https://github.com/iwatake2222/play_with_ncnn
Sample projects to use ncnn
https://github.com/iwatake2222/play_with_ncnn
cpp deeplearning ncnn
Last synced: 4 months ago
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Sample projects to use ncnn
- Host: GitHub
- URL: https://github.com/iwatake2222/play_with_ncnn
- Owner: iwatake2222
- License: apache-2.0
- Created: 2019-10-19T11:51:32.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2022-09-04T11:33:39.000Z (about 3 years ago)
- Last Synced: 2025-05-17T10:11:10.773Z (5 months ago)
- Topics: cpp, deeplearning, ncnn
- Language: C++
- Homepage:
- Size: 81.4 MB
- Stars: 7
- Watchers: 3
- Forks: 5
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Play with ncnn
- Sample projects to use ncnn in C++ for multi-platform
- Typical project structure is like the following diagram
- 
## Target
- Platform
- Linux (x64)
- Linux (armv7)
- Linux (aarch64)
- Android (aarch64)
- Windows (x64). Visual Studio 2019
- Option
- with Vulkan
- without Vulkan
## Usage
```
./main [input]
- input = blank
- use the default image file set in source code (main.cpp)
- e.g. ./main
- input = *.mp4, *.avi, *.webm
- use video file
- e.g. ./main test.mp4
- input = *.jpg, *.png, *.bmp
- use image file
- e.g. ./main test.jpg
- input = number (e.g. 0, 1, 2, ...)
- use camera
- e.g. ./main 0
```
## How to build a project
### 0. Requirements
- OpenCV 4.x
- Vulkan SDK (even if you don't use it)
- https://github.com/iwatake2222/InferenceHelper#extra-steps-ncnn
### 1. Download
- Download source code and pre-built libraries
```sh
git clone https://github.com/iwatake2222/play_with_ncnn.git
cd play_with_ncnn
git submodule update --init
sh InferenceHelper/third_party/download_prebuilt_libraries.sh
```
- Download models
```sh
sh ./download_resource.sh
```
- If you want to change pre-built library to be used, modify the following file
- `InferenceHelper/third_party/cmakes/ncnn.cmake`
### 2-a. Build in Linux
```
cd pj_ncnn_cls_mobilenet_v2 # for example
mkdir -p build && cd build
cmake ..
make
./main
```
### 2-b. Build in Windows (Visual Studio)
- Configure and Generate a new project using cmake-gui for Visual Studio 2019 64-bit
- `Where is the source code` : path-to-play_with_ncnn/pj_ncnn_cls_mobilenet_v2 (for example)
- `Where to build the binaries` : path-to-build (any)
- Open `main.sln`
- Set `main` project as a startup project, then build and run!
**Note:** Debug mode in Visual Studio doesn't work because debuggable libraries are not provided
### 2-c. Build in Android Studio
- Please refer to
- https://github.com/iwatake2222/InferenceHelper_Sample#2-d-build-in-android-studio
- Copy `resource` directory to `/storage/emulated/0/Android/data/com.iwatake.viewandroidncnn/files/Documents/resource`
- the directory will be created after running the app (so the first run should fail because model files cannot be read)
- Modify `ViewAndroid\app\src\main\cpp\CMakeLists.txt` to select a image processor you want to use
- `set(ImageProcessor_DIR "${CMAKE_CURRENT_LIST_DIR}/../../../../../pj_ncnn_cls_mobilenet_v2/image_processor")`
- replace `pj_ncnn_cls_mobilenet_v2` to another
- In case you encounter `error: use of typeid requires -frtti` error, modify `ViewAndroid\sdk\native\jni\include\opencv2\opencv_modules.hpp`
- `//#define HAVE_OPENCV_FLANN`
# License
- Copyright 2020 iwatake2222
- Licensed under the Apache License, Version 2.0
- [LICENSE](LICENSE)
# Acknowledgements
- This project utilizes OSS (Open Source Software)
- [NOTICE.md](NOTICE.md)