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Trocr Small Stage1

Developed by microsoft
TrOCR is a Transformer-based pre-trained optical character recognition model that adopts an encoder-decoder architecture, suitable for OCR tasks on single-line text images.
Downloads 3,713
Release Time : 3/2/2022

Model Overview

The TrOCR model combines an image Transformer encoder with a text Transformer decoder, capable of converting text in images into readable text content.

Model Features

Transformer-based Architecture
Utilizes advanced Transformer architecture for processing images and text, combining the strengths of DeiT and UniLM.
Pre-trained Model
Provides pre-trained weights that can be directly used for OCR tasks or as a base model for fine-tuning.
Single-line Text Recognition
Specifically optimized for optical character recognition tasks on single-line text images.

Model Capabilities

Image to Text
Optical Character Recognition
Single-line Text Recognition

Use Cases

Document Digitization
Scanned Document Recognition
Convert scanned document images into editable text content
High-precision text conversion results
Automated Processing
Form Processing
Automatically recognize and extract text information from forms
Improves data processing efficiency
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