ncnn

My platform

• ubuntu 18.04
• Intel(R) Xeon(R) Gold 6240 CPU @ 2.60GHz
• cmake 3.17.1
• opencv built from source

NOTE

Though this demo runs on x86 platform, you can also use it on mobile platforms. NCNN is better optimized on mobile platforms.

Install ncnn

1. dependencies

$ python -m pip install onnx-simplifier

2. build ncnn

Just follow the ncnn official tutoral of build-for-linux to install ncnn:

step 1: install dependencies

# apt install build-essential git libprotobuf-dev protobuf-compiler 

step 2: (optional) install vulkan

step 3: install opencv from source

step 4: build
I am using commit 9391fae741a1fb8d58cdfdc92878a5e9800f8567, and I have not tested over newer commits.

$ git clone https://github.com/Tencent/ncnn.git
$ cd ncnn
$ git submodule update --init
$ mkdir -p build
$ cmake -DCMAKE_TOOLCHAIN_FILE=../toolchains/host.gcc.toolchain.cmake ..
$ make -j
$ make install 

Convert model, build and run the demo

1. convert pytorch model to ncnn model via onnx

$ cd BiSeNet/
$ python tools/export_onnx.py --aux-mode eval --config configs/bisenetv2_city.py --weight-path /path/to/your/model.pth --outpath ./model_v2.onnx 
$ python -m onnxsim model_v2.onnx model_v2_sim.onnx
$ /path/to/ncnn/build/tools/onnx/onnx2ncnn model_v2_sim.onnx model_v2_sim.param model_v2_sim.bin
$ mkdir -p ncnn/moidels
$ mv model_v2_sim.param ncnn/models 
$ mv model_v2_sim.bin ncnn/models 

2. compile demo code

mkdir -p ncnn/build
cd ncnn/build
cmake .. -DNCNN_ROOT=/path/to/ncnn/build/install
make

3. run demo

./segment