OpenCC (Open Chinese Convert) is a deterministic, dictionary-based Chinese text conversion library and CLI tool that converts between Simplified Chinese, Traditional Chinese, and regional variants (Taiwan, Hong Kong, Japan), including experimental Small Seal Script (Unicode 18.0). It is used in production by input method engines (RIME, fcitx), dictionary tools (GoldenDict), and NLP pipelines for text normalization and preprocessing. The core is a C++ library with a plugin-based segmentation system (built-in mmseg, optional jieba). Conversion is config-driven via JSON files that define normalization, segmentation, and a chain of dictionary groups with match policies (short_circuit, union). Dictionaries are compiled from text files into binary formats (marisa-trie .ocd2, legacy .ocd). The library exposes C, C++, Python (pybind11), and Node.js (N-API) APIs. A CLI tool provides conversion, inspection, ambiguity detection, and dictionary management. Data flows: text input is segmented, then each segment is looked up in a chain of dictionaries (character, phrase, regional variants). The first match is used (short_circuit) or all matches are unioned. The result is reassembled. The system supports streaming conversion with bounded memory via chunked processing. External dependencies include marisa-trie, darts-clone, rapidjson, pybind11, Google Test, and Google Benchmark; optional jieba (C++ fork) for segmentation plugin.
This repository is a curated collection of traditional Chinese patterns organized as structured open data. It contains 100 high-resolution pattern images accompanied by detailed metadata (in JSON format) and Chinese-language description pages. The data is organized into six thematic categories (Flora, Fauna & Beasts, Geometric, Cloud-Water-Stone, Auspicious Objects, Characters & Composite) and aggregated into machine-readable JSON and CSV formats. Each pattern includes standardized metadata fields for identification, categorization, semantic description, and visual characteristics, along with cryptographic hashes for verification. The project serves as a cultural heritage resource for designers, researchers, and educators interested in traditional Chinese decorative arts.