Technology

Image Structured Extraction

Automate the transformation of visual data from any image into clean, validated JSON or Pydantic schemas.

Image Structured Extraction is the process of converting unstructured visual information into a predictable, machine-readable format: think JSON or XML. This is not basic Optical Character Recognition (OCR); it leverages Multimodal Language Models (e.g., GPT-4o) to understand context and relationships within the image. We use this to reliably pull specific data fields—like an invoice number, a pharmaceutical dosage (500mg), or product metadata (color: 'navy', size: 'L')—and map them directly to a defined schema. This two-step approach (OCR for text, LLM for structure) ensures high-accuracy extraction and validation, making data instantly actionable for downstream systems.

https://www.useinstructor.com/blog/extracting-metadata-from-images-using-structured-extraction

What builders pair with Image Structured Extraction

Projects using both technologies. Select a pairing to see a project.

Built with Image Structured Extraction

ABBYY FineReader 1 shared project Amazon Textract 1 shared project Azure Computer Vision 1 shared project BLIP 1 shared project BLIP-2 1 shared project CLIP 1 shared project

12 more pairings

Data Augmentation 1 shared project Demo App 1 shared project Flamingo 1 shared project Google Cloud Vision API 1 shared project LXMERT 1 shared project OpenCV 1 shared project PaddleOCR 1 shared project Tesseract 1 shared project UNITER 1 shared project ViLBERT 1 shared project Vision Fine-Tuning 1 shared project Vision-Language Models 1 shared project

Pairing: ABBYY FineReader

Applying 4o Vision Finetuning to Chemistry Diagrams

Singapore · November 19, 2024

view project | view ABBYY FineReader

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4o Vision Finetuning Chemistry Diagrams

Singapore Nov 19

CLIP Vision Fine-Tuning