How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.
Official Pytorch implementation of CRAFT text detector | Paper | Pretrained Model | Supplementary
The main features of clovaai/craft-pytorch are: Computer Vision Libraries, Natural Language Processing, Text Detection, Text detection.
Projects with overlapping indexed features include: zyddnys/manga-image-translator — This project is an automated image translation system and pipeline specifically optimized for manga and comics. It… paddlepaddle/paddlex — PaddleX is a PaddlePaddle-based framework for building, deploying, and fine-tuning AI model pipelines, with pre-built… daybreak-u/chineseocr_lite — chineseocr_lite is a lightweight Chinese optical character recognition engine designed to detect text regions, analyze… 7compass/sentimental — Simple sentiment analysis with Ruby. abitdodgy/gibran — Gibran is an Elixir natural language processor, and a port of WordsCounted. abadojack/whatlanggo — Natural language detection library for Go.
PaddleX is a PaddlePaddle-based framework for building, deploying, and fine-tuning AI model pipelines, with pre-built support for computer vision, OCR, document analysis, and time series tasks. It offers a toolkit of ready-to-use pipelines for image classification, object detection, segmentation, and pose estimation, alongside an end-to-end OCR document analysis pipeline that extracts text, tables, formulas, and layout information. The platform also includes a dedicated time series forecasting pipeline for analyzing historical data to detect anomalies, classify patterns, and predict future val
This project is an automated image translation system and pipeline specifically optimized for manga and comics. It provides a sequence of text detection, machine translation, and typesetting, and is available as an image translation API, a command-line tool for batch processing, and an LLM-powered translator. The system utilizes OCR to detect text regions and an inpainter to remove original content by synthesizing background pixels. Translated text is then overlaid using an automated typesetter that manages font sizes, colors, and reading directions based on the original coordinates. The wor
chineseocr_lite is a lightweight Chinese optical character recognition engine designed to detect text regions, analyze orientation, and convert Chinese characters from images into digital text. It supports both horizontal and vertical reading layouts and can be deployed as a web service for image uploads and result visualization. The system utilizes a multi-backend inference framework that supports ncnn, mnn, and tnn, allowing it to run across diverse hardware and platforms. It is specifically engineered for lightweight deployment on mobile and desktop environments through the use of small mo
