{
    "info": {
        "author": "Minh-Tri Pham, Viet-Dung D. Hoang, and Tat-Jen Cham",
        "author_email": "mtpham@ntu.edu.sg",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Developers",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved",
            "Operating System :: Microsoft :: Windows",
            "Operating System :: POSIX",
            "Operating System :: Unix",
            "Programming Language :: C",
            "Programming Language :: Python",
            "Topic :: Scientific/Engineering",
            "Topic :: Software Development"
        ],
        "description": "PyCV is a package of C++ and Python modules implementing various algorithms\r\nthat are useful in computer vision, and augments the capabilities of OpenCV.\r\nIn particular, PyCV provides implementations for:\r\n\r\n- Fast training and selection of Haar-like features for a weak classifier\r\n  [Pham2007b]_.  This is currently the world's fastest method for training a face\r\n  detector. It runs in just a few hours, while most existing methods run in\r\n  days or weeks.\r\n- Asymmetric Online Boosting [Pham2007a]_: a variant of AdaBoost that learns\r\n  incrementally using an asymmetric goal as the learning criterion.\r\n\r\nAdditionally, PyCV contains many useful modules for computer vision and\r\nmachine learning, specially boosting techniques, Haar-like features, and face\r\ndetection.\r\n\r\nThe package is primarily developed by Minh-Tri Pham, as part of his PhD\r\nresearch on face detection. This research is being carried out in the Centre\r\nfor Multimedia & Network Technology (CeMNet), School of Computer Engineering,\r\nNanyang Technological University, Singapore.\r\n\r\nCopyright 2007 Nanyang Technological University, Singapore.\r\n\r\n:Founding Contributors:\r\n  Minh-Tri Pham <mtpham@ntu.edu.sg> -- Primary author\r\n\r\n  Viet-Dung D. Hoang <hoan0008@ntu.edu.sg> -- Contributing author\r\n\r\n  Tat-Jen Cham <astjcham@ntu.edu.sg> -- Supervising faculty\r\n\r\n\r\nReferences\r\n----------\r\n\r\n.. [Pham2007a] Minh-Tri Pham and Tat-Jen Cham. Online Learning Asymmetric\r\n   Boosted Classifiers for Object Detection. In Proc. IEEE Computer Society\r\n   Conference on Computer Vision and Pattern Recognition (CVPR'07),\r\n   Minneapolis, MN, 2007.\r\n\r\n.. [Pham2007b] Minh-Tri Pham and Tat-Jen Cham. Fast Training and Selection of\r\n   Haar features using Statistics in Boosting-based Face Detection. In Proc.\r\n   11th IEEE International Conference on Computer Vision (ICCV'07), Rio de\r\n   Janeiro, Brazil, 2007.",
        "description_content_type": null,
        "docs_url": null,
        "download_url": "http://www.ntu.edu.sg/home5/pham0004/pycv/",
        "downloads": {
            "last_day": -1,
            "last_month": -1,
            "last_week": -1
        },
        "home_page": "http://www.ntu.edu.sg/home5/pham0004/pycv/",
        "keywords": "",
        "license": "GNU Public License version 3",
        "maintainer": "Minh-Tri Pham, Viet-Dung D. Hoang",
        "maintainer_email": "mtpham@ntu.edu.sg",
        "name": "pycv",
        "package_url": "https://pypi.org/project/pycv/",
        "platform": "Windows,Linux,Unix",
        "project_url": "https://pypi.org/project/pycv/",
        "project_urls": {
            "Download": "http://www.ntu.edu.sg/home5/pham0004/pycv/",
            "Homepage": "http://www.ntu.edu.sg/home5/pham0004/pycv/"
        },
        "release_url": "https://pypi.org/project/pycv/0.2.2/",
        "requires_dist": null,
        "requires_python": null,
        "summary": "PyCV - A Computer Vision Package for Python Incorporating Fast Training of Face Detection",
        "version": "0.2.2"
    },
    "last_serial": 47154,
    "releases": {
        "0.2.1": [],
        "0.2.2": []
    },
    "urls": []
}