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hanziart
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hanzi version of asciiart
Download README (.md)
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README.md
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hanziart
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# Hanziart Hanzi (Chinese characters) version of `asciiart`. ASCII art uses monospaced keyboard characters, originally limited to those encoded by the ASCII standard, in place of pixels to draw raster images. The intensity of a given pixel is approximated by the visual density of the ASCII character. Chinese characters, or *hanzi*, also known by their Japanese name *kanji*, present an even wider variety of characters to use for ASCII art. For an example, see `apple40.txt`. Best viewed in a text editor with line-wrapping turned off. As a proxy for their visual density, we shall use the *stroke count* of a character. Stroke count data are provided in [Unihan database](https://www.unicode.org/reports/tr38/) produced by the Unicode consortium. ## Source data You will need to download [Unihan data (zip archive)](http://www.unicode.org/Public/UCD/latest/ucd/Unihan.zip) from Unicode. The file we need is `Unihan_DictionaryLikeData.txt` within the `Unihan.zip` archive. ## Dependencies Written in Python3. Requires the following libraries: scikit-image (`skimage`), `scipy`, `matplotlib`, `numpy`, `argparse`, `csv`, `random`, `re`, `collections`. ## Usage ```bash python3 hanziart.py --image photo.jpeg python3 hanziart.py --image photo.jpeg --gradelevel 2 # Use characters up to grade level 2 python3 hanziart.py --help # Help message ``` The only required argument is the path to the image file. Assumes that `Unihan_DictionaryLikeData.txt` is in the current folder by default. Use `--help` option to see all options and their defaults. ## To do list Some ideas for future development * Measure the visual density of each character, instead of using stroke count as a proxy. * Match the visual pattern of a character to the image, e.g. characters with strong diagonal elements better approximate part of an image with diagonal texture. * Use n-grams from actual written text, to better simulate readable text.
