asepharyanaandKilo
67288c8723
Implement self-hosted document scanner and media processing tools as an alternative to CamScanner/ilovepdf without third-party uploads. Backend: Rust Axum gateway + worker pool with NATS JetStream queue Frontend: Next.js 16 + shadcn/ui + Tailwind v4 + Framer Motion Pipeline: Canny edge detection -> DLT homography warp -> Sauvola binarization -> Hough deskew -> Tesseract OCR -> searchable PDF Phase 1 (MVP) delivers: - Document scanner with perspective correction and OCR - Image compress/resize/convert tools - PDF merge/split/compress tools - Real-time WebSocket progress updates - Rate limiting, auto-cleanup, Prometheus metrics - Full CI/CD pipeline with Docker multi-stage build Co-Authored-By: Kilo <kilo@kilo.ai>
112 lines
3.2 KiB
Rust
112 lines
3.2 KiB
Rust
use image::GrayImage;
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use tools_common::error::PipelineError;
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/// OCR result with text and word-level bounding boxes.
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pub struct OcrResult {
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pub full_text: String,
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pub words: Vec<OcrWord>,
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pub confidence: f32,
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}
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/// A single word detected by OCR with its bounding box.
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#[derive(Debug, Clone)]
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pub struct OcrWord {
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pub text: String,
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pub bbox: Bbox,
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pub confidence: i32,
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}
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/// Bounding box coordinates.
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#[derive(Debug, Clone)]
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pub struct Bbox {
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pub x: i32,
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pub y: i32,
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pub width: i32,
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pub height: i32,
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}
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/// Initialize Tesseract OCR engine.
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/// Uses leptess crate which binds to libtesseract.
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/// Falls back gracefully if Tesseract is not installed.
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#[cfg(feature = "tesseract")]
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fn init_tesseract(lang: &str) -> Result<leptess::LepTess, PipelineError> {
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let tessdata_prefix = std::env::var("TESSDATA_PREFIX")
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.unwrap_or_else(|_| "/usr/share/tesseract-ocr/5/tessdata".to_string());
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let mut tess = leptess::LepTess::new(Some(&tessdata_prefix), lang)
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.map_err(|e| PipelineError::Ocr(format!("Failed to init Tesseract: {}", e)))?;
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Ok(tess)
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}
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/// Run OCR on a grayscale image and return extracted text.
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/// Uses Tesseract via leptess crate when the "tesseract" feature is enabled.
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/// Falls back to a placeholder when Tesseract is unavailable.
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pub fn ocr_text(img: &GrayImage, lang: &str) -> Result<OcrResult, PipelineError> {
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#[cfg(feature = "tesseract")]
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{
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let mut tess = init_tesseract(lang)?;
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let width = img.width() as i32;
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let height = img.height() as i32;
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// Set image from memory
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tess.set_image_from_mem(&img.to_vec(), width, height, 1, width)
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.map_err(|e| PipelineError::Ocr(format!("Failed to set image: {}", e)))?;
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tess.set_source_resolution(300);
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// Set PSM to automatic
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tess.set_page_seg_mode(3);
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let text = tess.get_utf8_text()
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.map_err(|e| PipelineError::Ocr(format!("OCR failed: {}", e)))?;
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let words = tess.get_words()
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.iter()
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.map(|w| OcrWord {
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text: w.text.clone(),
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bbox: Bbox {
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x: w.x,
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y: w.y,
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width: w.w,
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height: w.h,
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},
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confidence: w.confidence,
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})
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.collect();
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let confidence = if words.is_empty() {
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0.0
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} else {
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words.iter().map(|w| w.confidence as f32).sum::<f32>() / words.len() as f32
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};
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Ok(OcrResult {
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full_text: text,
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words,
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confidence,
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})
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}
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#[cfg(not(feature = "tesseract"))]
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{
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tracing::warn!("Tesseract feature not enabled, OCR returning placeholder");
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Ok(OcrResult {
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full_text: String::new(),
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words: Vec::new(),
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confidence: 0.0,
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})
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}
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}
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/// Run OCR on a grayscale image, returning only the text.
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pub fn ocr_text_only(img: &GrayImage, lang: &str) -> Result<String, PipelineError> {
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ocr_text(img, lang).map(|r| r.full_text)
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}
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/// Run OCR with word-level bounding boxes.
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pub fn ocr_words(img: &GrayImage, lang: &str) -> Result<Vec<OcrWord>, PipelineError> {
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ocr_text(img, lang).map(|r| r.words)
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} |