wifi-densepose/vendor/ruvector/examples/scipix/docs/PREPROCESSING_API.md

Preprocessing Module API Reference

Quick Start

use ruvector_scipix::preprocess::{preprocess, PreprocessOptions};
use image::open;

// Basic preprocessing with defaults
let img = open("document.jpg")?;
let options = PreprocessOptions::default();
let processed = preprocess(&img, &options)?;

Core Types

PreprocessOptions

Complete configuration struct:

pub struct PreprocessOptions {
    pub auto_rotate: bool,              // Enable rotation detection
    pub auto_deskew: bool,              // Enable skew correction
    pub enhance_contrast: bool,         // Enable CLAHE
    pub denoise: bool,                  // Enable Gaussian blur
    pub threshold: Option<u8>,          // Manual threshold (None = auto Otsu)
    pub adaptive_threshold: bool,       // Use adaptive thresholding
    pub adaptive_window_size: u32,      // Window size for adaptive (odd number)
    pub target_width: Option<u32>,      // Resize width
    pub target_height: Option<u32>,     // Resize height
    pub detect_regions: bool,           // Enable text region detection
    pub blur_sigma: f32,                // Gaussian blur sigma
    pub clahe_clip_limit: f32,          // CLAHE clip limit
    pub clahe_tile_size: u32,           // CLAHE tile size
}

TextRegion

Detected text region with metadata:

pub struct TextRegion {
    pub region_type: RegionType,        // Text, Math, Table, Figure, Unknown
    pub bbox: (u32, u32, u32, u32),     // (x, y, width, height)
    pub confidence: f32,                // 0.0 to 1.0
    pub text_height: f32,               // Average text height in pixels
    pub baseline_angle: f32,            // Baseline angle in degrees
}

PreprocessPipeline Builder

Creating a Pipeline

use ruvector_scipix::preprocess::pipeline::PreprocessPipeline;

let pipeline = PreprocessPipeline::builder()
    // Rotation & Skew
    .auto_rotate(true)
    .auto_deskew(true)
    
    // Enhancement
    .enhance_contrast(true)
    .clahe_clip_limit(2.0)    // 2.0-4.0 recommended
    .clahe_tile_size(8)        // 8 or 16
    
    // Denoising
    .denoise(true)
    .blur_sigma(1.0)           // 0.5-2.0 typical
    
    // Thresholding
    .adaptive_threshold(true)
    .adaptive_window_size(15)  // Must be odd
    .threshold(None)           // None = auto Otsu
    
    // Resizing
    .target_size(Some(800), Some(600))
    
    // Progress tracking
    .progress_callback(|step, progress| {
        println!("{}... {:.0}%", step, progress * 100.0);
    })
    
    .build();

Processing

// Single image
let result = pipeline.process(&image)?;

// Batch processing (parallel)
let images = vec![img1, img2, img3];
let results = pipeline.process_batch(images)?;

// With intermediates for debugging
let intermediates = pipeline.process_with_intermediates(&image)?;
for (name, img) in intermediates {
    img.save(format!("debug_{}.png", name))?;
}

Module Functions

transforms.rs

// Basic operations
pub fn to_grayscale(image: &DynamicImage) -> GrayImage;
pub fn gaussian_blur(image: &GrayImage, sigma: f32) -> Result<GrayImage>;
pub fn sharpen(image: &GrayImage, sigma: f32, amount: f32) -> Result<GrayImage>;

// Thresholding
pub fn otsu_threshold(image: &GrayImage) -> Result<u8>;
pub fn threshold(image: &GrayImage, threshold: u8) -> GrayImage;
pub fn adaptive_threshold(image: &GrayImage, window_size: u32) -> Result<GrayImage>;

rotation.rs

pub fn detect_rotation(image: &GrayImage) -> Result<f32>;
pub fn rotate_image(image: &GrayImage, angle: f32) -> Result<GrayImage>;
pub fn detect_rotation_with_confidence(image: &GrayImage) -> Result<(f32, f32)>;
pub fn auto_rotate(image: &GrayImage, confidence_threshold: f32) -> Result<(GrayImage, f32, f32)>;

