Extract text from documents
Extract and search text from images
OCR and Document Search Web Application
Extract text from images using OCR
Upload an image to extract text
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Extract and correct text from images
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Give it a pdf and it'll extract the text
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What is OnnxTR OCR?
OnnxTR OCR is a robust Optical Character Recognition (OCR) tool designed to extract text from various document formats with high accuracy. Leveraging the power of ONNX (Open Neural Network Exchange), it provides optimized performance for text recognition while maintaining ease of use.
Features
• High Accuracy: Delivers precise text extraction from scanned documents, images, or digital texts.
• Multi-Language Support: Recognizes text in multiple languages, making it versatile for global use.
• Document Flexibility: Supports various document formats, including PDF, JPG, PNG, and more.
• Optimized Performance: Utilizes ONNX for fast and efficient text recognition.
• Customizable: Allows users to fine-tune settings for specific use cases.
• Integration Ready: Easily integrates with other applications and workflows for seamless text processing.
How to use OnnxTR OCR?
Install the Library: Download and install OnnxTR OCR from its official repository or package manager.
Import the Tool: Integrate the OCR tool into your project using the provided API or SDK.
Load the Model: Initialize the pre-trained ONNX model for text recognition.
Upload Your Document: Load the document or image you want to process.
Extract Text: Run the OCR process to extract text from the uploaded document.
Review Results: Obtain and review the extracted text for further use or editing.
Frequently Asked Questions
What document formats does OnnxTR OCR support?
OnnxTR OCR supports a wide range of formats, including PDF, JPG, PNG, BMP, and more.
Can OnnxTR OCR handle multi-language documents?
Yes, OnnxTR OCR is capable of recognizing text in multiple languages, making it suitable for global applications.
How do I improve the accuracy of text extraction?
You can improve accuracy by ensuring high-quality input images, adjusting OCR settings, or using post-processing tools to refine the output.