“ocr”的搜索结果

Socratic questioning partner named Gadfly for deep learning through dialogue. Use this skill when the user wants to learn, understand, or explore a topic through questions rather than explanations. Trigger when the user says "teach me about...", "help me understand...", "I want to learn...", "ask me questions about...", "quiz me", "Socratic method", "Gadfly", or wants to deeply understand something through dialogue rather than passive reading. Also trigger when the user provides a text or document and wants to be questioned about it, or wants to check their own understanding of a concept.

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OCR scanned or image-only corpora with vision-language models in four phases: `triage` inventories the scans, identifies script and language, and shortlists models by script, hardware, and data constraints; `evaluate` picks a system by measured CER/WER against ground truth, using born-digital twins, a second reader, and decision rules set in advance; `run` builds the production pipeline; and `clean` removes model artifacts, audits what every cleaning rule deletes, corrects with rule-based and LLM passes, and records provenance. Born-digital documents with a text layer go to $doc-to-markdown; runs on Leiden's ALICE cluster add $vlm-ocr-alice.

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Select an OCR/HTR engine by benchmarking candidates on the same labelled samples — source ground truth from open datasets (e.g. Hugging Face PAGE-XML corpora) or hand-transcription, wrap every engine behind a transcribe(image_path) -> str adapter (vision-LLMs via any OpenAI-compatible endpoint, dedicated HTR REST APIs, cloud OCR), and score with zero-dependency raw CER, lenient CER, WER, and a critical name/date token diff. Use when choosing an engine for handwriting or historical-document transcription, when published accuracy claims need honest verification on your own material, or when a records workflow must surface confident-but-wrong names and dates that a low aggregate CER hides.

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docling CLIを使用したドキュメント変換スキル。PDF、DOCX、PPTX、HTML、画像、Excel等のあらゆるドキュメントをMarkdown、JSON、YAML、HTML、テキストに変換。OCR対応で画像内テキストも抽出可能。Use when converting documents to Markdown or other formats, extracting text from PDFs, processing scanned documents with OCR, or converting office documents. Argument hint: [file_path] [--to md|json|yaml|html|text] [--ocr-lang ja] [--output output_dir]

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Expert en AudioCraft avancé (MusicGen text-to-music, AudioGen text-to-sound, fine-tuning)

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画像ファイルからテキストを抽出しクリップボードにコピー。「文字起こし」「OCR」などで使用。

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Break a stuck or complex problem into the smallest sub-question that, if answered, unlocks the next step — then answer it and repeat until the path forward is clear. Load when a problem feels genuinely stuck, when reasoning keeps circling, or when deep-thinking diagnoses a Socratic frame. Also triggers on "I keep going in circles", "what is the real question here", "help me reason through this step by step", "unstick my thinking", "recursive questioning", "what is the root question". Based on the recursive Socratic questioning method (EMNLP 2023) which outperforms CoT and Tree-of-Thought on complex reasoning tasks.

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Extract text from PDFs, inspect page counts and document metadata, merge files, or split them into individual pages. Create PDFs from Markdown, HTML, or Python code, using the tools suited to each task.

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• Extracting text from a PDF
• Combining several PDFs into one
• Splitting a PDF into individual pages

Develop a research question, search and verify literature, and combine findings into an academic report. Modes also support guided research discussions, claim checking, paper comparisons, and systematic reviews with optional meta-analysis, which statistically combines study results.

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• Clarify a research direction through guided questions
• Search literature and compare findings across sources
• Check specific claims against supporting sources

Convert PDF, Office, and other documents into Markdown that preserves useful text structure. Use batch conversion and literature organization to prepare files for search, text analysis, or AI systems that retrieve information from documents.

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• Convert PDF and Office files to Markdown
• Batch-convert a document folder
• Organize research papers with source metadata

Help junior developers and AI newcomers understand code through guided questions and progressive hints. Support debugging, concept learning, and critical review of AI-generated code so learners can explain their reasoning and work toward solutions themselves.

