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        "author": "vfdev-5",
        "author_email": "vfdev.5@gmail.com",
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        "description": "[![Build Status](https://travis-ci.org/vfdev-5/ImageTilingUtils.svg?branch=master)](https://travis-ci.org/vfdev-5/ImageTilingUtils)\n[![Coverage Status](https://coveralls.io/repos/github/vfdev-5/ImageTilingUtils/badge.svg?branch=master)](https://coveralls.io/github/vfdev-5/ImageTilingUtils?branch=master)\n[![Documentation Status](https://readthedocs.org/projects/imagetilingutils/badge/?version=latest)](http://imagetilingutils.readthedocs.io/en/latest/?badge=latest)\n\n# Image Tiling Utils\nMinimalistic set of image reader agnostic tools to easily iterate over large images\n\n**Example 1**\n\nLet's iterate over a large image with overlapping tiles of the \nsame size tiles in pixels. At boundaries we add \"no-data\" pixels. \nLet's assume the data access is provided with an example function\n```python\ndef read_data(x, y, width, height, out_width=None, out_height=None):\n    out_width = width if out_width is None else out_width\n    out_height = height if out_height is None else out_height    \n    img.read(x, y, width, height, out_width, out_height)\n``` \nThus, overlapping tiles can be extracted as  \n```python\nfrom tiling import ConstStrideTiles\n\ntiles = ConstStrideTiles(image_size=(500, 500), tile_size=(256, 256), stride=(100, 100), \n                         origin=(-100, -100),\n                         scale=1.0,\n                         include_nodata=True)\n\nprint(\"Number of tiles: %i\" % len(tiles))\nfor extent, out_size in tiles:\n    x, y, width, height = extent\n    data = read_data(x, y, width, height, \n                     out_width=out_size[0], \n                     out_height=out_size[1])\n    print(\"data.shape: {}\".format(data.shape))\n\n# Access a tile:\ni = len(tiles) // 2 \nextent, out_size  = tiles[i]\n```\n\n![example 1 tiles](assets/example_const_stride_tiles.png)\n\n\n**Example 2**\n\nLet's iterate over a large image with overlapping tiles of the same size in pixels. \nIn this case we prefer to not going outside the input image and fill tiles with `nodata`.\nIn this situation, overlapping is not constant. \nLet's assume the data access is provided with an example function\n```python\ndef read_data(x, y, width, height, out_width=None, out_height=None):\n    out_width = width if out_width is None else out_width\n    out_height = height if out_height is None else out_height    \n    img.read(x, y, width, height, out_width, out_height)\n``` \nThus, overlapping tiles can be extracted as  \n```python\nfrom tiling import ConstSizeTiles\n\ntiles = ConstSizeTiles(image_size=(500, 500), tile_size=(256, 256), min_overlapping=15, scale=1.0)\n\nprint(\"Number of tiles: %i\" % len(tiles))\nfor extent in tiles:\n    x, y, width, height = extent\n    data = read_data(x, y, width, height, \n                     out_width=tiles.tile_size[0], \n                     out_height=tiles.tile_size[1])\n    print(\"data.shape: {}\".format(data.shape))\n\n# Access a tile:\ni = len(tiles) // 2 \nextent  = tiles[i]\n```\n\n![example 2 tiles](assets/example_const_size_tiles.png)\n\n\n## Installation:\n\n#### from pip\n```bash\npip install tiling\n```\n\n#### from sources\n\n```bash\npip install git+https://github.com/vfdev-5/ImageTilingUtils.git\n```\n\n## Examples \n\nFor more practical examples, see [notebooks](examples)\n\n\n",
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