | 


--------------------------------------------------------------------------------
/windows/RNTensorflowLite/Properties/RNTensorflowLite.rd.xml:
--------------------------------------------------------------------------------
 1 | <?xml version="1.0" encoding="utf-8"?>
 2 | <!--
 3 |     This file contains Runtime Directives, specifications about types your application accesses
 4 |     through reflection and other dynamic code patterns. Runtime Directives are used to control the
 5 |     .NET Native optimizer and ensure that it does not remove code accessed by your library. If your
 6 |     library does not do any reflection, then you generally do not need to edit this file. However,
 7 |     if your library reflects over types, especially types passed to it or derived from its types,
 8 |     then you should write Runtime Directives.
 9 |     The most common use of reflection in libraries is to discover information about types passed
10 |     to the library. Runtime Directives have three ways to express requirements on types passed to
11 |     your library.
12 |     1.  Parameter, GenericParameter, TypeParameter, TypeEnumerableParameter
13 |         Use these directives to reflect over types passed as a parameter.
14 |     2.  SubTypes
15 |         Use a SubTypes directive to reflect over types derived from another type.
16 |     3.  AttributeImplies
17 |         Use an AttributeImplies directive to indicate that your library needs to reflect over
18 |         types or methods decorated with an attribute.
19 |     For more information on writing Runtime Directives for libraries, please visit
20 |     http://go.microsoft.com/fwlink/?LinkID=391919
21 | -->
22 | <Directives xmlns="http://schemas.microsoft.com/netfx/2013/01/metadata">
23 |   <Library Name="RNTensorflowLite">
24 | 
25 |   	<!-- add directives for your library here -->
26 | 
27 |   </Library>
28 | </Directives>
29 | 


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/android/src/main/java/com/rntensorflowlite/Classifier.java:
--------------------------------------------------------------------------------
 1 | package com.rntensorflowlite;
 2 | 
 3 | import android.graphics.Bitmap;
 4 | 
 5 | import com.facebook.react.bridge.*;
 6 | import java.util.*;
 7 | 
 8 | /**
 9 |  * Created by amitshekhar on 17/03/18.
10 |  */
11 | 
12 | public interface Classifier {
13 | 
14 |     class Recognition {
15 |         /**
16 |          * A unique identifier for what has been recognized. Specific to the class, not the instance of
17 |          * the object.
18 |          */
19 |         private final String id;
20 | 
21 |         /**
22 |          * Display name for the recognition.
23 |          */
24 |         private final String title;
25 | 
26 |         /**
27 |          * A sortable score for how good the recognition is relative to others. Higher should be better.
28 |          */
29 |         private final Float confidence;
30 | 
31 |         public Recognition(
32 |                 final String id, final String title, final Float confidence) {
33 |             this.id = id;
34 |             this.title = title;
35 |             this.confidence = confidence;
36 |         }
37 | 
38 |         public String getId() {
39 |             return id;
40 |         }
41 | 
42 |         public String getTitle() {
43 |             return title;
44 |         }
45 | 
46 |         public Float getConfidence() {
47 |             return confidence;
48 |         }
49 | 
50 |         @Override
51 |         public String toString() {
52 |             String resultString = "";
53 |             if (id != null) {
54 |                 resultString += "[" + id + "] ";
55 |             }
56 | 
57 |             if (title != null) {
58 |                 resultString += title + " ";
59 |             }
60 | 
61 |             if (confidence != null) {
62 |                 resultString += String.format("(%.1f%%) ", confidence * 100.0f);
63 |             }
64 | 
65 |             return resultString.trim();
66 |         }
67 |     }
68 | 
69 | 
70 |     WritableArray recognizeImage(String image, Integer inputShape);
71 | 
72 |     void close();
73 | }


--------------------------------------------------------------------------------
/windows/RNTensorflowLite/RNTensorflowLitePackage.cs:
--------------------------------------------------------------------------------
 1 | using ReactNative.Bridge;
 2 | using ReactNative.Modules.Core;
 3 | using ReactNative.UIManager;
 4 | using System;
 5 | using System.Collections.Generic;
 6 | 
 7 | namespace Tensorflow.Lite.RNTensorflowLite
 8 | {
 9 |     /// <summary>
10 |     /// Package defining core framework modules (e.g., <see cref="UIManagerModule"/>).
11 |     /// It should be used for modules that require special integration with
12 |     /// other framework parts (e.g., with the list of packages to load view
13 |     /// managers from).
