Compare commits
+1
-1
@@ -17,7 +17,7 @@ crate-type = ["lib", "cdylib"]
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pyo3 = { version = "0.25", features = ["extension-module"], optional = true }
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# PDF parsing
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lopdf = { git = "https://github.com/J-F-Liu/lopdf", rev = "052674053814a9f4897af94f0b8e46a545c9b329", features = ["rayon"] }
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lopdf = { git = "https://github.com/J-F-Liu/lopdf", rev = "7a05512d831415b1f2b1ce522391d6beab8a1284", features = ["rayon"] }
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# Error handling
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thiserror = "2.0"
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@@ -16,6 +16,23 @@ Built by [Firecrawl](https://firecrawl.dev) to handle text-based PDFs locally in
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- **Single document load** — The document is parsed once and shared between detection and extraction, avoiding redundant I/O.
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- **Lightweight** — Pure Rust, no ML models, no external services. Single dependency on `lopdf` for PDF parsing.
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## Benchmark
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Evaluated on the [opendataloader-bench](https://github.com/opendataloader-project/opendataloader-bench) corpus (200 PDFs). Only direct text extraction engines are shown — no OCR, no ML models. Scores are 0-1, higher is better.
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| Engine | Overall | Reading Order (NID) | Tables (TEDS) | Headings (MHS) | Speed (200 docs) |
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|---|---|---|---|---|---|
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| pdf-inspector | 0.77 | 0.87 | 0.52 | 0.58 | 4s |
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| opendataloader | 0.84 | 0.91 | 0.49 | 0.74 | 11s |
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| pymupdf4llm | 0.73 | 0.89 | 0.40 | 0.41 | 18s |
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| markitdown | 0.58 | 0.88 | 0.00 | 0.00 | 8s |
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For context, engines that use OCR/ML (docling, marker, mineru) score 0.83-0.88 overall but take 2-180 minutes on the same corpus.
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**Where we do well:** Speed (fastest of all engines), reading order, table detection vs other direct-text tools.
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**Where we lag:** Heading detection trails opendataloader — many PDFs use bold text at body font size for headings, or headings that are only slightly larger than body text. Table detection trails OCR-based engines that can see visual table structure.
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## Quick start
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### Python
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+1
-1
@@ -1,6 +1,6 @@
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{
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"name": "firecrawl-pdf-inspector",
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"version": "0.3.2",
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"version": "0.3.3",
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"description": "Fast PDF classification and text extraction. Detect text-based vs scanned PDFs, extract text by region with quality checks. Native Rust performance via napi-rs.",
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"main": "index.js",
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"types": "index.d.ts",
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@@ -82,7 +82,7 @@ pub(crate) fn extract_page_text_items(
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page_num: u32,
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font_cmaps: &FontCMaps,
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include_invisible: bool,
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) -> Result<(PageExtraction, bool), PdfError> {
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) -> Result<(PageExtraction, bool, bool), PdfError> {
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use lopdf::content::Content;
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let mut items = Vec::new();
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@@ -182,7 +182,7 @@ pub(crate) fn extract_page_text_items(
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content.operations.len(),
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MAX_OPERATIONS
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);
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return Ok(((Vec::new(), Vec::new(), Vec::new()), false));
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return Ok(((Vec::new(), Vec::new(), Vec::new()), false, false));
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}
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// Graphics state tracking
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@@ -1009,11 +1009,12 @@ pub(crate) fn extract_page_text_items(
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// Some PDFs embed landscape content in portrait pages using a rotated text
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// matrix (e.g. [0, b, -b, 0, tx, ty] for 90° CCW). The layout engine
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// assumes x=horizontal, y=vertical — so we swap coordinates to match.
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let (items, rects, lines) = correct_rotated_page(items, rects, lines, &rotation_votes);
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let (items, rects, lines, coords_rotated) =
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correct_rotated_page(items, rects, lines, &rotation_votes);
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let items = super::merge_text_items(items);
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let items = super::merge_subscript_items(items);
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Ok(((items, rects, lines), has_gid_fonts))
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Ok(((items, rects, lines), has_gid_fonts, coords_rotated))
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}
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/// Counts of text operators with horizontal vs rotated combined matrices.
