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
tensorrtx is a computer vision inference engine and model implementation library designed for graphics processor acceleration. It provides a framework for optimizing deep learning models through a GPU inference optimizer, a deep learning model converter for transforming weights from frameworks like TensorFlow and PyTorch, and a custom plugin library to implement operations not natively supported by the TensorRT API. The project distinguishes itself through a comprehensive collection of pre-defined network implementations, ranging from various YOLO versions and DETR transformers for object det
jetson-inference is a set of libraries and tools for executing optimized deep learning models on embedded GPU hardware. Its primary purpose is to enable real-time computer vision and AI inference at the edge with low latency and high throughput. The project distinguishes itself through high-performance streaming analytics and the ability to execute concurrent AI pipelines on auto-grade silicon. It provides specialized support for multi-sensor stream processing, utilizing zero-copy data transport to load camera frames directly into GPU memory. The codebase covers a broad surface of capabiliti
This repository provides the pre-trained neural network and legacy data files used by Tesseract to recognize and extract printed text from images. It serves as a multilingual training data repository and a collection of Long Short-Term Memory models designed for high-accuracy optical character recognition across various global scripts and languages. The data includes specialized models for analyzing image layouts to determine text rotation and script direction. It provides the necessary language-specific datasets and linguistic patterns required to enable Tesseract OCR engines to function. T
ddddocr is a Python library for automated image analysis, focused on extracting text and detecting objects from visual content. Its core capabilities include character recognition that can handle alphanumeric, Chinese, and special characters, as well as object detection that returns bounding box coordinates for targets within images.
Die Hauptfunktionen von sml2h3/ddddocr sind: Text Recognition, Optical Character Recognitions, Slider CAPTCHA Solvers, Object Detection, Custom Model Training, GPU-Accelerated Inference, ONNX Model Loaders, OCR REST API Servers.
Open-Source-Alternativen zu sml2h3/ddddocr sind unter anderem: paddlepaddle/paddlex — PaddleX is a PaddlePaddle-based framework for building, deploying, and fine-tuning AI model pipelines, with pre-built… wang-xinyu/tensorrtx — tensorrtx is a computer vision inference engine and model implementation library designed for graphics processor… dusty-nv/jetson-inference — jetson-inference is a set of libraries and tools for executing optimized deep learning models on embedded GPU… tesseract-ocr/tessdata — This repository provides the pre-trained neural network and legacy data files used by Tesseract to recognize and… olafenwamoses/imageai — ImageAI is a Python computer vision library providing a suite of tools for image classification, object detection, and… thtrieu/darkflow — Darkflow is an object detection framework and computer vision pipeline that provides a programmatic interface for…