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• Understand errors through guided questions
• Explain AI-generated code in your own words
• Learn with pseudocode and progressive hints

Build a screening pipeline for web pages, PDFs, and images before an AI agent reads them. Extract hidden text, check for malicious instructions with detection models, and record decisions to block or allow content.

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• Screening external content before an agent reads it
• Checking uploaded PDFs and images for hidden instructions
• Scanning documents before adding them to a knowledge base

Route articles, meeting notes, videos, documents, and conversations to specialized workflows for saving in GBrain. Preserve sources, add citations, and update related people, companies, concepts, and timelines with links back to the saved material.

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• Save an article with its sources and related concepts
• Update attendee pages from meeting notes
• Organize video and podcast transcripts

Develop applications with the Claude API using examples from Anthropic's official cookbooks. Explore document summarization, image analysis, document retrieval, external tool calls, and prompt caching through practical Python code and implementation guidance.

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• Learning basic Claude API integration
• Building an assistant that searches documents
• Extracting text and information from images

Convert office documents, spreadsheets, presentations, ebooks, and PDFs into Markdown text that an agent can read. Save large conversions to a file and use hosted text recognition for scanned PDF pages when needed.

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• Prepare Word documents for an agent to read
• Convert spreadsheets and slides into Markdown
• Extract content from PDFs and ebooks

Extract PDF text when the usual file reader returns errors or unusable output. Choose command-line tools or Python libraries for plain text, metadata, tables, and complex layouts, with checks for scanned or copy-protected documents.

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• Recovering text when PDF reading fails
• Extracting tables and structured data from PDFs
• Inspecting PDF metadata

Extract PDF text using a sequence of tools when one method fails. Validate downloaded files, check whether the extracted text is substantial, record the successful method, and investigate alternative sources if extraction remains unsuccessful.

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• Extracting text from regulatory documents and handbooks
• Checking whether a PDF download returned an error page
• Trying another tool after empty or garbled text extraction

Convert various file formats (PDF, Office documents, images, audio, web content, structured data) to Markdown optimized for LLM processing. Use when converting documents to markdown, extracting text from PDFs/Office files, transcribing audio, performing OCR on images, extracting YouTube transcripts, or processing batches of files. Supports 20+ formats including DOCX, XLSX, PPTX, PDF, HTML, EPUB, CSV, JSON, images with OCR, and audio with transcription.

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Universal deep research agent team. 13-agent pipeline for rigorous academic research on any topic. 7 modes: full research, quick brief, paper review, lit-review, fact-check, Socratic guided research dialogue, and systematic review with optional meta-analysis. Covers research question formulation, Socratic mentoring, methodology design, systematic literature search, source verification, cross-source synthesis, risk of bias assessment, meta-analysis, APA 7.0 report compilation, editorial review, devil's advocate challenges, ethics review, and post-research literature monitoring. Triggers on: research, deep research, literature review, systematic review, meta-analysis, PRISMA, evidence synthesis, fact-check, guide my research, help me think through, 研究, 深度研究, 文獻回顧, 文獻探討, 系統性回顧, 後設分析, 事實查核, 引導我的研究, 幫我釐清, 幫我想想, 我不確定要研究什麼, 研究方向, 研究主題.

