Search Results for "batch ocr"
Sort By:
Showing 10 open source projects for "batch ocr"
View related business solutions-
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
-
Veeam Data Platform v13.1Try Veeam Data Platform today. Experience the unified platform that's secure by design, portable by default, and proven to recover clean, fast, and anywhere.
-
1
Umi-OCR
OCR software, free and offline
...The software supports flexible usage patterns including screenshot capture OCR, batch processing of large sets of images or documents, PDF parsing, QR code detection, and layout-aware paragraph output. Users can interact with Umi-OCR through a graphical interface, command-line options, or HTTP interfaces, making it adaptable to both casual desktop usage and programmatic automation. Because the project is open source, developers can inspect, modify, and extend its capabilities, and plugins allow for different recognition engines or enhanced features. -
2
Zerox OCR
PDF to Markdown with vision models
A dead simple way of OCR-ing a document for AI ingestion. Documents are meant to be a visual representation after all. With weird layouts, tables, charts, etc. The vision models just make sense. ZeroX is an open-source machine learning framework designed for fast experimentation and production deployment, optimized for speed and ease of use. -
3
Unlimited OCR Works
Welcome the Era of One-shot Long-horizon Parsing
...The repository also includes example code for batch inference over image folders or PDF inputs. Overall, it is useful for researchers and developers who need advanced OCR, long-document parsing, and model-based extraction from complex visual documents. -
4
DeepSeek-OCR
Contexts Optical Compression
DeepSeek-OCR is an open-source optical character recognition solution built as part of the broader DeepSeek AI vision-language ecosystem. It is designed to extract text from images, PDFs, and scanned documents, and integrates with multimodal capabilities that understand layout, context, and visual elements beyond raw character recognition. The system treats OCR not simply as “read the text” but as “understand what the text is doing in the image”—for example distinguishing captions from body... -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
-
5
DeepSeek-OCR 2
Visual Causal Flow
DeepSeek-OCR-2 is the second-generation optical character recognition system developed to improve document understanding by introducing a “visual causal flow” mechanism, enabling the encoder to reorder visual tokens in a way that better reflects semantic structure rather than strict raster scan order. It is designed to handle complex layouts and noisy documents by giving the model causal reasoning capabilities that mimic human visual scanning behavior, enhancing OCR performance on documents with rich spatial structure. ... -
6
LLM-Aided OCR Project
Enhances Tesseract OCR output using LLMs (local or API)
LLM Aided OCR is an open-source system designed to improve optical character recognition accuracy by combining traditional OCR tools with large language models. The project addresses common OCR challenges such as distorted text, unusual fonts, historical documents, and complex layouts that often produce inaccurate results with standard OCR pipelines. The system first extracts raw text using OCR engines and then applies language models to analyze and correct recognition errors based on... -
7
Video-subtitle-extractor
A GUI tool for extracting hard-coded subtitle (hardsub) from videos
Video hard subtitle extraction, generate srt file. There is no need to apply for a third-party API, and text recognition can be implemented locally. A deep learning-based video subtitle extraction framework, including subtitle region detection and subtitle content extraction. A GUI tool for extracting hard-coded subtitles (hardsub) from videos and generating srt files. Use local OCR recognition, no need to set up and call any API, and do not need to access online OCR services such as Baidu... -
8
deepdoctection
A Repo For Document AI
DeepDoctection is a document AI framework that applies deep learning techniques to analyze and extract structured data from scanned documents, PDFs, and images. deepdoctection is a Python library that orchestrates document extraction and document layout analysis tasks using deep learning models. It does not implement models but enables you to build pipelines using highly acknowledged libraries for object detection, OCR and selected NLP tasks and provides an integrated frameworks for... -
9
Chandra
OCR model for complex documents with layout-aware structured outputs
...Chandra can be run locally using transformer-based inference or deployed with a high-performance server setup for large-scale processing. It also includes command-line tools and optional web-based interfaces to simplify interaction and batch processing workflows. -
Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
-
10
OCR Reader
The tool supports template-based parsing, allowing structured output i
OCR Reader is a lightweight Windows utility designed to extract text from PDF files and images using OCR (Tesseract engine). The tool supports template-based parsing, allowing structured output into CSV or TXT without manual coding. Core components Tesseract OCR engine Poppler (PDF rendering) Template-based extraction system Homepage: https://martan1484.github.io/OCR_Reader
- Previous
- You're on page 1
- Next