This is a sample ncnn yolov8 object segment android project, it depends on ncnn library and opencv.
Method 1
Method 2
Method 3
ultralytics 8.0.129
add YOLOv8 Tencent NCNN export #3529 ultralytics/ultralytics#3529
- Download ncnn-YYYYMMDD-android-vulkan.zip.
- Extract ncnn-YYYYMMDD-android-vulkan.zip into app/src/main/jni folder and change the ncnn_DIR path to yours in app/src/main/jni/CMakeLists.txt.
For example:
ncnn-20221128-android-vulkan
- Download opencv-mobile-XYZ-android.zip
- Extract opencv-mobile-XYZ-android.zip into app/src/main/jni and change the OpenCV_DIR path to yours in app/src/main/jni/CMakeLists.txt.
For example:
opencv-mobile-4.6.0-android
- Open this project with Android Studio, build it and enjoy!
- Android ndk camera is used for best efficiency.
- Crash may happen on very old devices for lacking HAL3 camera interface.
- All models are manually modified to accept dynamic input shape.
- Most small models run slower on GPU than on CPU, this is common.
- FPS may be lower in dark environment because of longer camera exposure time.