{ "info": { "author": "Manish Sahu", "author_email": "manish.sahu.civ13@iitbhu.ac.in", "bugtrack_url": null, "classifiers": [ "License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", "Topic :: Scientific/Engineering :: GIS", "Topic :: Utilities" ], "description": "COG\n===\n\nIntroduction\n------------\n\nIt validates the TIF and convert it into COG compliant using gdal.\nFollowing are the Use-Cases kept in mind while designing:\n\n1. Large TIF that cannot be fit into memory\n2. Reading data block by block, so can be run of even low memory server\n3. Supports Multiband TIFs\n4. 3-4 Band uint8 TIF (Orthomosaic)\n5. Building pyramids if not available (This will improve rendering\n speed)\n6. Compressing data\n7. Compressing to the same compression format as the original TIF. If\n original TIF was not compressed then LZW lossless compression is used\n to compress.\n8. Tile whole into 256x256 smaller blocks internally\n\nValidator.py\n~~~~~~~~~~~~\n\nIt will validate tiff for COG format.\n\nConverter.py\n~~~~~~~~~~~~\n\nIt has the actual converter function which converts tifs into COG format\n\nTo-Do\n-----\n\n1. Multi-core processing for faster results.\n\nHow to Run\n----------\n\n1. 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