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examples/scipix/README.md
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# SciPix - Rust OCR Engine for Scientific Documents & Math Equations
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[](https://crates.io/crates/ruvector-scipix)
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[](https://docs.rs/ruvector-scipix)
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[](https://crates.io/crates/ruvector-scipix)
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[](https://opensource.org/licenses/MIT)
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[](https://www.rust-lang.org/)
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[](https://github.com/ruvnet/ruvector/actions)
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<p align="center">
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<strong>🔬 Production-ready Rust OCR library for extracting LaTeX, MathML, and text from scientific images</strong>
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</p>
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<p align="center">
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<em>Convert mathematical equations, scientific papers, and technical diagrams to structured text with GPU-accelerated inference</em>
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</p>
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<p align="center">
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<a href="#installation">Installation</a> |
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<a href="#quick-start">Quick Start</a> |
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<a href="#sdk-usage">SDK Usage</a> |
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<a href="#cli-reference">CLI Reference</a> |
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<a href="#tutorials">Tutorials</a> |
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<a href="#api-reference">API Reference</a>
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</p>
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---
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## Why SciPix?
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**SciPix** is a blazing-fast, memory-safe OCR (Optical Character Recognition) engine written in pure Rust. Unlike traditional OCR tools, SciPix is purpose-built for **scientific documents**, **mathematical equations**, and **technical diagrams** — making it the ideal choice for researchers, academics, and developers working with STEM content.
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### Use Cases
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- 📄 **Academic Paper Digitization** - Extract text and equations from scanned research papers
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- 🧮 **Math Homework Assistance** - Convert handwritten equations to LaTeX for AI tutoring apps
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- 📊 **Technical Documentation** - Process engineering diagrams and scientific charts
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- 🔬 **Research Data Extraction** - Batch process journal articles and extract structured data
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- 🤖 **AI/LLM Integration** - Feed scientific content to language models via MCP protocol
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### Key Features
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| Feature | Description |
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|---------|-------------|
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| 🚀 **ONNX Runtime** | GPU-accelerated neural network inference with CUDA, TensorRT, and CoreML support |
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| 📐 **LaTeX Output** | Accurate mathematical equation recognition with LaTeX, MathML, and AsciiMath export |
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| ⚡ **SIMD Optimized** | 4x faster image preprocessing with AVX2, SSE4, and NEON vectorization |
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| 🌐 **REST API** | Production-ready HTTP server with rate limiting, caching, and authentication |
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| 💻 **CLI Tool** | Batch processing, PDF conversion, and watch mode for continuous OCR |
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| 🦀 **Pure Rust SDK** | Type-safe, async/await native library with zero-copy image processing |
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| 🔌 **WebAssembly** | Run OCR directly in browsers with full WASM support |
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| 🤖 **MCP Server** | Integrate with Claude, ChatGPT, and other AI assistants via Model Context Protocol |
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| 📦 **Cross-Platform** | Linux, macOS, Windows, and ARM64 support out of the box |
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### Performance Benchmarks
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| Operation | SciPix | Tesseract | Mathpix |
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|-----------|--------|-----------|---------|
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| Simple Text OCR | **50ms** | 120ms | 200ms* |
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| Math Equation | **80ms** | N/A | 150ms* |
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| Batch (100 images) | **2.1s** | 8.5s | N/A |
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| Memory Usage | **45MB** | 180MB | Cloud |
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*API latency, not processing time
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---
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## Installation
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### From crates.io (Rust SDK)
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```bash
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cargo add ruvector-scipix
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```
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Or add to your `Cargo.toml`:
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```toml
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[dependencies]
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ruvector-scipix = "0.1.16"
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# With specific features
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ruvector-scipix = { version = "0.1.16", features = ["ocr", "math", "optimize"] }
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```
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### From Source (CLI & Server)
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```bash
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# Clone the repository
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git clone https://github.com/ruvnet/ruvector.git
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cd ruvector/examples/scipix
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# Build CLI and Server
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cargo build --release
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# Install globally (optional)
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cargo install --path .
