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Extract text from scanned documents
Multimodal VDR Demo

Multimodal VDR Demo

Multimodal retrieval using llamaindex/vdr-2b-multi-v1

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What is Multimodal VDR Demo ?

The Multimodal VDR Demo is an advanced AI tool designed to extract text from scanned documents using cutting-edge technology. It leverages the llamaindex/vdr-2b-multi-v1 model to enable multimodal retrieval, allowing users to search through documents not just by text but also by images. This innovative approach combines natural language processing (NLP) with computer vision to provide a robust and intuitive document analysis experience.

Features

• Text Extraction: Accurately extract text from scanned documents, ensuring clarity and precision.
• Image Recognition: Identify and analyze images within documents, enabling multimodal search.
• Advanced Search: Combine text and image-based searches for more comprehensive results.
• Support for Multiple Formats: Process various document formats, including PDF, JPEG, and PNG.
• Integration Ready: Easily integrate with existing workflows for seamless document management.

How to use Multimodal VDR Demo ?

  1. Prepare Your Documents: Upload your scanned documents or images to the platform. Ensure they are in supported formats (e.g., PDF, JPEG, PNG).
  2. Initiate Search: Use the search interface to input text or upload images to find relevant documents.
  3. Preview Results: Review the retrieved documents and extracted text for accuracy.
  4. Refine Search: Fine-tune your queries or images to improve results if needed.
  5. Export Data: Download or save the extracted text and metadata for further use.

Frequently Asked Questions

1. What formats does the Multimodal VDR Demo support?
The demo supports PDF, JPEG, and PNG formats for document processing.

2. Can I integrate this tool with my existing software?
Yes, the Multimodal VDR Demo is designed to be integration-ready, allowing seamless compatibility with your current workflows.

3. How accurate is the image recognition feature?
The image recognition feature is highly accurate due to the advanced llamaindex/vdr-2b-multi-v1 model, but accuracy may vary based on the quality of scanned images.

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