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@@ -1030,9 +1031,9 @@ fn correct_rotated_page(
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mut rects: Vec<PdfRect>,
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mut lines: Vec<PdfLine>,
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votes: &RotationVotes,
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) -> (Vec<TextItem>, Vec<PdfRect>, Vec<PdfLine>) {
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) -> (Vec<TextItem>, Vec<PdfRect>, Vec<PdfLine>, bool) {
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if items.len() < 2 {
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return (items, rects, lines);
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return (items, rects, lines, false);
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}
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// Use the combined-matrix direction votes collected during extraction.
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@@ -1041,7 +1042,7 @@ fn correct_rotated_page(
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let total_votes = votes.horizontal + votes.rotated;
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if total_votes == 0 || votes.rotated * 3 < total_votes * 2 {
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// Less than ~67% of text operators are rotated → not a rotated page
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return (items, rects, lines);
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return (items, rects, lines, false);
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}
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log::debug!(
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@@ -1092,7 +1093,7 @@ fn correct_rotated_page(
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line.y2 = new_y2;
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}
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(items, rects, lines)
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(items, rects, lines, true)
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}
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/// Remove near-duplicate rects (same coordinates within 0.5 pt tolerance).
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@@ -1228,7 +1229,7 @@ mod tests {
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let font_cmaps = FontCMaps::from_doc(&doc);
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let result = extract_page_text_items(&doc, page_id, 1, &font_cmaps, false).unwrap();
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let ((items, rects, lines), _has_gid) = result;
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let ((items, rects, lines), _has_gid, _coords_rotated) = result;
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assert!(items.is_empty());
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assert!(rects.is_empty());
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assert!(lines.is_empty());
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+28
-2
@@ -35,6 +35,7 @@ pub(crate) fn detect_columns(
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if page_items.is_empty() {
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return vec![];
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}
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debug!("page {}: detect_columns: {} items", page, page_items.len());
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// Find page bounds
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let x_min = page_items.iter().map(|i| i.x).fold(f32::INFINITY, f32::min);
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@@ -166,6 +167,23 @@ pub(crate) fn detect_columns(
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return vec![ColumnRegion { x_min, x_max }];
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}
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// Try center-based assignment first (handles asymmetric layouts / sidebars
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// better than edge-based). Fall back to edge-based if center produces
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// a degenerate split (one side empty).
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let result = validate_and_build_columns(
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&valleys,
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&page_items,
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x_min,
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BIN_WIDTH,
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x_max,
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MIN_ITEMS_PER_COLUMN,
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MIN_VERTICAL_SPAN_RATIO,
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page,
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true, // center-based assignment
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);
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if result.len() > 1 {
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return result;
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}
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return validate_and_build_columns(
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&valleys,
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&page_items,
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@@ -175,7 +193,7 @@ pub(crate) fn detect_columns(
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MIN_ITEMS_PER_COLUMN,
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MIN_VERTICAL_SPAN_RATIO,
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page,
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false, // edge-based assignment for absolute valleys
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false, // edge-based fallback
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);
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}
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@@ -505,7 +523,15 @@ fn validate_and_build_columns(
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})
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.collect();
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if left_items.len() < min_items || right_items.len() < min_items {
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// Require both sides to have items. Symmetric layout needs min_items
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// on each side. Asymmetric layouts (sidebars) are accepted when the
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// dominant side has ≥ min_items and the smaller side has ≥ 3 items.