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```
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### Pre-built Binaries
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```bash
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# Download latest release (Linux)
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curl -L https://github.com/ruvnet/ruvector/releases/latest/download/scipix-cli-linux-x64 -o scipix-cli
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chmod +x scipix-cli
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# Download latest release (macOS)
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curl -L https://github.com/ruvnet/ruvector/releases/latest/download/scipix-cli-darwin-arm64 -o scipix-cli
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chmod +x scipix-cli
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```
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### Feature Flags
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| Flag | Description | Default |
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|------|-------------|---------|
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| `default` | preprocess, cache, optimize | ✅ |
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| `ocr` | ONNX-based OCR engine | ❌ |
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| `math` | Math expression parsing | ❌ |
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| `preprocess` | Image preprocessing | ✅ |
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| `cache` | Result caching | ✅ |
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| `optimize` | SIMD & parallel optimizations | ✅ |
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| `wasm` | WebAssembly support | ❌ |
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---
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## Quick Start
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### 30-Second Setup
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```bash
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# Build and run the server
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cd examples/scipix
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cargo run --release --bin scipix-server
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# In another terminal, test the API
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curl http://localhost:3000/health
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# {"status":"healthy","version":"0.1.16"}
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```
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### Process Your First Image
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```bash
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# Encode an image to base64
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BASE64_IMAGE=$(base64 -w 0 equation.png)
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# Send OCR request
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curl -X POST http://localhost:3000/v3/text \
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-H "Content-Type: application/json" \
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-H "app_id: demo" \
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-H "app_key: demo_key" \
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-d "{\"base64\": \"$BASE64_IMAGE\", \"metadata\": {\"formats\": [\"text\", \"latex\"]}}"
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```
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---
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## SDK Usage
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### Basic Usage
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```rust
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use ruvector_scipix::{Config, Result};
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fn main() -> Result<()> {
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// Load default configuration
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let config = Config::default();
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// Validate configuration
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config.validate()?;
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println!("SciPix version: {}", ruvector_scipix::VERSION);
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Ok(())
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}
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```
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### Image Preprocessing
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```rust
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use ruvector_scipix::preprocess::{PreprocessPipeline, transforms};
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use image::open;
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fn preprocess_image(path: &str) -> Result<(), Box<dyn std::error::Error>> {
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// Load image
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let img = open(path)?;
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// Create preprocessing pipeline
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let pipeline = PreprocessPipeline::new()
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.with_auto_rotate(true)
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.with_auto_deskew(true)
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.with_noise_reduction(true)
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.with_contrast_enhancement(true);
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// Process image
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let processed = pipeline.process(img)?;
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// Save result
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processed.save("processed.png")?;
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Ok(())
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}
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```
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### OCR Engine (requires `ocr` feature)
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```rust
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use ruvector_scipix::ocr::{OcrEngine, OcrOptions};
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use ruvector_scipix::OcrConfig;
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#[tokio::main]
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async fn main() -> Result<(), Box<dyn std::error::Error>> {
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// Initialize OCR engine
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let config = OcrConfig::default();
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let engine = OcrEngine::new(config).await?;
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// Load and process image
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let image = image::open("equation.png")?;
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let result = engine.recognize(&image).await?;
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println!("Text: {}", result.text);
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println!("Confidence: {:.2}%", result.confidence * 100.0);
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// Get LaTeX output
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if let Some(latex) = result.latex {
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println!("LaTeX: {}", latex);
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}
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Ok(())
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}
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```
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### Math Parsing (requires `math` feature)
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```rust
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use ruvector_scipix::math::{parse_expression, to_latex, to_mathml};
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fn parse_math() -> Result<(), Box<dyn std::error::Error>> {
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// Parse a mathematical expression
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let expr = parse_expression("x^2 + 2x + 1")?;
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// Convert to different formats
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let latex = to_latex(&expr)?;
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let mathml = to_mathml(&expr)?;
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println!("LaTeX: {}", latex);
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println!("MathML: {}", mathml);
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Ok(())
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}
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```
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### Caching Results
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```rust
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use ruvector_scipix::cache::CacheManager;
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use ruvector_scipix::CacheConfig;
