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Darknetpy is a simple binding for darknet’s yolo (v4) detector.


Install it from pypi

curl -sSf | sh
rustup default nightly
pip install darknetpy

Install a pre-built binary

pip install

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.



from darknetpy.detector import Detector

detector = Detector('<absolute-path-to>/darknet/cfg/',

results = detector.detect('<absolute-path-to>/darknet/data/dog.jpg')





[{'right': 194, 'bottom': 353, 'top': 264, 'class': 'dog', 'prob': 0.8198755383491516, 'left': 71}]


On the project root directory

docker pull hoshizora/manylinux1-clang_x86_64
docker run --rm -v `pwd`:/io hoshizora/manylinux1-clang_x86_64 /io/

Project details

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darknetpy-4.2.tar.gz (10.0 kB view hashes)

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