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let (smaller, larger) = if left_items.len() <= right_items.len() {
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(left_items.len(), right_items.len())
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} else {
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(right_items.len(), left_items.len())
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};
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if larger < min_items || smaller < 3 {
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continue;
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}
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@@ -188,7 +188,7 @@ fn extract_positioned_text_impl(
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continue;
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}
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}
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let ((mut items, rects, lines), has_gid_fonts) =
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let ((mut items, rects, lines), has_gid_fonts, _coords_rotated) =
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extract_page_text_items(doc, page_id, *page_num, font_cmaps, include_invisible)?;
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if has_gid_fonts {
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gid_encoded_pages.insert(*page_num);
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+133
-52
@@ -358,6 +358,8 @@ pub fn extract_text_in_regions_mem(
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let mut items_by_page: HashMap<u32, Vec<TextItem>> = HashMap::new();
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let mut page_heights: HashMap<u32, f32> = HashMap::new();
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let mut gid_pages: HashSet<u32> = HashSet::new();
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let mut page_thresholds: HashMap<u32, f32> = HashMap::new();
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let mut rotated_pages: HashSet<u32> = HashSet::new();
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for (page_num, &page_id) in pages.iter() {
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if !needed_pages.contains(page_num) {
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@@ -369,7 +371,7 @@ pub fn extract_text_in_regions_mem(
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page_heights.insert(*page_num, height);
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// Extract text items for this page
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let ((mut items, _rects, _lines), has_gid) =
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let ((mut items, _rects, _lines), has_gid, coords_rotated) =
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extractor::content_stream::extract_page_text_items(
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&doc,
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page_id,
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@@ -377,10 +379,16 @@ pub fn extract_text_in_regions_mem(
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&font_cmaps,
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false,
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)?;
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text_utils::fix_letterspaced_items(&mut items);
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let threshold = text_utils::fix_letterspaced_items(&mut items);
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if threshold > 0.10 {
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page_thresholds.insert(*page_num, threshold);
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}
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if has_gid {
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gid_pages.insert(*page_num);
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}
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if coords_rotated {
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rotated_pages.insert(*page_num);
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}
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items_by_page.insert(*page_num, items);
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}
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@@ -392,6 +400,12 @@ pub fn extract_text_in_regions_mem(
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let items = items_by_page.get(&page_1idx);
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let page_h = page_heights.get(&page_1idx).copied().unwrap_or(792.0);
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let page_has_gid = gid_pages.contains(&page_1idx);
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let adaptive_threshold = page_thresholds.get(&page_1idx).copied().unwrap_or(0.10);
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let coords = if rotated_pages.contains(&page_1idx) {
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RegionCoordSpace::Rotated90Ccw
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} else {
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RegionCoordSpace::Standard
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};
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let mut page_results = Vec::with_capacity(regions.len());
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@@ -399,7 +413,16 @@ pub fn extract_text_in_regions_mem(
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let [rx1, ry1, rx2, ry2] = *rect;
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let text = match items {
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Some(items) => collect_text_in_region(items, rx1, ry1, rx2, ry2, page_h),
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Some(items) => collect_text_in_region_with_options(
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items,
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rx1,
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ry1,
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rx2,
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ry2,
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page_h,
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coords,
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adaptive_threshold,
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),
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None => String::new(),
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};
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@@ -454,6 +477,20 @@ fn obj_to_f32(obj: &lopdf::Object) -> Option<f32> {
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}
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}
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#[derive(Clone, Copy)]
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enum RegionCoordSpace {
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Standard,
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Rotated90Ccw,
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}
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#[derive(Clone, Copy)]
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struct RegionBounds {
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x_min: f32,
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y_min: f32,
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x_max: f32,
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y_max: f32,
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}
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/// Collect text items that fall within a region bbox (top-left origin, PDF points)
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/// and return them as a single string in reading order.
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pub fn collect_text_in_region(
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@@ -464,65 +501,109 @@ pub fn collect_text_in_region(
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ry2: f32,
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page_height: f32,
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) -> String {
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// Convert region from top-left to bottom-left origin
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let by1 = page_height - ry2; // top-left y2 → bottom-left y1
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let by2 = page_height - ry1; // top-left y1 → bottom-left y2
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collect_text_in_region_with_options(
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items,
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rx1,
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ry1,
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rx2,
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ry2,
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page_height,
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infer_region_coord_space(items),
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0.10,
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)
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}
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// Collect items whose center falls within the region
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let mut matched: Vec<&TextItem> = items
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#[allow(clippy::too_many_arguments)]
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fn collect_text_in_region_with_options(
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items: &[TextItem],
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rx1: f32,
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ry1: f32,
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rx2: f32,
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ry2: f32,
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page_height: f32,
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coord_space: RegionCoordSpace,
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adaptive_threshold: f32,
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) -> String {
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let bounds = region_bounds(rx1, ry1, rx2, ry2, page_height, coord_space);
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let Some(page) = items.first().map(|item| item.page) else {
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return String::new();
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};
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let matched: Vec<TextItem> = items
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.iter()
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.filter(|item| {
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let cx = item.x + item.width / 2.0;
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let cy = item.y + item.height / 2.0;
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cx >= rx1 && cx <= rx2 && cy >= by1 && cy <= by2
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})
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.filter(|item| region_overlaps_item(item, bounds))
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.cloned()
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.collect();
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if matched.is_empty() {
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return String::new();
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}
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// Sort top→bottom (descending Y in bottom-left coords), then left→right.
