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Construction de pipelines de prétraitement OCR et d'analyse de…

Utilisez deepdoctection lorsqu'un workflow d'agent nécessite un pipeline Python local pour l'analyse de mise en page de documents, l'OCR, la reconnaissance de tableaux et l'extraction au niveau de la page avant l'ingestion par LLM.

Qu'est-ce que Construction de pipelines de prétraitement OCR et d'analyse de… ?

Cette compétence permet aux agents IA de construire des pipelines de prétraitement locaux en Python avec deepdoctection pour l'analyse de mise en page de documents, l'OCR, la reconnaissance de tableaux et l'extraction au niveau de la page. Elle est particulièrement utile avant d'ingérer des documents dans un LLM, car elle structure et nettoie les données. La compétence prend en charge les environnements Python (>=3.10) et s'intègre avec `pip` ou `uv`. Elle orchestre des modèles de détection et de classification de tokens, et inclut des exemples d'utilisation de l'analyseur intégré pour décomposer des PDF en structures de mise en page. Les dépendances principales incluent `timm`, `transformers`, `python-doctr` et `deepdoctection`. La documentation complète est disponible sur Read the Docs et le code source sur GitHub.

Compatible avec~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/agentskillexchange/skills/tree/main/skills/build-ocr-and-layout-analysis-preprocessing-pipelines-with-deepdoctection
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Construction de pipelines de prétraitement OCR et d'analyse de mise en page avec deepdoctection

Utilisez deepdoctection lorsqu'un workflow d'agent nécessite un pipeline Python local pour l'analyse de mise en page de documents, l'OCR, la reconnaissance de tableaux et l'extraction au niveau de la page avant l'ingestion par LLM.

Prérequis

Environnement Python ; package deepdoctection ; dépendances sélectionnées pour OCR/mise en page/modèle ; PDF locaux ou images de documents scannés

Installation

Utilisez le chemin d'installation en amont ou la configuration qui correspond à votre environnement :

  • uv pip install timm # nécessaire pour la configuration par défaut
  • uv pip install transformers
  • uv pip install python-doctr
  • uv pip install deepdoctection

Exigences et remarques de la source amont :

  • deepdoctection est une bibliothèque Python qui orchestre l'analyse de mise en page de documents scannés et PDF, l'OCR et la reconnaissance de documents.
  • python
  • Python >= 3.10

Notes d'utilisation de base ou de démarrage :

Documentation

Source

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

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ActivityWatch Cross-Platform Automated Time Tracker and Producti

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act Local GitHub Actions Runner

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Use AgentClick when an agent should pause before risky commands, plans, drafts, or code changes so a human can inspect, edit, approve, or reject them in a purpose-built browser UI.

Add Claude design-system and accessibility workflows with UX/UI

Use UX/UI Agent Skills when Claude should generate tokens, component specs, accessibility audits, and framework-specific UI code from a repeatable design workflow.

Add executable smoke tests for shell scripts and CLIs before ref

Use Bats-core when an agent needs to turn fragile shell scripts or command-line workflows into something it can verify repeatedly after edits. The agent writes focused Bash tests for success paths, failure paths, and output contracts, then runs them locally or in CI before a refactor, release, or incident fix goes out.

Add graph-backed memory and context retrieval to agent workflows

Use Cognee to ingest project knowledge into graph and vector memory so agents can retrieve durable context across sessions and workflows.

Add IDE-style semantic code navigation and symbol-safe refactors

Give a coding agent symbol-aware lookup, cross-file rename, and structural edit tools before it starts making brittle text-only changes.

Add managed long-term memory to LangGraph agents with LangMem

Give LangGraph agents memory management and search tools so they can store, retrieve, and update durable facts across sessions.

Add multimodal lifelong memory to MCP and Python agents with Sim

Use SimpleMem to store, compress, index, and retrieve text or multimodal memories for agents through MCP or Python integrations.

Add persistent project memory and hook-driven synthesis with Cla

Keep Claude Code sessions grounded in prior decisions, project context, and daily handoff notes instead of starting from zero every time.

Add Postgres-native vector retrieval to agent and RAG workflows

Store embeddings beside application data in Postgres, create vector indexes, and query nearest neighbors for semantic search, RAG, recommendations, or agent memory retrieval.

Address GitHub PR review comments from the current branch with g

Find the open PR for the current branch, gather unresolved review comments, and drive a focused comment-resolution workflow with gh-authenticated context.

Add runtime guardrails to TypeScript agents with VoltAgent

Use VoltAgent to intercept, validate, and enforce input/output policies in TypeScript agent workflows.

Add temporal context memory to agent workflows with Zep

Use Zep as an external context layer for agents that need to store events, assemble temporal graph context, and retrieve relevant memory before model calls.

Adobe Firefly API Batch Image Generator

Calls Adobe Firefly

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