14 |     /// </summary>
15 |     public class RNTensorflowLitePackage : IReactPackage
16 |     {
17 |         /// <summary>
18 |         /// Creates the list of native modules to register with the react
19 |         /// instance.
20 |         /// </summary>
21 |         /// <param name="reactContext">The react application context.</param>
22 |         /// <returns>The list of native modules.</returns>
23 |         public IReadOnlyList<INativeModule> CreateNativeModules(ReactContext reactContext)
24 |         {
25 |             return new List<INativeModule>
26 |             {
27 |                 new RNTensorflowLiteModule(),
28 |             };
29 |         }
30 | 
31 |         /// <summary>
32 |         /// Creates the list of JavaScript modules to register with the
33 |         /// react instance.
34 |         /// </summary>
35 |         /// <returns>The list of JavaScript modules.</returns>
36 |         public IReadOnlyList<Type> CreateJavaScriptModulesConfig()
37 |         {
38 |             return new List<Type>(0);
39 |         }
40 | 
41 |         /// <summary>
42 |         /// Creates the list of view managers that should be registered with
43 |         /// the <see cref="UIManagerModule"/>.
44 |         /// </summary>
45 |         /// <param name="reactContext">The react application context.</param>
46 |         /// <returns>The list of view managers.</returns>
47 |         public IReadOnlyList<IViewManager> CreateViewManagers(
48 |             ReactContext reactContext)
49 |         {
50 |             return new List<IViewManager>(0);
51 |         }
52 |     }
53 | }
54 | 


--------------------------------------------------------------------------------
/android/src/main/java/com/rntensorflowlite/RNTFLiteImageRecognizerModule.java:
--------------------------------------------------------------------------------
 1 | package com.rntensorflowlite.imagerecognition;
 2 | 
 3 | import com.facebook.react.bridge.*;
 4 | 
 5 | import java.util.HashMap;
 6 | import java.util.Map;
 7 | import java.util.List;
 8 | 
 9 | 
10 | public class RNTFLiteImageRecognizerModule extends ReactContextBaseJavaModule {
11 | 
12 |     private Map < Integer, TFLiteImageRecognizer > imageRecognizers = new HashMap < > ();
13 |     private final ReactApplicationContext reactContext;
14 | 
15 |     public RNTFLiteImageRecognizerModule(ReactApplicationContext reactContext) {
16 |         super(reactContext);
17 |         this.reactContext = reactContext;
18 |     }
19 | 
20 |     @Override
21 |     public String getName() {
22 |         return "RNTFLiteImageRecognition";
23 |     }
24 | 
25 |     @ReactMethod
26 |     public void createImageRecognizer(ReadableMap data, Promise promise) {
27 |         try {
28 |             String modelPath = data.getString("model");
29 |             String labelPath = data.getString("labels");
30 | 
31 |             TFLiteImageRecognizer ImageRecognizer = TFLiteImageRecognizer.create(this.reactContext, modelPath, labelPath);
32 |             imageRecognizers.put(1, ImageRecognizer);
33 |             promise.resolve(true);
34 |         } catch (Exception e) {
35 |             promise.reject(e);
36 |         }
37 |     }
38 | 
39 |     @ReactMethod
40 |     public void recognize(ReadableMap data, Promise promise) {
41 |         try {
42 |             String image = data.getString("image");
43 |             Integer inputShape = data.hasKey("inputShape") ? data.getInt("inputShape") : 224;
44 | 
45 |             TFLiteImageRecognizer ImageRecognizer = imageRecognizers.get(1);
46 |             WritableArray result = ImageRecognizer.recognizeImage(image, inputShape);
47 |             promise.resolve(result);
48 |         } catch (Exception e) {
49 |             promise.reject(e);
50 |         }
51 |     }
52 | 
53 |     @ReactMethod
54 |     public void close(Promise promise) {
55 |         try {
56 |             imageRecognizers.remove(1);
57 |             promise.resolve(true);
58 |         } catch (Exception e) {
59 |             promise.reject(e);
60 |         }
61 |     }
62 | }
63 | 


--------------------------------------------------------------------------------
/README.md:
--------------------------------------------------------------------------------
  1 | 
  2 | # react-native-tensorflow-lite
  3 | 
  4 | A react native library for running Tensorflow Lite Image Recognition on Android app.