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fn use_cache() -> Result<(), Box<dyn std::error::Error>> {
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let config = CacheConfig {
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max_size: 1000,
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ttl_seconds: 3600,
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..Default::default()
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};
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let cache = CacheManager::new(config)?;
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// Store result
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cache.store("image_hash_123", &result)?;
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// Retrieve result
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if let Some(cached) = cache.get("image_hash_123")? {
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println!("Cache hit: {}", cached.latex);
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}
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Ok(())
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}
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```
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### Configuration Presets
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```rust
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use ruvector_scipix::{default_config, high_accuracy_config, high_speed_config};
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fn configure() {
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// Default balanced configuration
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let config = default_config();
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// High accuracy (slower, more precise)
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let accurate = high_accuracy_config();
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// High speed (faster, may sacrifice accuracy)
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let fast = high_speed_config();
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}
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```
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---
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## CLI Reference
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### Installation
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```bash
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# Install from source
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cargo install --path examples/scipix
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# Or use pre-built binary
|
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./scipix-cli --help
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```
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### Commands
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#### `ocr` - Process Single Image
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```bash
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# Basic OCR
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scipix-cli ocr --input document.png
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# With output file and format
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scipix-cli ocr --input equation.png --output result.json --format latex
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# Specify output formats
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scipix-cli ocr --input image.png --formats text,latex,mathml
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```
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**Options:**
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| Flag | Description | Default |
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|------|-------------|---------|
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| `-i, --input` | Input image path | Required |
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| `-o, --output` | Output file path | stdout |
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| `-f, --format` | Output format (json, text, latex) | json |
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| `--formats` | OCR formats (text, latex, mathml, html) | text |
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| `--confidence` | Minimum confidence threshold | 0.5 |
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#### `batch` - Process Multiple Images
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```bash
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# Process directory
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scipix-cli batch --input-dir ./images --output-dir ./results
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# With parallel processing
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scipix-cli batch -i ./images -o ./results --parallel 8
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# Recursive with specific formats
|
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scipix-cli batch -i ./docs -o ./output --recursive --format latex
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|
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# Watch mode for continuous processing
|
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scipix-cli batch -i ./inbox -o ./processed --watch
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```
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||||
|
||||
**Options:**
|
||||
| Flag | Description | Default |
|
||||
|------|-------------|---------|
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||||
| `-i, --input-dir` | Input directory | Required |
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||||
| `-o, --output-dir` | Output directory | Required |
|
||||
| `-p, --parallel` | Parallel workers | CPU cores |
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||||
| `-r, --recursive` | Process subdirectories | false |
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||||
| `--watch` | Watch for new files | false |
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||||
| `--max-retries` | Retry failed files | 3 |
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|
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#### `serve` - Start API Server
|
||||
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||||
```bash
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# Start with defaults
|
||||
scipix-cli serve
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||||
|
||||
# Custom address and port
|
||||
scipix-cli serve --address 0.0.0.0 --port 8080
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||||
|
||||
# With configuration file
|
||||
scipix-cli serve --config ./config.toml
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||||
|
||||
# Enable debug logging
|
||||
RUST_LOG=debug scipix-cli serve
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||||
```
|
||||
|
||||
**Options:**
|
||||
| Flag | Description | Default |
|
||||
|------|-------------|---------|
|
||||
| `-a, --address` | Bind address | 127.0.0.1 |
|
||||
| `-p, --port` | Port number | 3000 |
|
||||
| `-c, --config` | Config file path | None |
|
||||
| `--workers` | Worker threads | CPU cores |
|
||||
|
||||
#### `config` - Manage Configuration
|
||||
|
||||
```bash
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||||
# Show current configuration
|
||||
scipix-cli config show
|
||||
|
||||
# Initialize default config file
|
||||
scipix-cli config init
|
||||
|
||||
# Set specific values
|
||||
scipix-cli config set ocr.confidence_threshold 0.8
|
||||
scipix-cli config set server.port 8080
|
||||
|
||||
# Validate configuration
|
||||
scipix-cli config validate
|
||||
```
|
||||
|
||||
#### `doctor` - Environment Check
|
||||
|
||||
```bash
|
||||
# Run full diagnostics
|
||||
scipix-cli doctor
|
||||
|
||||
# Check specific components
|
||||
scipix-cli doctor --check cpu,memory,deps
|
||||
|
||||
# Output as JSON
|
||||
scipix-cli doctor --format json
|
||||
|
||||
# Auto-fix issues
|
||||
scipix-cli doctor --fix
|
||||
```
|
||||
|
||||
**Checks performed:**
|
||||
- CPU cores and SIMD capabilities (SSE2, AVX, AVX2, AVX-512, NEON)
|
||||
- Memory availability
|
||||
- ONNX Runtime installation
|
||||
- Model file availability
|
||||
- Configuration validity
|
||||
- Network port availability
|
||||
|
||||
#### `mcp` - MCP Server Mode
|
||||
|
||||
```bash
|
||||
# Start MCP server for AI integration
|
||||
scipix-cli mcp
|
||||
|
||||
# With debug logging
|
||||
scipix-cli mcp --debug
|
||||
|
||||
# With custom models directory
|
||||
scipix-cli mcp --models-dir ./custom-models
|
||||
```
|
||||
|
||||
**Available MCP Tools:**
|
||||
| Tool | Description |
|
||||
|------|-------------|
|
||||
| `ocr_image` | Process image file with OCR |
|
||||
| `ocr_base64` | Process base64-encoded image |
|
||||
| `batch_ocr` | Batch process multiple images |
|
||||
| `preprocess_image` | Apply image preprocessing |
|
||||
| `latex_to_mathml` | Convert LaTeX to MathML |
|
||||
| `benchmark_performance` | Run performance benchmarks |
|
||||
|
||||
**Claude Code Integration:**
|
||||
```bash
|
||||
claude mcp add scipix -- scipix-cli mcp
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Tutorials
|
||||
|
||||
### Tutorial 1: Basic Image OCR
|
||||
|
||||
Learn to extract text from images using the REST API.
