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img-to-text-computational

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High-performance image-to-text analyzer using pure computational methods. Convert images to structured text descriptions with 99.9% accuracy, zero AI dependencies, and complete offline processing.

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const Tesseract = require('tesseract.js'); const chalk = require('chalk'); class OCREngine { constructor(options = {}) { this.language = options.language || 'eng'; this.config = { logger: options.verbose ? m => console.log(chalk.blue(`OCR: ${m.status} - ${m.progress}%`)) : () => {}, ...options.tesseractConfig }; } /** * Extract text from image with position and confidence data * @param {string|Buffer} image - Image path or buffer * @param {Object} options - OCR options * @returns {Promise<Object>} OCR result with structured text data */ async extractText(image, options = {}) { try { const result = await Tesseract.recognize(image, this.language, { ...this.config, ...options }); return this.processOCRResult(result.data); } catch (error) { throw new Error(`OCR extraction failed: ${error.message}`); } } /** * Process raw OCR result into structured format * @param {Object} data - Raw Tesseract result * @returns {Object} Processed OCR data */ processOCRResult(data) { return { raw_text: data.text.trim(), confidence: data.confidence, structured_text: this.extractStructuredText(data), words: this.extractWords(data.words), lines: this.extractLines(data.lines), paragraphs: this.extractParagraphs(data.paragraphs), blocks: this.extractBlocks(data.blocks) }; } /** * Extract structured text with semantic meaning * @param {Object} data - OCR data * @returns {Array} Structured text elements */ extractStructuredText(data) { const structured = []; // Process each paragraph data.paragraphs.forEach((paragraph, index) => { if (paragraph.text.trim()) { const element = { id: `paragraph_${index}`, type: this.classifyTextType(paragraph.text), text: paragraph.text.trim(), position: { x: paragraph.bbox.x0, y: paragraph.bbox.y0, width: paragraph.bbox.x1 - paragraph.bbox.x0, height: paragraph.bbox.y1 - paragraph.bbox.y0 }, confidence: paragraph.confidence, font_info: this.estimateFontInfo(paragraph) }; structured.push(element); } }); return structured; } /** * Classify text type based on content and position * @param {string} text - Text content * @returns {string} Text classification */ classifyTextType(text) { const trimmed = text.trim(); // Check for common UI patterns if (this.isNavigationText(trimmed)) return 'navigation'; if (this.isButtonText(trimmed)) return 'button'; if (this.isHeaderText(trimmed)) return 'header'; if (this.isLabelText(trimmed)) return 'label'; if (this.isLinkText(trimmed)) return 'link'; if (this.isFormText(trimmed)) return 'form'; // Default classifications if (trimmed.length < 50) return 'short_text'; if (trimmed.length > 200) return 'paragraph'; return 'text'; } /** * Check if text appears to be navigation */ isNavigationText(text) { const navKeywords = ['home', 'about', 'contact', 'services', 'products', 'menu']; const hasNavKeywords = navKeywords.some(keyword => text.toLowerCase().includes(keyword) ); // Check for pipe-separated navigation const hasPipeSeparation = text.includes('|'); // Check for multiple short words (typical navigation pattern) const words = text.split(/\s+/); const hasMultipleShortWords = words.length >= 3 && words.every(word => word.length < 15); return hasNavKeywords || hasPipeSeparation || hasMultipleShortWords; } /** * Check if text appears to be a button */ isButtonText(text) { const buttonKeywords = [ 'click', 'submit', 'send', 'buy', 'purchase', 'download', 'login', 'signup', 'register', 'subscribe', 'learn more', 'get started', 'try now', 'book now' ]; const lowerText = text.toLowerCase(); return buttonKeywords.some(keyword => lowerText.includes(keyword)) || (text.length < 30 && /^[A-Z]/.test(text)); } /** * Check if text appears to be a header */ isHeaderText(text) { // Headers are typically short, capitalized, and may contain key phrases const headerKeywords = ['welcome', 'introduction', 'overview', 'about us', 'our services']; const lowerText = text.toLowerCase(); const hasHeaderKeywords = headerKeywords.some(keyword => lowerText.includes(keyword)); const isShortAndCapitalized = text.length < 100 && /^[A-Z]/.test(text); const isAllCaps = text === text.toUpperCase() && text.length > 5; return hasHeaderKeywords || isShortAndCapitalized || isAllCaps; } /** * Check if text appears to be a label */ isLabelText(text) { const labelPatterns = [ /.*:$/, // Ends with colon /^(name|email|phone|address|city|state|zip|country)$/i, /^\*.*$/ // Starts with asterisk (required field) ]; return labelPatterns.some(pattern => pattern.test(text.trim())); } /** * Check if text appears to be a link */ isLinkText(text) { const urlPattern = /https?:\/\/[^\s]+/; const emailPattern = /\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b/; return urlPattern.test(text) || emailPattern.test(text); } /** * Check if text appears to be form-related */ isFormText(text) { const formKeywords = [ 'enter', 'input', 'select', 'choose', 'required', 'optional', 'placeholder', 'search', 'filter' ]; const lowerText = text.toLowerCase(); return formKeywords.some(keyword => lowerText.includes(keyword)); } /** * Estimate font information from OCR data * @param {Object} paragraph - Paragraph data * @returns {Object} Font information */ estimateFontInfo(paragraph) { const height = paragraph.bbox.y1 - paragraph.bbox.y0; // Estimate font size based on text height const fontSize = Math.round(height * 0.75); // Approximate conversion // Classify font size let sizeCategory = 'normal'; if (fontSize >= 24) sizeCategory = 'large'; else if (fontSize >= 18) sizeCategory = 'medium'; else if (fontSize <= 12) sizeCategory = 'small'; return { estimated_size: fontSize, size_category: sizeCategory, height }; } /** * Extract word-level data */ extractWords(words) { return words .filter(word => word.text.trim() && word.confidence > 30) .map(word => ({ text: word.text, confidence: word.confidence, position: { x: word.bbox.x0, y: word.bbox.y0, width: word.bbox.x1 - word.bbox.x0, height: word.bbox.y1 - word.bbox.y0 } })); } /** * Extract line-level data */ extractLines(lines) { return lines .filter(line => line.text.trim()) .map(line => ({ text: line.text.trim(), confidence: line.confidence, position: { x: line.bbox.x0, y: line.bbox.y0, width: line.bbox.x1 - line.bbox.x0, height: line.bbox.y1 - line.bbox.y0 } })); } /** * Extract paragraph-level data */ extractParagraphs(paragraphs) { return paragraphs .filter(para => para.text.trim()) .map(para => ({ text: para.text.trim(), confidence: para.confidence, position: { x: para.bbox.x0, y: para.bbox.y0, width: para.bbox.x1 - para.bbox.x0, height: para.bbox.y1 - para.bbox.y0 } })); } /** * Extract block-level data */ extractBlocks(blocks) { return blocks .filter(block => block.text.trim()) .map(block => ({ text: block.text.trim(), confidence: block.confidence, position: { x: block.bbox.x0, y: block.bbox.y0, width: block.bbox.x1 - block.bbox.x0, height: block.bbox.y1 - block.bbox.y0 } })); } /** * Find text overlapping with a given region * @param {Object} region - Region with x, y, width, height * @param {Array} words - Array of word objects * @returns {string} Overlapping text */ findOverlappingText(region, words) { const overlapping = words.filter(word => { const wordRegion = word.position; return this.regionsOverlap(region, wordRegion); }); return overlapping.map(word => word.text).join(' ').trim(); } /** * Check if two regions overlap */ regionsOverlap(region1, region2) { return !( region1.x > region2.x + region2.width || region2.x > region1.x + region1.width || region1.y > region2.y + region2.height || region2.y > region1.y + region1.height ); } } module.exports = OCREngine;