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// Uses strict total_cmp ordering to guarantee transitivity (required by
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// Rust's sort). The line-grouping phase below handles fuzzy Y matching.
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matched.sort_by(|a, b| {
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b.y.total_cmp(&a.y) // descending Y = top to bottom
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.then(a.x.total_cmp(&b.x)) // ascending X = left to right
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});
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// Group into lines and join
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let mut lines: Vec<String> = Vec::new();
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let mut current_line = String::new();
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let mut last_y = f32::NAN;
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let mut last_x_end = 0.0_f32;
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for item in &matched {
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let line_threshold = item.font_size * 0.5;
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let same_line = (item.y - last_y).abs() < line_threshold;
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if !same_line && !current_line.is_empty() {
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lines.push(current_line.clone());
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current_line.clear();
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}
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if !current_line.is_empty() {
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// Insert space if there's a gap between items on the same line
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let gap = item.x - last_x_end;
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if gap > item.font_size * 0.15 {
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current_line.push(' ');
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}
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}
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current_line.push_str(&item.text);
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last_y = item.y;
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last_x_end = item.x + item.width;
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let mut thresholds = HashMap::new();
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if adaptive_threshold > 0.10 {
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thresholds.insert(page, adaptive_threshold);
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}
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let lines = extractor::group_into_lines_with_thresholds(matched, &thresholds, &HashSet::new());
|
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lines
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.into_iter()
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.map(|line| line.text())
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.collect::<Vec<_>>()
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.join("\n")
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}
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|
||||
if !current_line.is_empty() {
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lines.push(current_line);
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fn infer_region_coord_space(items: &[TextItem]) -> RegionCoordSpace {
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// Rotated-page normalization currently maps y = -old_x, so most text items
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// land at negative Y. Use this to keep `collect_text_in_region` behavior
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// compatible for direct callers that do not have extractor metadata.
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let negative_y = items.iter().filter(|item| item.y < 0.0).count();
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if !items.is_empty() && negative_y * 2 >= items.len() {
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RegionCoordSpace::Rotated90Ccw
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} else {
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RegionCoordSpace::Standard
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||||
}
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||||
}
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|
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lines.join("\n")
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fn region_bounds(
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rx1: f32,
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ry1: f32,
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rx2: f32,
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ry2: f32,
|
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page_height: f32,
|
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coord_space: RegionCoordSpace,
|
||||
) -> RegionBounds {
|
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let tx_min = rx1.min(rx2);
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let tx_max = rx1.max(rx2);
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let ty_min = ry1.min(ry2);
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let ty_max = ry1.max(ry2);
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let by_min = page_height - ty_max;
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let by_max = page_height - ty_min;
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match coord_space {
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RegionCoordSpace::Standard => RegionBounds {
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x_min: tx_min,
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y_min: by_min,
|
||||
x_max: tx_max,
|
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y_max: by_max,
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},
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RegionCoordSpace::Rotated90Ccw => RegionBounds {
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x_min: by_min,
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x_max: by_max,
|
||||
y_min: -tx_max,
|
||||
y_max: -tx_min,
|
||||
},
|
||||
}
|
||||
}
|
||||
|
||||
fn region_overlaps_item(item: &TextItem, bounds: RegionBounds) -> bool {
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const REGION_MARGIN: f32 = 1.5;
|
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let item_x_min = item.x;
|
||||
let item_x_max = item.x + text_utils::effective_width(item);
|
||||
let item_y_min = item.y;
|
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let item_y_max = item.y + item.height;
|
||||
|
||||
let x_overlap = (item_x_max.min(bounds.x_max + REGION_MARGIN)
|
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- item_x_min.max(bounds.x_min - REGION_MARGIN))
|
||||
.max(0.0);
|
||||
let y_overlap = (item_y_max.min(bounds.y_max + REGION_MARGIN)
|
||||
- item_y_min.max(bounds.y_min - REGION_MARGIN))
|
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.max(0.0);
|
||||
x_overlap > 0.0 && y_overlap > 0.0
|
||||
}
|
||||
|
||||
// =========================================================================
|
||||
|
||||
@@ -8,6 +8,24 @@ use log::debug;
|
||||
/// Font statistics for a document
|
||||
pub(crate) struct FontStats {
|
||||
pub(crate) most_common_size: f32,
|
||||
/// Font size frequency distribution (size_key → line count).