  5 | 
  6 | 
  7 | ## Installing
  8 | 
  9 | `$ npm install react-native-tensorflow-lite --save`
 10 | 
 11 | ### Linking
 12 | 
 13 | `$ react-native link react-native-tensorflow-lite`
 14 | 
 15 | ### Converting your model to tflite format
 16 | 
 17 | `Follow this guide: https://www.tensorflow.org/lite/convert/cmdline_examples`
 18 | 
 19 | ### Android
 20 | 
 21 |   - Open up `android/app/src/main/java/[...]/MainActivity.java`
 22 |   - Add `import com.reactlibrary.RNTensorflowLitePackage;` to the imports at the top of the file
 23 |   - Add `new RNTensorflowLitePackage()` to the list returned by the `getPackages()` method
 24 |   - Add the following lines to your app's build.gradle(`android/app/build.gradle`):
 25 |   	```
 26 |   	android {
 27 | 		aaptOptions {
 28 | 		   noCompress 'tflite'
 29 | 		   noCompress 'lite'
 30 | 		}
 31 | 	}
 32 |   	```
 33 | 
 34 | ## Usage
 35 | Place your tflite model file and labels.txt in your app's asset folder. 
 36 | 
 37 | ```javascript
 38 | import {TFLiteImageRecognition} from 'react-native-tensorflow-lite';
 39 | 
 40 | class MyImageClassifier extends Component {
 41 | 
 42 |   constructor() {
 43 |     super()
 44 |     this.state = {}
 45 | 
 46 |     try {
 47 | 	// Initialize Tensorflow Lite Image Recognizer
 48 |         this.classifier = new TFLiteImageRecognition({
 49 |         model: "mymodel.tflite",  // Your tflite model in assets folder.
 50 |         labels: "label.txt" // Your label file
 51 |       })
 52 | 
 53 |     } catch(err) {
 54 |       alert(err)
 55 |     }
 56 |   }
 57 | 
 58 |   componentWillMount() {
 59 | 	this.classifyImage("apple.jpg") // Your image path.
 60 |   }
 61 |   
 62 |   async classifyImage(imagePath) {
 63 | 	try {
 64 |       const results = await this.classifier.recognize({
 65 |         image: imagePath, // Your image path.
 66 |         inputShape: 224, // the input shape of your model. If none given, it will be default to 224.
 67 |       })
 68 | 
 69 |       const resultObj = {
 70 | 	name: "Name: " + results[0].name,  
 71 | 	confidence: "Confidence: " + results[0].confidence, 
 72 | 	inference: "Inference: " + results[0].inference + "ms"
 73 |       };
 74 |       this.setState(resultObj)
 75 | 		
 76 |     } catch(err) {
 77 |       alert(err)
 78 |     }   
 79 |   }
 80 |   
 81 |   componentWillUnmount() {
 82 |     this.classifier.close() // Must close the classifier when destroying or unmounting component to release object.
 83 |   }
 84 | 
 85 |   render() {
 86 |     return (
 87 |       <View style={styles.container}>
 88 |         <View>
 89 |           <Text style={styles.results}>
 90 |             {this.state.name}
 91 |           </Text>
 92 |           <Text style={styles.results}>
 93 |             {this.state.confidence}
 94 |           </Text>
 95 |           <Text style={styles.results}>
 96 |             {this.state.inference}
 97 |           </Text>
 98 |         </View>
 99 |       </View>
100 |     );
101 |   }
102 | }
103 | ```
104 | 
105 | ### Things to note
106 | 
107 | - Sometimes, when using the float model the tensorflow lite inference is slower than using the ordinary tensorflow mobile as discussed in this issue https://github.com/tensorflow/tensorflow/issues/21787
108 | 
109 | 


--------------------------------------------------------------------------------
/windows/RNTensorflowLite.sln:
--------------------------------------------------------------------------------
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/windows/RNTensorflowLite/RNTensorflowLite.csproj:
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--------------------------------------------------------------------------------
/android/src/main/java/com/rntensorflowlite/TFLiteImageRecognizer.java:
--------------------------------------------------------------------------------
  1 | package com.rntensorflowlite.imagerecognition;
  2 | 
  3 | import com.facebook.react.bridge.*;
  4 | import com.rntensorflowlite.Classifier;
  5 | 
  6 | import android.annotation.SuppressLint;
  7 | import android.content.res.AssetFileDescriptor;
  8 | import android.content.res.AssetManager;
  9 | import android.graphics.Bitmap;
 10 | import android.graphics.BitmapFactory;
 11 | import android.graphics.Canvas;
 12 | import android.graphics.Matrix;
 13 | 
 14 | import org.tensorflow.lite.Interpreter;
