darknetpy
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darknetpy is a simple binding for darknet's yolo detector.
========= Darknetpy
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Darknetpy is a simple binding for darknet's yolo (v4) detector.
.. image:: https://raw.githubusercontent.com/danielgatis/darknetpy/master/example/example.png
Installation
Install it from pypi
::
curl https://sh.rustup.rs -sSf | sh
::
rustup default nightly
::
pip install darknetpy
Install a pre-built binary
::
pip install https://github.com/danielgatis/darknetpy/raw/master/dist/darknetpy-4.2-cp37-cp37m-linux_x86_64.whl
Advanced options (only for pypi installation)
::
GPU=1 pip install darknetpy
to build with CUDA to accelerate by using GPU (CUDA should be in /use/local/cuda).
::
CUDNN=1 pip install darknetpy
to build with cuDNN to accelerate training by using GPU (cuDNN should be in /usr/local/cudnn).
::
OPENCV=1 pip install darknetpy
to build with OpenCV.
::
OPENMP=1 pip install darknetpy
to build with OpenMP support to accelerate Yolo by using multi-core CPU.
Usage
In example.py::
from darknetpy.detector import Detector
detector = Detector('<absolute-path-to>/darknet/cfg/coco.data',
'<absolute-path-to>/darknet/cfg/yolo.cfg',
'<absolute-path-to>/darknet/yolo.weights')
results = detector.detect('<absolute-path-to>/darknet/data/dog.jpg')
print(results)
Runing::
python example.py
Result::
[{'right': 194, 'bottom': 353, 'top': 264, 'class': 'dog', 'prob': 0.8198755383491516, 'left': 71}]
Build
On the project root directory
::
docker run --rm -v `pwd`:/io quay.io/pypa/manylinux2010_x86_64 /io/build-wheels.sh
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