|
||||
/// Used for rarity-based heading detection.
|
||||
pub(crate) size_counts: HashMap<i32, usize>,
|
||||
/// Total number of lines counted.
|
||||
pub(crate) total_lines: usize,
|
||||
}
|
||||
|
||||
/// Compute how rare a font size is in the document (0.0 = most common, 1.0 = unique).
|
||||
/// Mirrors opendataloader's font rarity boosting approach: heading fonts appear on
|
||||
/// far fewer lines than body text, so their percentile rank is high.
|
||||
pub(crate) fn font_size_rarity(font_size: f32, stats: &FontStats) -> f32 {
|
||||
if stats.total_lines == 0 {
|
||||
return 0.0;
|
||||
}
|
||||
let key = (font_size * 10.0) as i32;
|
||||
let count = stats.size_counts.get(&key).copied().unwrap_or(0);
|
||||
// Rarity = 1 - (frequency ratio). A size used on 1/100 lines has rarity ~0.99.
|
||||
1.0 - (count as f32 / stats.total_lines as f32)
|
||||
}
|
||||
|
||||
/// Calculate font stats directly from items (before grouping into lines)
|
||||
@@ -21,6 +39,8 @@ pub(crate) fn calculate_font_stats_from_items(items: &[TextItem]) -> FontStats {
|
||||
}
|
||||
}
|
||||
|
||||
let total_lines = size_counts.values().sum();
|
||||
|
||||
// Break ties by preferring the smaller font size for deterministic output
|
||||
let most_common_size = size_counts
|
||||
.iter()
|
||||
@@ -30,7 +50,11 @@ pub(crate) fn calculate_font_stats_from_items(items: &[TextItem]) -> FontStats {
|
||||
.map(|(size, _)| *size as f32 / 10.0)
|
||||
.unwrap_or(12.0);
|
||||
|
||||
FontStats { most_common_size }
|
||||
FontStats {
|
||||
most_common_size,
|
||||
size_counts,
|
||||
total_lines,
|
||||
}
|
||||
}
|
||||
|
||||
/// Calculate font stats from grouped lines
|
||||
@@ -48,6 +72,8 @@ pub(crate) fn calculate_font_stats(lines: &[TextLine]) -> FontStats {
|
||||
}
|
||||
}
|
||||
|
||||
let total_lines = size_counts.values().sum();
|
||||
|
||||
// Break ties by preferring the smaller font size for deterministic output
|
||||
let most_common_size = size_counts
|
||||
.iter()
|
||||
@@ -57,7 +83,23 @@ pub(crate) fn calculate_font_stats(lines: &[TextLine]) -> FontStats {
|
||||
.map(|(size, _)| *size as f32 / 10.0)
|
||||
.unwrap_or(12.0);
|
||||
|
||||
FontStats { most_common_size }
|
||||
FontStats {
|
||||
most_common_size,
|
||||
size_counts,
|
||||
total_lines,
|
||||
}
|
||||
}
|
||||
|
||||
/// Determine the heading level for a bold-only line that didn't meet the font-size
|
||||
/// threshold. These are common in academic papers where section headings are bold
|
||||
/// at the same size as body text.
|
||||
///
|
||||
/// Returns a level below the lowest font-size tier (or H2 when no tiers exist).
|
||||
pub(crate) fn bold_heading_level(heading_tiers: &[f32]) -> usize {
|
||||
let level = heading_tiers.len() + 1;
|
||||
// Clamp to 1..=6 — if no font-size tiers, bold headings become H2
|
||||
// (H1 is reserved for titles which are typically larger)
|
||||
level.clamp(2, 6)
|
||||
}
|
||||
|
||||
/// Detect TOC-style lines that contain dot leaders (e.g., "Section Name .... 42").