deskew.rs

pub fn detect_skew_angle(image: &GrayImage) -> Result<f32>;
pub fn deskew_image(image: &GrayImage, angle: f32) -> Result<GrayImage>;
pub fn auto_deskew(image: &GrayImage, max_angle: f32) -> Result<(GrayImage, f32)>;
pub fn detect_skew_projection(image: &GrayImage) -> Result<f32>;

enhancement.rs

pub fn clahe(image: &GrayImage, clip_limit: f32, tile_size: u32) -> Result<GrayImage>;
pub fn normalize_brightness(image: &GrayImage) -> GrayImage;
pub fn remove_shadows(image: &GrayImage) -> Result<GrayImage>;
pub fn contrast_stretch(image: &GrayImage) -> GrayImage;

segmentation.rs

pub fn find_text_regions(image: &GrayImage, min_region_size: u32) -> Result<Vec<TextRegion>>;
pub fn merge_overlapping_regions(regions: Vec<(u32, u32, u32, u32)>, merge_distance: u32) -> Vec<(u32, u32, u32, u32)>;
pub fn find_text_lines(image: &GrayImage, regions: &[(u32, u32, u32, u32)]) -> Vec<Vec<(u32, u32, u32, u32)>>;

Common Workflows

Document Scanning

let pipeline = PreprocessPipeline::builder()
    .auto_rotate(true)
    .auto_deskew(true)
    .enhance_contrast(true)
    .remove_shadows(true)  // Note: not in builder, manual call
    .adaptive_threshold(true)
    .build();

Low-Quality Images

let pipeline = PreprocessPipeline::builder()
    .denoise(true)
    .blur_sigma(1.5)        // Higher blur for noise
    .enhance_contrast(true)
    .clahe_clip_limit(3.0)  // Higher clip for more contrast
    .adaptive_threshold(true)
    .adaptive_window_size(21) // Larger window
    .build();

Fast Processing

let pipeline = PreprocessPipeline::builder()
    .auto_rotate(false)     // Skip if not needed
    .auto_deskew(false)
    .enhance_contrast(false)
    .denoise(false)
    .threshold(Some(128))   // Fixed threshold
    .build();

High Quality

let pipeline = PreprocessPipeline::builder()
    .auto_rotate(true)
    .auto_deskew(true)
    .enhance_contrast(true)
    .clahe_clip_limit(2.0)
    .clahe_tile_size(16)    // Larger tiles
    .denoise(true)
    .blur_sigma(0.8)        // Gentle blur
    .adaptive_threshold(true)
    .adaptive_window_size(11)
    .build();

Error Handling

use ruvector_scipix::preprocess::PreprocessError;

match preprocess(&img, &options) {
    Ok(processed) => { /* success */ },
    Err(PreprocessError::ImageLoad(msg)) => { /* handle load error */ },
    Err(PreprocessError::InvalidParameters(msg)) => { /* handle invalid params */ },
    Err(PreprocessError::Processing(msg)) => { /* handle processing error */ },
    Err(PreprocessError::Segmentation(msg)) => { /* handle segmentation error */ },
}

Performance Tips

1. Batch Processing: Use process_batch() for multiple images
2. Disable Unused Steps: Turn off rotation/deskew if not needed
3. Fixed Threshold: Use manual threshold instead of Otsu for speed
4. Smaller Tiles: Use 8x8 CLAHE tiles for speed, 16x16 for quality
5. Target Size: Resize before processing to reduce computation

Parameter Tuning

blur_sigma

• 0.5-1.0: Minimal noise reduction
• 1.0-1.5: Moderate (recommended)
• 1.5-2.5: Heavy denoising

clahe_clip_limit

• 1.5-2.0: Subtle enhancement
• 2.0-3.0: Moderate (recommended)
• 3.0-4.0: Strong enhancement

clahe_tile_size

• 4: Very local, may cause artifacts
• 8: Good balance (recommended)
• 16: Smoother, less local

adaptive_window_size

• 7-11: Small features, faster
• 13-17: Medium (recommended)
• 19-25: Large features, slower

Examples

See /home/user/ruvector/examples/scipix/examples/ for complete working examples.