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Unofficial repository for [Scene Text Detection with Supervised Pyramid Context Network][https://arxiv.org/abs/1811.08605] with tensorflow. 网络实现主要借鉴Keras版本的Mask-RCNN,训练数据接口参考了argman/EAST.论文作者在知乎的文章介绍SPCNet. 训练数据放在data/下，训练数据准备在data/icdar.py：…
The main features of airbernard/scene-text-detection-with-spcnet are: 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… daybreak-u/chineseocr_lite — chineseocr_lite is a lightweight Chinese optical character recognition engine designed to detect text regions, analyze… paddlepaddle/paddlex — PaddleX is a PaddlePaddle-based framework for building, deploying, and fine-tuning AI model pipelines, with pre-built… clovaai/craft-pytorch — Official Pytorch implementation of CRAFT text detector | Paper | Pretrained Model | Supplementary. dpengwen/pcr — Our paper: Progressive Contour Regression for Arbitrary-Shape Scene Text Detection, CVPR 2021.… whai362/psenet — Official Pytorch implementations of PSENet.
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
Official Pytorch implementation of CRAFT text detector | Paper | Pretrained Model | Supplementary