Author: IronSublimate

Source Code: https://github.com/IronSublimate/NCNN_ObjectDetection

use Tencent's NCNN framework to run yolov4-tiny yolov5 and mobilenet-ssd
NCNN Verison : 20220420

https://github.com/Tencent/ncnn/releases

download ncnn-android-vulkan-lib.zip or build ncnn for android yourself

extract ncnn-android-vulkan-lib.zip into app/src/main/jni or change the ncnn path to yours in app/src/main/jni/CMakeLists.txt

open this project with Android Studio, build it and enjoy!

1. Write a java class extends NCNNDetector and fininsh 3 method inherited from NCNNDetector. These methods might be native methods.

   public boolean Init(AssetManager mgr);
   public NCNNDetector.Obj[] Detect(Bitmap bitmap, boolean use_gpu);
   public boolean Deinit();

2. Write *jni.cpp to define native methods above and add your cpp in CMakeLists.txt.

   add_library(
           ncnn_detector SHARED
           NCNN_detector_public_jni.cpp
           mobilenetssdncnn_jni.cpp
           yolov5ncnn_jni.cpp
           # add your cpp here
   )

   Warning If there are more than two dynamic library(.so) both linking to libncnn.a, you will get Fatal signal 6 (SIGABRT) in running fuction load_param. You must compile all *jni.cpp into one dynamic library(libncnn_detector.so).

   See also Tencent/ncnn#976

3. Add your class in MainActivity.java

   public class MainActivity extends AppCompatActivity {
       //...
       private static final HashMap<String, String> detectNetwork = new HashMap<String, String>() {{
           // class name ： method name
           //method name shows in GUI
           //class name is used to reflect
           put(MobilenetSSDNcnn.class.getName(), "MobileNet SSD");
           put(YoloV5Ncnn.class.getName(), "YOLOv5");
           put(NanoDet.class.getName(), "Nano Det");
       put(YOLOv4Tiny.class.getName(),"YOLOv4 Tiny");
       }};
       //...
   }

1. Might be crashed when first open this app
2. only ncnn version 1.0.20220420 and before is supported, other version will crash in yolox_s-int8

        yoloXInt8.load_model(mgr, "yolox_s-int8.bin");

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