 15 | 
 16 | import java.io.InputStream;
 17 | import java.io.BufferedReader;
 18 | import java.io.FileInputStream;
 19 | import java.io.IOException;
 20 | import java.io.InputStreamReader;
 21 | import java.nio.ByteBuffer;
 22 | import java.nio.ByteOrder;
 23 | import java.nio.MappedByteBuffer;
 24 | import java.nio.channels.FileChannel;
 25 | import java.lang.System;
 26 | import java.util.*;
 27 | 
 28 | public class TFLiteImageRecognizer implements Classifier {
 29 | 
 30 |     private TFLiteImageRecognizer ImageRecognizer;
 31 |     private ReactContext reactContext;
 32 | 
 33 |     private static final int MAX_RESULTS = 3;
 34 |     private static final int BATCH_SIZE = 1;
 35 |     private static final int PIXEL_SIZE = 3;
 36 |     private static final float THRESHOLD = 0.1f;
 37 | 
 38 |     long initialTime;
 39 |     long finalTime;
 40 | 
 41 |     private Interpreter classifier;
 42 |     private int inputShape;
 43 |     private List<String> labelList;
 44 | 
 45 | 
 46 |     public TFLiteImageRecognizer() {}
 47 | 
 48 |     public static TFLiteImageRecognizer create(ReactContext reactContext, String modelPath, String labelPath) throws IOException {
 49 |         TFLiteImageRecognizer imageRecognizer = new TFLiteImageRecognizer();
 50 |         imageRecognizer.reactContext = reactContext;
 51 |         imageRecognizer.classifier = new Interpreter(imageRecognizer.loadModelFile(reactContext.getAssets(), modelPath));
 52 |         imageRecognizer.labelList = imageRecognizer.loadLabelList(reactContext.getAssets(), labelPath);
 53 | 
 54 |         return imageRecognizer;
 55 |     }
 56 | 
 57 |     private MappedByteBuffer loadModelFile(AssetManager assetManager, String modelPath) throws IOException {
 58 |         AssetFileDescriptor fileDescriptor = assetManager.openFd(modelPath);
 59 |         FileInputStream inputStream = new FileInputStream(fileDescriptor.getFileDescriptor());
 60 |         FileChannel fileChannel = inputStream.getChannel();
 61 |         long startOffset = fileDescriptor.getStartOffset();
 62 |         long declaredLength = fileDescriptor.getDeclaredLength();
 63 |         return fileChannel.map(FileChannel.MapMode.READ_ONLY, startOffset, declaredLength);
 64 |     }
 65 | 
 66 |     @Override
 67 |     public WritableArray recognizeImage(final String image, final Integer inputShape) {
 68 |         this.inputShape = inputShape;
 69 | 
 70 |         Bitmap bitmap = convertToBitmap(loadResource(image));
 71 |         ByteBuffer byteBuffer = convertBitmapToByteBuffer(bitmap);
 72 |         float[][] result = new float[1][labelList.size()];
 73 |         initialTime = System.currentTimeMillis();
 74 |         classifier.run(byteBuffer, result);
 75 |         finalTime = System.currentTimeMillis() - initialTime;
 76 |         return getSortedResult(result);
 77 |     }
 78 | 
 79 |     public Boolean hasFilePrefix(String resource) {
 80 |         if (resource.startsWith("file://")) {
 81 |             return true;
 82 |         }
 83 |         return false;
 84 |     }
 85 | 
 86 |     private byte[] loadResource(String resource) {
 87 |         try {
 88 |             InputStream inputStream = this.reactContext.getAssets().open(hasFilePrefix(resource) ? resource.substring(7) : resource);
 89 |             return inputStreamToByteArray(inputStream);
 90 |         } catch (Exception e) {
 91 |             try {
 92 |                 InputStream inputStream = new FileInputStream(hasFilePrefix(resource) ? resource.substring(7) : resource);
 93 |                 return inputStreamToByteArray(inputStream);
 94 |             } catch (Exception e2) {
 95 |                 return null;
 96 |             }
 97 |         }
 98 | 
 99 |     }
100 | 
101 |     private byte[] inputStreamToByteArray(InputStream inputStream) throws IOException {
102 |         try {
103 |             byte[] b = new byte[inputStream.available()];
104 |             inputStream.read(b);
105 |             return b;
106 |         } catch (Exception e) {
107 |             return null;
108 |         }
109 |     }
110 | 
111 |     private Bitmap convertToBitmap(byte[] image) {
112 |         BitmapFactory.Options options = new BitmapFactory.Options();
113 |         options.inPreferredConfig = Bitmap.Config.ARGB_8888;
114 |         return BitmapFactory.decodeByteArray(image, 0, image.length);
115 |     }
