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Project description
darknetpy is a simple binding for darknet’s yolo detector.
Installation
pip install darknetpy
Advanced options
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}]
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