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    "info": {
        "author": "Daniel Gatis Carrazzoni",
        "author_email": "danielgatis@gmail.com",
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        "description": "=========\nDarknetpy\n=========\n\ndarknetpy is a simple binding for darknet's yolo detector.\n\n.. image:: https://raw.githubusercontent.com/danielgatis/darknetpy/master/example/example.png\n\nInstallation\n============\n\n::\n\n    pip install darknetpy\n\nAdvanced options\n--------------------\n::\n\n    GPU=1 pip install darknetpy\n\nto build with CUDA to accelerate by using GPU (CUDA should be in /use/local/cuda).\n\n::\n\n    CUDNN=1 pip install darknetpy\n\nto build with cuDNN to accelerate training by using GPU (cuDNN should be in /usr/local/cudnn).\n\n::\n\n    OPENCV=1 pip install darknetpy\n\nto build with OpenCV.\n\n::\n\n    OPENMP=1 pip install darknetpy\n\nto build with OpenMP support to accelerate Yolo by using multi-core CPU.\n\nUsage\n====================\n\nIn example.py::\n\n    from darknetpy.detector import Detector\n\n    detector = Detector('<absolute-path-to>/darknet/cfg/coco.data',\n                        '<absolute-path-to>/darknet/cfg/yolo.cfg',\n                        '<absolute-path-to>/darknet/yolo.weights')\n\n    results = detector.detect('<absolute-path-to>/darknet/data/dog.jpg')\n\n    print(results)\n\nRuning::\n\n    python example.py\n\n\nResult::\n\n    [{'right': 194, 'bottom': 353, 'top': 264, 'class': 'dog', 'prob': 0.8198755383491516, 'left': 71}]",
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