|
||||
|
||||
```bash
|
||||
# Step 1: Start the server
|
||||
cargo run --bin scipix-server
|
||||
|
||||
# Step 2: Encode your image
|
||||
BASE64=$(base64 -w 0 document.png)
|
||||
|
||||
# Step 3: Send OCR request
|
||||
curl -X POST http://localhost:3000/v3/text \
|
||||
-H "Content-Type: application/json" \
|
||||
-H "app_id: test" \
|
||||
-H "app_key: test123" \
|
||||
-d "{\"base64\": \"$BASE64\", \"metadata\": {\"formats\": [\"text\"]}}"
|
||||
```
|
||||
|
||||
### Tutorial 2: Mathematical Equation Recognition
|
||||
|
||||
Convert math images to LaTeX format.
|
||||
|
||||
```bash
|
||||
curl -X POST http://localhost:3000/v3/text \
|
||||
-H "Content-Type: application/json" \
|
||||
-H "app_id: test" \
|
||||
-H "app_key: test123" \
|
||||
-d '{
|
||||
"url": "https://example.com/equation.png",
|
||||
"metadata": {
|
||||
"formats": ["latex", "mathml"],
|
||||
"math_mode": true
|
||||
}
|
||||
}'
|
||||
```
|
||||
|
||||
**Response:**
|
||||
```json
|
||||
{
|
||||
"latex": "\\frac{-b \\pm \\sqrt{b^2 - 4ac}}{2a}",
|
||||
"mathml": "<math>...</math>",
|
||||
"confidence": 0.92
|
||||
}
|
||||
```
|
||||
|
||||
### Tutorial 3: Batch PDF Processing
|
||||
|
||||
Process multi-page PDFs asynchronously.
|
||||
|
||||
```bash
|
||||
# Submit PDF job
|
||||
JOB=$(curl -s -X POST http://localhost:3000/v3/pdf \
|
||||
-H "Content-Type: application/json" \
|
||||
-H "app_id: test" \
|
||||
-H "app_key: test123" \
|
||||
-d '{
|
||||
"url": "https://example.com/paper.pdf",
|
||||
"options": {"format": "mmd", "enable_ocr": true}
|
||||
}')
|
||||
|
||||
JOB_ID=$(echo $JOB | jq -r '.pdf_id')
|
||||
|
||||
# Poll for completion
|
||||
curl http://localhost:3000/v3/pdf/$JOB_ID \
|
||||
-H "app_id: test" -H "app_key: test123"
|
||||
```
|
||||
|
||||
### Tutorial 4: CLI Batch Processing
|
||||
|
||||
```bash
|
||||
# Process entire directory
|
||||
scipix-cli batch \
|
||||
--input-dir ./documents \
|
||||
--output-dir ./results \
|
||||
--format latex \
|
||||
--parallel 4 \
|
||||
--recursive
|
||||
|
||||
# Watch mode for continuous processing
|
||||
scipix-cli batch \
|
||||
--input-dir ./inbox \
|
||||
--output-dir ./processed \
|
||||
--watch
|
||||
```
|
||||
|
||||
### Tutorial 5: WebAssembly Integration
|
||||
|
||||
```bash
|
||||
# Build WASM module
|
||||
cargo install wasm-pack
|
||||
wasm-pack build --target web --features wasm
|
||||
```
|
||||
|
||||
```html
|
||||
<script type="module">
|
||||
import init, { ScipixWasm } from './pkg/ruvector_scipix.js';
|
||||
|
||||
async function processImage() {
|
||||
await init();
|
||||
const scipix = new ScipixWasm();
|
||||
await scipix.initialize();
|
||||
|
||||
const canvas = document.getElementById('canvas');
|
||||
const imageData = canvas.getContext('2d').getImageData(0, 0, canvas.width, canvas.height);
|
||||
const result = await scipix.recognize(imageData.data);
|
||||
console.log('Result:', result);
|
||||
}
|
||||
|
||||
processImage();
|
||||
</script>
|
||||
```
|
||||
|
||||
### Tutorial 6: Using as MCP Server
|
||||
|
||||
Integrate SciPix with Claude Code or other AI assistants.
