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It's very common that many tilesets are unorganized and contains unrecognaizable names. With TileParser you can take one tile (for example screenshot from web) and find whitch tileset contains that tile.\nTo parse large amount of files TilesetParser uses AI (openCV)\n\n---\n\n## Instalation\n\n```\npip install TilesetParser\n```\n\n## How to use?\n\n```\ntilesetparser /path/to/source/image.bmp /path/to/folder_with_tilesets\n```\n\nAfter parsing every file, preview window will appear. You can browse tilesets that program found similar to the source tile.\n\nProgram takes a few arguments:\n\n## Algorithms\n\nBy default TilesetParser calculates historgrams for input tile and every tile in tileset. You can use SSIM algorithm, whitch gives far more accurate results, but takes a bit more time.\n\n### positional arguments:\n\n- source_image_path\n  \u003e Path to single source tile you need to find\n- tiles_folder\n  \u003e Path to tileset folder you want to parse\n\n### options:\n\n- -h, --help\n  \u003e Show help message and exit\n- -s, --size\n  \u003e Size of a tile (default: 32)\n- -q, --similarity\n  \u003e Similarity level for openCV (default: 0.8)\n- -e, --extension\n  \u003e Extension of the files (default: bmp)\n- -t, --tiles_per_tileset\n  \u003e How many tiles are in single tileset (default: 12)\n- -d, --ssim_algorithm\n  \u003e Use SSIM algorithm (default: false)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkernel-sqz%2Ftilesetparser","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkernel-sqz%2Ftilesetparser","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkernel-sqz%2Ftilesetparser/lists"}