Pydantic schema hub for VLM-driven structured data extraction
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This project provides a curated catalog of Pydantic schemas designed for extracting structured data from visual inputs using Vision Language Models (VLMs). It targets developers and researchers needing to automate visual data extraction, offering pre-validated, industry-specific schemas to streamline integration and ensure data quality.
How It Works
The hub leverages Pydantic's robust data validation and type-hinting capabilities to define schemas for various visual data types like invoices, driver's licenses, and product information. These schemas act as structured output targets for VLMs, enabling them to return data in a predictable, machine-readable format. This approach simplifies complex parsing and validation, making VLM outputs directly usable in downstream applications and workflows.
Quick Start & Requirements
pip install vlmrun-hub
Highlighted Details
Maintenance & Community
Licensing & Compatibility
Limitations & Caveats
The README does not explicitly state the license type, which could be a blocker for some users. While it mentions qualitative results and benchmarks, direct performance metrics for the schemas themselves are not provided.
2 months ago
1 week