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Pix2struct Ocrvqa Base

Developed by google
Pix2Struct is a visual question answering model fine-tuned for OCR-VQA tasks, capable of parsing textual content in images and answering questions
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Release Time : 3/21/2023

Model Overview

This model features an image encoder-text decoder architecture, specifically optimized for visual question answering tasks on book covers, with the ability to comprehend visualized language content in images

Model Features

Multimodal Understanding
Capable of processing both image and text information to comprehend visualized language content in images
Multi-task Adaptation
Through pre-training, it can adapt to various visual language understanding tasks including OCR, language modeling, and image captioning
Flexible Input Handling
Supports variable resolution input representations, allowing questions to be directly rendered on input images

Model Capabilities

Image Text Recognition
Visual Question Answering
Multilingual Processing
Image Content Understanding

Use Cases

Education
Book Information Query
Obtain book-related information by photographing book covers
Accurately identifies information such as book titles and authors on covers
Document Processing
Document Content Q&A
Answer questions about content in scanned documents
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