import { createScipix } from 'ruvector-scipix-wasm';

// Initialize
const scipix = await createScipix();

// Recognize from file
const result = await scipix.recognize(imageData);
console.log(result.text);
console.log(result.latex);

Canvas Example

import { recognizeCanvas } from 'ruvector-scipix-wasm';

const canvas = document.getElementById('myCanvas');
const result = await recognizeCanvas(canvas);

Web Worker Example

import { createWorker } from 'ruvector-scipix-wasm';

const worker = createWorker();

// Process in background
const result = await worker.recognize(imageData);

// Batch processing with progress
const results = await worker.recognizeBatch(images, {
  onProgress: ({ processed, total }) => {
    console.log(`Progress: ${processed}/${total}`);
  }
});

worker.terminate();

API Reference

`createScipix(options?)`

Create a new Scipix instance.

const scipix = await createScipix({
  format: 'both',           // 'text' | 'latex' | 'both'
  confidenceThreshold: 0.5  // 0.0 - 1.0
});

`ScipixWasm`

Main API class.

Methods

recognize(imageData: Uint8Array): Promise<OcrResult>
recognizeFromCanvas(canvas: HTMLCanvasElement): Promise<OcrResult>
recognizeBase64(base64: string): Promise<OcrResult>
recognizeImageData(imageData: ImageData): Promise<OcrResult>
recognizeBatch(images: Uint8Array[]): Promise<OcrResult[]>
setFormat(format: RecognitionFormat): void
setConfidenceThreshold(threshold: number): void
getVersion(): string

Helper Functions

import {
  recognizeFile,      // From File/Blob
  recognizeCanvas,    // From HTMLCanvasElement
  recognizeBase64,    // From base64 string
  recognizeUrl,       // From image URL
  recognizeBatch,     // Batch processing
  imageToCanvas,      // Convert image to canvas
} from 'ruvector-scipix-wasm';

Types

`OcrResult`

interface OcrResult {
  text: string;           // Recognized text
  latex?: string;         // LaTeX (if enabled)
  confidence: number;     // 0.0 - 1.0
  metadata?: {
    width?: number;
    height?: number;
    format?: string;
  };
}

`RecognitionFormat`

type RecognitionFormat = 'text' | 'latex' | 'both';

Demo

Run the interactive demo:

npm run dev

Open http://localhost:8080/example.html

Performance Tips

Use Web Workers for large images or batch processing
Set confidence threshold to filter low-quality results
Resize images before processing if possible
Reuse instances instead of creating new ones
Use SharedImageBuffer for large image batches

Browser Support

Chrome 57+
Firefox 52+
Safari 11+
Edge 16+

Requires WebAssembly support.

Bundle Size

WASM module: ~800KB (gzipped)
JavaScript wrapper: ~15KB (gzipped)
Total: <1MB

License

MIT

Credits

Built with: