{
    "info": {
        "author": "Jeremy Rutman",
        "author_email": "jeremy.rutman@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Topic :: Software Development :: Build Tools"
        ],
        "description": "ml support code in python\n=========================\n\n\nTypical usage\noften looks like this::\n\n    #!/usr/bin/env python\n    import ml_utils as mlu\n    mlu.imutils.resize_keep_aspect(img_arr):\n\n\nSome functions for supporting machine learning, generally and caffe-specific. Currently just a dump, ideally will clean up and add install.py, examples etc\n\ncaffe - python layers for\n-------------------------\n* image read (file or lmdb) - single / multi label, pixel level labels\n\n* on-the-fly augmentation\n\n* support for pixel-level segmentation (read mask as label, etc)\n\n* controlling and reporting acc/loss of solver with solver.step\n\nimage processing\n----------------\n\n* image augmentation - including bounding boxes and pixel level\n\n* acccuracy/precision/recall reporting for single label, multilabel , bounding box, and pixel level\n\n* utilities e.g. read from anywhere (url/db/local file/img array)\n\n* grabcut\n\nread/write various file formats\n-------------------------------\n\n* lmdb, hd5\n\n* yolo\n\n* deepfashion\n\n* tamara berg\n\n* ILSRVC\n\n* etc\n\n\ntagging tools\n-------------\n\n* multilabel\n\n* pixel level\n\n\n",
        "description_content_type": "",
        "docs_url": null,
        "download_url": "",
        "downloads": {
            "last_day": -1,
            "last_month": -1,
            "last_week": -1
        },
        "home_page": "https://github.com/jeremy-rutman/ml-support-code-in-python",
        "keywords": "neural networks support code",
        "license": "LICENSE.txt",
        "maintainer": "",
        "maintainer_email": "",
        "name": "nn-utils",
        "package_url": "https://pypi.org/project/nn-utils/",
        "platform": "",
        "project_url": "https://pypi.org/project/nn-utils/",
        "project_urls": {
            "Homepage": "https://github.com/jeremy-rutman/ml-support-code-in-python"
        },
        "release_url": "https://pypi.org/project/nn-utils/0.1.0/",
        "requires_dist": [
            "numpy (>=0.1.4)"
        ],
        "requires_python": "",
        "summary": "Useful machine-learning related stuff.",
        "version": "0.1.0"
    },
    "last_serial": 3685114,
    "releases": {
        "0.1.0": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "75b819c411889162de2c421bee5db12d",
                    "sha256": "da13f723bb3feb843999348b79fa38ceccab7d1b5076ddf46525fb9070a3070c"
                },
                "downloads": -1,
                "filename": "nn_utils-0.1.0-py2.py3-none-any.whl",
                "has_sig": false,
                "md5_digest": "75b819c411889162de2c421bee5db12d",
                "packagetype": "bdist_wheel",
                "python_version": "py2.py3",
                "requires_python": null,
                "size": 326755,
                "upload_time": "2018-03-19T19:15:00",
                "url": "https://files.pythonhosted.org/packages/dc/9d/e71db8903643a187b55310289bcd6175bbba7cae6547d9511a4334056cd2/nn_utils-0.1.0-py2.py3-none-any.whl"
            },
            {
                "comment_text": "",
                "digests": {
                    "md5": "0d1a2e468ecebcc969798f9d23bbc6fd",
                    "sha256": "b953eb4cc56971220dfe040903a6fdda64898adfb6abb561cca11c1f5a1e238a"
                },
                "downloads": -1,
                "filename": "nn_utils-0.1.0.tar.gz",
                "has_sig": false,
                "md5_digest": "0d1a2e468ecebcc969798f9d23bbc6fd",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 155160,
                "upload_time": "2018-03-19T19:15:03",
                "url": "https://files.pythonhosted.org/packages/24/c1/d2945e8c2a5edf15938225f62da3dcd0af004fef9576ab2faec1ec2c247c/nn_utils-0.1.0.tar.gz"
            }
        ]
    },
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "md5": "75b819c411889162de2c421bee5db12d",
                "sha256": "da13f723bb3feb843999348b79fa38ceccab7d1b5076ddf46525fb9070a3070c"
            },
            "downloads": -1,
            "filename": "nn_utils-0.1.0-py2.py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "75b819c411889162de2c421bee5db12d",
            "packagetype": "bdist_wheel",
            "python_version": "py2.py3",
            "requires_python": null,
            "size": 326755,
            "upload_time": "2018-03-19T19:15:00",
            "url": "https://files.pythonhosted.org/packages/dc/9d/e71db8903643a187b55310289bcd6175bbba7cae6547d9511a4334056cd2/nn_utils-0.1.0-py2.py3-none-any.whl"
        },
        {
            "comment_text": "",
            "digests": {
                "md5": "0d1a2e468ecebcc969798f9d23bbc6fd",
                "sha256": "b953eb4cc56971220dfe040903a6fdda64898adfb6abb561cca11c1f5a1e238a"
            },
            "downloads": -1,
            "filename": "nn_utils-0.1.0.tar.gz",
            "has_sig": false,
            "md5_digest": "0d1a2e468ecebcc969798f9d23bbc6fd",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": null,
            "size": 155160,
            "upload_time": "2018-03-19T19:15:03",
            "url": "https://files.pythonhosted.org/packages/24/c1/d2945e8c2a5edf15938225f62da3dcd0af004fef9576ab2faec1ec2c247c/nn_utils-0.1.0.tar.gz"
        }
    ]
}