|
||||
|
||||
```bash
|
||||
# Add to Claude Code
|
||||
claude mcp add scipix -- scipix-cli mcp
|
||||
|
||||
# Or run standalone
|
||||
scipix-cli mcp --debug
|
||||
```
|
||||
|
||||
Then use tools in your AI conversations:
|
||||
- "Use the ocr_image tool to extract text from ./screenshot.png"
|
||||
- "Convert this LaTeX to MathML: \\frac{1}{2}"
|
||||
|
||||
---
|
||||
|
||||
## API Reference
|
||||
|
||||
### Authentication
|
||||
|
||||
All API endpoints (except `/health`) require authentication:
|
||||
|
||||
```
|
||||
app_id: your_application_id
|
||||
app_key: your_secret_key
|
||||
```
|
||||
|
||||
### Endpoints
|
||||
|
||||
#### `POST /v3/text` - Image OCR
|
||||
|
||||
```json
|
||||
{
|
||||
"base64": "...",
|
||||
"url": "https://...",
|
||||
"metadata": {
|
||||
"formats": ["text", "latex", "mathml"],
|
||||
"confidence_threshold": 0.5,
|
||||
"math_mode": false
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
#### `POST /v3/strokes` - Digital Ink
|
||||
|
||||
```json
|
||||
{
|
||||
"strokes": [{"x": [0, 10, 20], "y": [0, 10, 0]}],
|
||||
"metadata": {"formats": ["latex"]}
|
||||
}
|
||||
```
|
||||
|
||||
#### `POST /v3/pdf` - PDF Processing
|
||||
|
||||
```json
|
||||
{
|
||||
"url": "https://example.com/doc.pdf",
|
||||
"options": {
|
||||
"format": "mmd",
|
||||
"enable_ocr": true,
|
||||
"page_range": "1-10"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
#### `GET /health` - Health Check
|
||||
|
||||
```json
|
||||
{"status": "healthy", "version": "0.1.16"}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Configuration
|
||||
|
||||
### Environment Variables
|
||||
|
||||
```bash
|
||||
SERVER_ADDR=127.0.0.1:3000
|
||||
RUST_LOG=scipix=info
|
||||
RATE_LIMIT_PER_MINUTE=100
|
||||
CACHE_MAX_SIZE=1000
|
||||
MODEL_PATH=./models
|
||||
```
|
||||
|
||||
### Configuration File
|
||||
|
||||
```toml
|
||||
[server]
|
||||
address = "127.0.0.1"
|
||||
port = 3000
|
||||
workers = 4
|
||||
|
||||
[ocr]
|
||||
model_path = "./models"
|
||||
confidence_threshold = 0.5
|
||||
|
||||
[cache]
|
||||
max_size = 1000
|
||||
ttl_seconds = 3600
|
||||
|
||||
[rate_limit]
|
||||
requests_per_minute = 100
|
||||
burst_size = 20
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Performance
|
||||
|
||||
| Operation | Time (avg) | Throughput |
|
||||
|-----------|------------|------------|
|
||||
| SIMD Grayscale | 101µs | 4.2x faster |
|
||||
| SIMD Resize | 2.63ms | 1.5x faster |
|
||||
| Full Pipeline | 0.49ms | 4.4x faster |
|
||||
| Simple text OCR | ~50ms | 20 img/s |
|
||||
| Math equation | ~80ms | 12 img/s |
|
||||
|
||||
---
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
```bash
|
||||
# Check environment
|
||||
scipix-cli doctor
|
||||
|
||||
# Enable debug logging
|
||||
RUST_LOG=debug scipix-cli serve
|
||||
|
||||
# Verify models installed
|
||||
ls -la models/
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Contributing
|
||||
|
||||
```bash
|
||||
# Run tests
|
||||
cargo test --all-features
|
||||
|
||||
# Run linting
|
||||
cargo clippy --all-features
|
||||
|
||||
# Format code
|
||||
cargo fmt
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## License
|
||||
|
||||
MIT License - see [LICENSE](../../LICENSE) for details.
|
||||
|
||||
---
|
||||
|
||||
<p align="center">
|
||||
Part of the <a href="https://github.com/ruvnet/ruvector">ruvector</a> ecosystem<br>
|
||||
Built with Rust 🦀 | Powered by ONNX Runtime
|
||||
</p>
|
||||
Reference in New Issue
Block a user