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Universal LaTeX document skill: create, compile, and convert any document to professional PDF with PNG previews. Supports resumes, reports, cover letters, invoices, academic papers, theses/dissertations, academic CVs, presentations (Beamer), scientific posters, formal letters, exams/quizzes, books, cheat sheets, reference cards, exam formula sheets, fillable PDF forms (hyperref form fields), conditional content (etoolbox toggles), mail merge from CSV/JSON (Jinja2 templates), version diffing (latexdiff), charts (pgfplots + matplotlib), tables (booktabs + CSV import), images (TikZ), Mermaid diagrams, AI-generated images, watermarks, landscape pages, bibliography/citations (BibTeX/biblatex), multi-language/CJK (auto XeLaTeX), algorithms/pseudocode, colored boxes (tcolorbox), SI units (siunitx), Pandoc format conversion (Markdown/DOCX/HTML ↔ LaTeX), and PDF-to-LaTeX conversion of handwritten or printed documents (math, business, legal, general). Compile script supports pdflatex, xelatex, lualatex with auto-detection, latexmk backend, texfot log filtering, PDF/A output, and verbosity control (--verbose/--quiet). Empirically optimized scaling: single agent 1-10 pages, split 11-20, batch-7 pipeline 21+. Use when user asks to: (1) create a resume/CV/cover letter, (2) write a LaTeX document, (3) create PDF with tables/charts/images, (4) compile a .tex file, (5) make a report/invoice/presentation, (6) anything involving LaTeX or pdflatex, (7) convert/OCR a PDF to LaTeX, (8) convert handwritten notes, (9) create charts/graphs/diagrams, (10) create slides, (11) write a thesis or dissertation, (12) create an academic CV, (13) create a poster, (14) create an exam/quiz, (15) create a book, (16) convert between document formats (Markdown, DOCX, HTML to/from LaTeX), (17) generate Mermaid diagrams for LaTeX, (18) create a formal business letter, (19) create a cheat sheet or reference card, (20) create an exam formula sheet or crib sheet, (21) condense lecture notes/PDFs into a cheat sheet, (22) create a fillable PDF form with text fields/checkboxes/dropdowns, (23) create a document with conditional content/toggles (show/hide sections), (24) generate batch/mail-merge documents from CSV/JSON data, (25) create a version diff PDF (latexdiff) highlighting changes between documents, (26) create a homework or assignment submission with problems and solutions, (27) create a lab report with data tables, graphs, and error analysis, (28) encrypt or password-protect a PDF, (29) merge multiple PDFs into one, (30) optimize/compress a PDF for web or email, (31) lint or check a LaTeX document for common issues, (32) count words in a LaTeX document, (33) analyze document statistics (figures, tables, citations), (34) fetch BibTeX from a DOI, (35) convert a Graphviz .dot file to PDF/PNG, (36) convert a PlantUML .puml file to PDF/PNG, (37) create a one-pager/fact sheet/executive summary, (38) create a datasheet or product specification sheet, (39) extract pages from a PDF (page ranges, odd/even), (40) check LaTeX package availability before compiling, (41) analyze citations and cross-reference with .bib files, (42) debug LaTeX compilation errors, (43) make a document accessible (PDF/A, tagged PDF), (44) create lecture notes or course handouts, (45) fill an existing PDF form (fillable fields or non-fillable with annotations), (46) extract text or tables from a PDF (pdfplumber, pypdf), (47) OCR a scanned PDF to text (pytesseract), (48) create a PDF programmatically with reportlab (Canvas, Platypus), (49) rotate or crop PDF pages (pypdf), (50) add a watermark to an existing PDF, (51) extract metadata from a PDF (title, author, subject).

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Run Apache Tika as a Docker container when you need guaranteed OCR (scanned PDFs, images) or geospatial raster support with zero local install — `apache/tika:<version>-full` bundles Tesseract, GDAL, ImageMagick, and fonts. Also covers the minimal image, port/volume/memory conventions, the path-identity mount gotcha, and how to confirm OCR actually ran rather than silently returning no text. Powered by Apache Tika. Use when a local `tika-app`/`tika-server` doesn't have Tesseract installed, or you want a disposable, self-contained parsing environment. Companion to the `file-to-markdown` skill, which covers the parsing calls themselves once a server is up.

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Use for Azure AI: Search, Speech, OpenAI, Document Intelligence. Helps with search, vector/hybrid search, speech-to-text, text-to-speech, transcription, OCR. WHEN: AI Search, query search, vector search, hybrid search, semantic search, speech-to-text, text-to-speech, transcribe, OCR, convert text to speech.

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Azure AI Vision Image Analysis SDK for captions, tags, objects, OCR, people detection, and smart cropping. Use for computer vision and image understanding tasks. Triggers: "image analysis", "computer vision", "OCR", "object detection", "ImageAnalysisClient", "image caption".

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Use when evaluating crypto charts through a CryptoCred-style structure lens: levels, confluence, market structure, risk definition, and educational technical process.

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