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    "info": {
        "author": "Keji Li",
        "author_email": "mail@keji.li",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Programming Language :: Python :: 3"
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        "description": "TiffReader, convenience wrapper for libtiff\n===========================================\n\nWhy?\n----\n\nCompared to PIL and some other tiff related projects, this package is\nmore for scientific imaging.\n\nFeatures exposed from libtiff:\n\n1. responds to\n\n   1. pixel bit depth\n   2. number of channels\n   3. compression scheme\n\n2. sequential and random access to frames in multi-frame tiff\n3. query length of multi-frame tiff\n\nOpen\n----\n\n.. code:: python\n\n   from tiffreader import TiffReader\n   tif = TiffReader.open(\"file_path.tif\")\n\nRandom Access\n-------------\n\n.. code:: python\n\n   tif.seek(10)\n   frame = tif.read_current()  # gives a 2D numpy array\n\nis equivalent to\n\n.. code:: python\n\n   frame = tif[10]\n\nSequential Access\n-----------------\n\nexample for an average image of the 10th to 20th frames:\n\n.. code:: python\n\n   tif.seek(10)\n   result = np.zeros(tif.shape, dtype=np.uint64)\n   for frame in zip(tif, range(10)):\n       result += frame\n   result /= 10\n\nAdditionally\n------------\n\n.. code:: python\n\n   from tiffreader import save_tiff\n   array = np.array([[1, 2, 3, 4], [5, 6, 7, 8]], dtype=np.uint8)\n   save_tiff(array, \"tif_path.tif\")\n\n.. code:: python\n\n   tif.length  # length of multi-frame tiff stack\n   tif.shape   # shape of one frame\n   tiffinfo(\"tif_path.tif\", [\"width\", \"height\"])  # wraps tiffinfo to query for additional tags",
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