App detect and Classifier using Yolov3 on Android

## TOOL - OpenCV 3.4.3 - Android Studio - Tensorflow 1.13.1 (Should using correctly version) - DW2TF-1.1 or DW2TF-1.2 (Don't using DW2TF-1.0) - Yolov3 Tiny ## MAIN ### 1. Convert Yolov3-tiny model of darknet to darkflow - clone DW2TF-1.2 (in last release) from here [DW2TF-1.2](https://github.com/jinyu121/DW2TF/releases/tag/v1.2) Problem with DW2TF-1.0 (Yolov3, Yolov3-tiny,... be affected). What is problem? [Problem](jinyu121/DW2TF#30) - Download (or train) Yolov3 tiny model and config file in darknet (.cfg and .weight). - Launch DW2TF conversion as mentioned on the github ```python3 python3 main.py \ --cfg 'data/yolov3-tiny.cfg' \ --weights 'data/yolov3-tiny.weights' \ --output 'data/' \ --prefix 'yolov3-tiny/' \ --gpu 0 ``` - Conver Darkflow to tensorflow for android. Launch freeze_graph to have a single bp graph file: ```python3 freeze_graph \ --input_graph yolov3-tiny.pb \ --input_checkpoint yolov3-tiny.ckpt \ --input_binary=true \ --output_graph=ultimate_yolov3-tiny.bp \ --output_node_names="yolov3-tiny/convolutional10/BiasAdd, yolov3-tiny/convolutional13/BiasAdd" ``` - Note: For older version of Yolo you can use darkflow tool [Order](https://github.com/thtrieu/darkflow),Load: ```python3 ./flow --model ../data/yolov2-tiny.cfg --load ../data/yolov2-tiny.weights --savepb ``` You can download [Yolo](https://pjreddie.com/darknet/yolo/) at offical page

2. Java code in android

Add package nesscessary

build.gradle(Module: App)

.....
repositories {
    maven {
        url 'https://google.bintray.com/tensorflow'
    }
}
dependencies {
    implementation fileTree(dir: "libs", include: ["*.jar"])
    implementation 'androidx.appcompat:appcompat:1.2.0'
    implementation 'androidx.constraintlayout:constraintlayout:2.0.4'
    testImplementation 'junit:junit:4.12'
    androidTestImplementation 'androidx.test.ext:junit:1.1.2'
    androidTestImplementation 'androidx.test.espresso:espresso-core:3.3.0'
    //implementation 'com.android.support:appcompat-v7:27.1.1'
    implementation 'com.android.support.constraint:constraint-layout:1.1.3'
    testImplementation 'junit:junit:4.12'
    androidTestImplementation 'com.android.support.test:runner:1.0.2'
    androidTestImplementation 'com.android.support.test.espresso:espresso-core:3.0.2'
//    androidTestImplementation 'androidx.test.espresso:espresso-core:3.1.1'
//    androidTestImplementation 'androidx.test:runner:1.1.1'
    androidTestImplementation 'androidx.test:rules:1.1.1'
    implementation 'org.tensorflow:tensorflow-android:1.13.1'
    implementation 'org.apache.commons:commons-lang3:3.0'
    implementation project(':openCVLibrary343')
}

settings.gradle( Project setting)

include ':app'
rootProject.name = "TinyYolo"
include ':openCVLibrary343'

Open some manefests necessary

 <uses-permission android:name="android.permission.WRITE_EXTERNAL_STORAGE"/>
    <uses-permission android:name="android.permission.READ_EXTERNAL_STORAGE"/>
    <uses-permission android:name="android.permission.CAMERA"/>
    <uses-feature android:name="android.hardware.camera" android:required="false"/>
    <uses-feature android:name="android.hardware.camera.autofocus" android:required="false"/>
    <uses-feature android:name="android.hardware.camera.front" android:required="false"/>
    <uses-feature android:name="android.hardware.camera.front.autofocus" android:required="false"/>

RecognizeImage using tensorflow in Java

Training model

- Main processing

- Main Algorithm

- Android Async Task

### 3. Result - App identifies and classifies correctly, but lacks

ndtands / yolotinyapp Goto Github PK

yolotinyapp's Introduction

App detect and Classifier using Yolov3 on Android

2. Java code in android

Add package nesscessary

Open some manefests necessary

RecognizeImage using tensorflow in Java

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