{ "info": { "author": "MAP Client Developers", "author_email": "", "bugtrack_url": null, "classifiers": [ "Development Status :: 3 - Alpha", "License :: OSI Approved :: Mozilla Public License 2.0 (MPL 2.0)", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3.5", "Topic :: Scientific/Engineering :: Medical Science Apps." ], "description": "GIAS2 (Geometry Image-Analysis Statistics)\n==========================================\n\nA Python library for tools used in musculoskeletal modelling. Includes\ntools for parametric meshing, registration, image analysis, statistical\nshape modelling, and 3-D visualisation using Mayavi.\n\nDependencies\n------------\n\n- scipy\n- scikit-learn\n\nOptional dependencies\n---------------------\n\n- VTK and VTK Python bindings (for mesh processing)\n- Mayavi (for 3-D visualisation, requires Numpy, VTK, wxPython,\n configobj)\n- PyCSG (for generating constructive solids)\n- pydicom (for reading DICOM images)\n- Cython (speeds up active shape model and random forest segmentation)\n- matplotlib for some inbuilt plotting functions\n\nInstallation\n------------\n\nLinux\n~~~~~\n\n1. If you would like to use in-built visualisation modules, first\n install Mayavi for you distribution, else you can skip this step.\n\n 1. Install VTK and VTK python bindings (e.g. through your package\n manager). VTK 5.10 is the most stable in my experience with\n Mayavi.\n 2. Install mayavi through your package manager (e.g. sudo apt-get\n install mayavi2) or pip (e.g. pip install --user mayavi)\n\n2. Download the\n `wheel `__ and\n\n ::\n\n pip install --user [path/to/wheel]\n\nWindows\n~~~~~~~\n\n1. The most painless way to install the python dependencies required by\n GIAS2 is to install the umbrella package\n `Anaconda `__.\n2. If you would like to use in-built visualisation modules, install\n Mayavi. In you installed Anaconda, from the Anaconda commandline,\n\n ::\n\n conda install mayavi\n\n3. Download the wheel and from the Anaconda commandline\n\n ::\n\n pip install --user [path/to/wheel]\n\nExamples\n--------\n\nExample of some the capabilities of GIAS2 can be found in the\ngias2/examples/ directory. We are working to add more examples.\n\nTutorials\n---------\n\n- `Using GIAS2 with MAP Client for lower limb model\n generation `__\n- `Using GIAS2 for statistical shape\n modelling `__\n\nLicense\n-------\n\nGIAS2 is under the `Mozilla Public license\n2.0 `__.\n\n\n", "description_content_type": "", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://bitbucket.org/jangle/gias2", "keywords": "musculoskeletal map mapclient", "license": "mozilla", "maintainer": "", "maintainer_email": "", "name": "gias2", "package_url": "https://pypi.org/project/gias2/", "platform": "", "project_url": "https://pypi.org/project/gias2/", "project_urls": { "Homepage": "https://bitbucket.org/jangle/gias2" }, "release_url": "https://pypi.org/project/gias2/0.6.14/", "requires_dist": [ "numpy (>=1.6.1)", "scipy (>=0.9)", "scikit-learn (>=0.15)", "scikit-image (>=0.13.0)", "cython (>=0.27.0)", "matplotlib", "pydicom (==1.3.0)", "configparser" ], "requires_python": "", "summary": "A library of musculoskeletal modelling tools.", "version": "0.6.14" }, "last_serial": 5562181, "releases": { "0.6.12": [ { "comment_text": "", "digests": { "md5": "26c81ae35cc3b3bf4a2602d28dcb7870", "sha256": "a5f654b86d08743af6bb11a3ff24a132237dceb4369251d52f8ac75f6a33fbb0" }, "downloads": -1, "filename": "gias2-0.6.12-py3-none-any.whl", "has_sig": false, "md5_digest": "26c81ae35cc3b3bf4a2602d28dcb7870", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": null, "size": 22460000, "upload_time": "2019-07-10T03:59:26", "url": "https://files.pythonhosted.org/packages/cb/a2/d014aab168294171799b1ca378bde79f052ee46dc82fbc07fd0d06d506af/gias2-0.6.12-py3-none-any.whl" } ], "0.6.14": [ { "comment_text": "", "digests": { "md5": "957f511518f23c8eac00af5da71ce82f", "sha256": "043f52c80ca4e374846e4aa1be4c3aa3cf7e5a1d571cd91c5b506fe6e777d513" }, "downloads": -1, "filename": "gias2-0.6.14-py3-none-any.whl", "has_sig": false, "md5_digest": "957f511518f23c8eac00af5da71ce82f", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": null, "size": 6450782, "upload_time": "2019-07-21T04:16:48", "url": "https://files.pythonhosted.org/packages/2f/95/e1920cdfc38d1d8796c97af1de0849874152c27923c364f0eef370e05bbd/gias2-0.6.14-py3-none-any.whl" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "957f511518f23c8eac00af5da71ce82f", "sha256": "043f52c80ca4e374846e4aa1be4c3aa3cf7e5a1d571cd91c5b506fe6e777d513" }, "downloads": -1, "filename": "gias2-0.6.14-py3-none-any.whl", "has_sig": false, "md5_digest": "957f511518f23c8eac00af5da71ce82f", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": null, "size": 6450782, "upload_time": "2019-07-21T04:16:48", "url": "https://files.pythonhosted.org/packages/2f/95/e1920cdfc38d1d8796c97af1de0849874152c27923c364f0eef370e05bbd/gias2-0.6.14-py3-none-any.whl" } ] }