This repo integrates the C++ image classification application with the NCNN inference engine, which is generated by my previous repo (https://github.com/freshtechyy/NCNN-Deployment-image-classification-example), into Android for deep learning model deployment on mobile phone.
- Ubuntu 20.04
- android-studio-2022.1.1.21-linux
- NDK
- ncnn-20230223-android-vulkan
- OpenCV-android-sdk
- CUDA 11.4
- CUDNN 8.2.4
git clone https://github.com/freshtechyy/NCNN-Android-image-classification-example.gitAndroid studio can be installed by following Android Studio installation page (https://developer.android.com/studio/install).
NDK can be installed via Android Studio by following Tools -> SDK Managers -> SDK Tools. A Settings window pops up and NDK can be installed by clicking NDK checkbox and Apply button.
- Download Android release of OpenCV from https://opencv.org/releases/;
- Extract it and move the subfolder OpenCV-android-sdk under it into app/src/main/cpp in the image classification app;
- Set OpenCV_DIR in app/src/main/cpp/CMakeLists.txt.
- Download ncnn-android-vulkan from https://github.com/Tencent/ncnn/releases, e.g. ncnn-20230223-android-vulkan.zip;
- Extract it into app/src/main/cpp;
- Set the ncnn_DIR path in app/src/main/cpp/CMakeLists.txt.
- Open Android Studio.
- In Android Sudio, perform Build->Make Project to build the project.
- Click the Run 'app' button to run the project. You will see the window below.
- Click the CLASSIFY button to get classification result.
The project structure is shown in the following figure.
The NCNN model files are placed in the asset folder, and the input image files are placed in the drawable folder.
- Android. https://developer.android.com/studio/install, 2023.
- Tencent, NVIDIA CUDA Convolutional Neural Network, https://github.com/tencent/ncnn, 2019.