116 | 
117 |     private ByteBuffer convertBitmapToByteBuffer(Bitmap bitmapRaw) {
118 |         ByteBuffer byteBuffer = ByteBuffer.allocateDirect(BATCH_SIZE * this.inputShape * this.inputShape * PIXEL_SIZE * 4);
119 |         byteBuffer.order(ByteOrder.nativeOrder());
120 |         int[] intValues = new int[this.inputShape * this.inputShape];
121 | 
122 |         Bitmap scaledBitmap = Bitmap.createBitmap(this.inputShape, this.inputShape, Bitmap.Config.ARGB_8888);
123 |         Matrix matrix = createMatrix(bitmapRaw.getWidth(), bitmapRaw.getHeight(), this.inputShape, this.inputShape);
124 |         final Canvas canvas = new Canvas(scaledBitmap);
125 |         canvas.drawBitmap(bitmapRaw, matrix, null);
126 |         scaledBitmap.getPixels(intValues, 0, scaledBitmap.getWidth(), 0, 0, scaledBitmap.getWidth(), scaledBitmap.getHeight());
127 |         int pixel = 0;
128 |         for (int i = 0; i < this.inputShape; ++i) {
129 |             for (int j = 0; j < this.inputShape; ++j) {
130 |                 final int val = intValues[pixel++];
131 |                 byteBuffer.putFloat(((val >> 16) & 0xFF) / 255.0f);
132 |                 byteBuffer.putFloat(((val >> 8) & 0xFF) / 255.0f);
133 |                 byteBuffer.putFloat((val & 0xFF) / 255.0f);
134 |             }
135 |         }
136 |         return byteBuffer;
137 | 
138 |     }
139 | 
140 | 
141 |     private List<String> loadLabelList(AssetManager assetManager, String labelPath) throws IOException {
142 |         List<String> labelList = new ArrayList<>();
143 |         BufferedReader reader = new BufferedReader(new InputStreamReader(assetManager.open(labelPath)));
144 |         String line;
145 |         while ((line = reader.readLine()) != null) {
146 |             labelList.add(line);
147 |         }
148 |         reader.close();
149 |         return labelList;
150 |     }
151 | 
152 |     @SuppressLint("DefaultLocale")
153 |     private WritableArray getSortedResult(float[][] labelProbArray) {
154 | 
155 |         List<WritableMap> results = new ArrayList<>();
156 | 
157 |         for (int i = 0; i < labelList.size(); ++i) {
158 |             float confidence = (labelProbArray[0][i] * 100) / 127.0 f;
159 |             if (confidence > THRESHOLD) {
160 |                 WritableMap entry = new WritableNativeMap();
161 |                 entry.putString("id", String.valueOf(i));
162 |                 entry.putString("name", labelList.size() > i ? labelList.get(i) : "unknown");
163 |                 entry.putDouble("confidence", confidence);
164 |                 entry.putString("inference", String.valueOf(finalTime));
165 |                 results.add(entry);
166 |             }
167 |         }
168 | 
169 |         Collections.sort(results, new Comparator <ReadableMap>() {
170 |             @Override
171 |             public int compare(ReadableMap first, ReadableMap second) {
172 |                 return Double.compare(second.getDouble("confidence"), first.getDouble("confidence"));
173 |             }
174 |         });
175 | 
176 |         WritableArray recognitions = new WritableNativeArray();
177 |         int recognitionsSize = Math.min(results.size(), MAX_RESULTS);
178 |         for (int i = 0; i < recognitionsSize; ++i) {
179 |             recognitions.pushMap(results.get(i));
180 |         }
181 | 
182 |         return recognitions;
183 |     }
184 | 
185 |     private Matrix createMatrix(int srcWidth, int srcHeight, int dstWidth, int dstHeight) {
186 |         Matrix matrix = new Matrix();
187 | 
188 |         if (srcWidth != dstWidth || srcHeight != dstHeight) {
189 |             float scaleFactorX = dstWidth / (float) srcWidth;
190 |             float scaleFactorY = dstHeight / (float) srcHeight;
191 |             float scaleFactor = Math.max(scaleFactorX, scaleFactorY);
192 |             matrix.postScale(scaleFactor, scaleFactor);
193 |         }
194 | 
195 |         matrix.invert(new Matrix());
196 |         return matrix;
197 |     }
198 | 
199 | 
200 |     @Override
201 |     public void close() {
202 |         this.classifier.close();
203 |         this.classifier = null;
204 |     }
205 | }
206 | 


--------------------------------------------------------------------------------
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260 | 


--------------------------------------------------------------------------------