{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/10"}],"enrichment":{"capability":"Detects text and mathematical formulas in images using pre-trained deep learning models, supporting Chinese, English, and multiple languages with both PyTorch and ONNX backends.","skillfed_tags":["ocr-detection","document-analysis","multilingual"],"use_cases":["Locate text regions in document images before feeding them to an OCR system for full text recognition","Detect and classify mathematical formulas in scientific papers or textbooks for formula extraction pipelines","Analyze document layout to identify structural elements like titles, tables, and figures for automated document parsing","Process multilingual documents with language-specific detection models for Chinese, English, or other supported languages","Deploy lightweight text detection on edge devices using MobileNet or ShuffleNet model variants"],"what_it_does":"CnSTD is a Python package for detecting text and other document elements in images. It provides pre-trained models for scene text detection (STD), mathematical formula detection (MFD), and layout analysis, supporting Chinese, English, and multiple other languages. The package includes models trained on standard OCR datasets and external models from PaddleOCR, available in both PyTorch and ONNX formats.\n\nThe package is typically used to locate and extract bounding boxes of text regions in images before passing them to an OCR engine for character recognition. It also detects mathematical formulas (inline and isolated) and identifies document layout elements like headers, footers, tables, and figures. Models range from lightweight mobile-optimized variants to larger, more accurate versions, and can run on CPU or GPU.","worth_installing":"Yes. Active maintenance, permissive Apache 2.0 license, no known vulnerabilities, and a mature model ecosystem make this a solid choice for text detection tasks. The 20-dependency footprint is typical for ML packages. Install if you need to locate text in images before OCR or analyze document layout; skip if you only need character recognition without localization."},"id":"cnstd","links":{"html":"https://skillfed.io/packages/cnstd","md":"https://skillfed.io/packages/cnstd.md","pypi":"https://pypi.org/project/cnstd/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-05","license_spdx":null,"license_treatment":"permissive","name":"cnstd","python_support":"supports_current","summary":"Python3 package for Chinese/English Scene Text Detection (STD), Mathematical Formula Detection (MFD), and Layout Analysis, with free pretrained models"},"popularity":{"monthly_downloads":98858,"position":13055,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.2.8"}