mirror of
https://github.com/Tencent/ncnn.git
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Integral
d72e9dd693
This option enables the use of the pybind11 package available in the official repositories of Linux distributions.
179 lines
3.4 KiB
Markdown
179 lines
3.4 KiB
Markdown
# ncnn
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python wrapper of ncnn with [pybind11](https://github.com/pybind/pybind11), only support python3.x now.
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Install from pip
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==================
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ncnn is available as wheel packages for macOS, Windows and Linux distributions, you can install with pip:
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```
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python -m pip install -U pip
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python -m pip install -U ncnn
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```
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# Build from source
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If you want to build ncnn with some options not as default, or just like to build everything yourself, it is not difficult to build ncnn from source.
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## Prerequisites
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**On Unix (Linux, OS X)**
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* A compiler with C++11 support
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* CMake >= 3.4
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**On Mac**
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* A compiler with C++11 support
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* CMake >= 3.4
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**On Windows**
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* Visual Studio 2015 or higher
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* CMake >= 3.4
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## Build & Install
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1. clone ncnn and init submodule.
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```bash
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cd /pathto/ncnn
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git submodule init && git submodule update
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```
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2. build and install.
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```
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python setup.py install
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```
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If you want to use a custom toolchain, you can install with the `CMAKE_TOOLCHAIN_FILE` environment variable, like this:
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```
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CMAKE_TOOLCHAIN_FILE="../../toolchains/power9le-linux-gnu-vsx.clang.toolchain.cmake" python setup.py install
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```
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if you want to enable the usage of vulkan, you can install as following:
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```
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python setup.py install --vulkan=on
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```
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> **Attention:**
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>
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> To enable Vulkan support, you must first install the Vulkan SDK.
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>
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> **For Windows or Linux Users:**
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>
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> Ensure that the `VULKAN_SDK` environment variable is set to the path of the Vulkan SDK.
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>
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> **For MacOS Users:**
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>
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> On MacOS, you will need to specify additional environment variables. For guidance on setting these variables, please refer to lines 279-286 in the following file: [ncnn/.github/workflows/release-python.yml at master · Tencent/ncnn](https://github.com/Tencent/ncnn/blob/master/.github/workflows/release-python.yml).
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## Custom-build & Install
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1. clone ncnn and init submodule.
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```bash
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cd /pathto/ncnn
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git submodule init && git submodule update
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```
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2. build.
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```bash
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mkdir build
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cd build
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cmake -DNCNN_PYTHON=ON ..
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make
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```
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To use the pybind11 package provided by your system, set the CMake variable `NCNN_SYSTEM_PYBIND11` to `ON` during the build process, like this:
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```bash
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mkdir build
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cd build
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cmake -DNCNN_PYTHON=ON -DNCNN_SYSTEM_PYBIND11=ON ..
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make
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```
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3. install
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```bash
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cd /pathto/ncnn
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pip install .
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```
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if you use conda or miniconda, you can also install as following:
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```bash
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cd /pathto/ncnn
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python3 setup.py install
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```
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## Tests
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**test**
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```bash
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cd /pathto/ncnn/python
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python3 tests/test.py
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```
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**benchmark**
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```bash
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cd /pathto/ncnn/python
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python3 tests/benchmark.py
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```
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## Numpy
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**ncnn.Mat->numpy.array, with no memory copy**
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```bash
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mat = ncnn.Mat(...)
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mat_np = np.array(mat)
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```
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**numpy.array->ncnn.Mat, with no memory copy**
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```bash
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mat_np = np.array(...)
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mat = ncnn.Mat(mat_np)
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```
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# Model Zoo
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install requirements
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```bash
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pip install -r requirements.txt
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```
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then you can import ncnn.model_zoo and get model list as follow:
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```bash
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import ncnn
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import ncnn.model_zoo as model_zoo
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print(model_zoo.get_model_list())
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```
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models now in model zoo are as list below:
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```bash
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mobilenet_yolov2
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mobilenetv2_yolov3
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yolov4_tiny
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yolov4
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yolov5s
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yolact
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mobilenet_ssd
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squeezenet_ssd
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mobilenetv2_ssdlite
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mobilenetv3_ssdlite
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squeezenet
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faster_rcnn
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peleenet_ssd
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retinaface
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rfcn
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shufflenetv2
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simplepose
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nanodet
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```
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all model in model zoo has example in ncnn/python/examples folder
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# Custom Layer
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custom layer demo is in ncnn/python/ncnn/model_zoo/yolov5.py:23
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