|
||||
|
||||
@@ -4,13 +4,11 @@
|
||||
pub(crate) fn is_caption_line(text: &str) -> bool {
|
||||
let trimmed = text.trim();
|
||||
|
||||
// Common caption prefixes in multiple languages
|
||||
let caption_prefixes = [
|
||||
"Figure ",
|
||||
// Caption prefixes that always match (always followed by identifiers)
|
||||
let always_prefixes = [
|
||||
"Figura ",
|
||||
"Fig. ",
|
||||
"Fig ",
|
||||
"Table ",
|
||||
"Tabela ",
|
||||
"Source:",
|
||||
"Fonte:",
|
||||
@@ -27,17 +25,39 @@ pub(crate) fn is_caption_line(text: &str) -> bool {
|
||||
"Photo ",
|
||||
"Foto ",
|
||||
];
|
||||
|
||||
// Check if line starts with a caption prefix
|
||||
for prefix in &caption_prefixes {
|
||||
for prefix in &always_prefixes {
|
||||
if trimmed.starts_with(prefix) {
|
||||
return true;
|
||||
}
|
||||
}
|
||||
|
||||
// Check case-insensitive patterns
|
||||
// "Figure" and "Table" need a digit/reference after them to distinguish
|
||||
// captions ("Table 1", "Figure 3.2") from headings ("Table of Contents")
|
||||
for prefix in ["Figure ", "Table "] {
|
||||
if let Some(rest) = trimmed.strip_prefix(prefix) {
|
||||
if rest
|
||||
.trim_start()
|
||||
.starts_with(|c: char| c.is_ascii_digit() || c == '(' || c == '#')
|
||||
{
|
||||
return true;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Check case-insensitive patterns — require digit or punctuation after
|
||||
// prefix to avoid matching "Table of Contents" or "Figure drawing" etc.
|
||||
let lower = trimmed.to_lowercase();
|
||||
if lower.starts_with("figure ") || lower.starts_with("table ") || lower.starts_with("source:") {
|
||||
for pfx in ["figure ", "table "] {
|
||||
if let Some(rest) = lower.strip_prefix(pfx) {
|
||||
if rest
|
||||
.trim_start()
|
||||
.starts_with(|c: char| c.is_ascii_digit() || c == '(' || c == '#')
|
||||
{
|
||||
return true;
|
||||
}
|
||||
}
|
||||
}
|
||||
if lower.starts_with("source:") {
|
||||
return true;
|
||||
}
|
||||
|
||||
|
||||
+48
-4
@@ -6,8 +6,8 @@ use crate::structure_tree::StructRole;
|
||||
use crate::types::TextLine;
|
||||
|
||||
use super::analysis::{
|
||||
calculate_font_stats, compute_heading_tiers, compute_paragraph_threshold, detect_header_level,
|
||||
has_dot_leaders,
|
||||
bold_heading_level, calculate_font_stats, compute_heading_tiers, compute_paragraph_threshold,
|
||||
detect_header_level, font_size_rarity, has_dot_leaders,
|
||||
};
|
||||
use super::classify::{format_list_item, is_caption_line, is_list_item, is_monospace_font};
|
||||
use super::postprocess::clean_markdown;
|
||||
@@ -443,7 +443,33 @@ pub(super) fn to_markdown_from_lines_with_tables_and_images(
|
||||
&& plain_trimmed.split_whitespace().count() <= 15
|
||||
{
|
||||
let line_font_size = line.items.first().map(|i| i.font_size).unwrap_or(base_size);
|
||||
detect_header_level(line_font_size, base_size, &heading_tiers)
|
||||
detect_header_level(line_font_size, base_size, &heading_tiers).or_else(|| {
|
||||
// Rarity-based heading detection (inspired by opendataloader).
|
||||
// Score = font_rarity * 0.5 + bold * 0.3 + standalone * 0.2
|
||||
// Lines scoring above threshold are promoted to headings.
|
||||
// Only consider lines at or above body font size.
|
||||
if line_font_size < base_size * 0.95 {
|
||||
return None;
|
||||
}
|
||||
let word_count = plain_trimmed.split_whitespace().count();
|
||||
if !(1..=15).contains(&word_count) {
|
||||
return None;
|
||||
}
|
||||
let rarity = font_size_rarity(line_font_size, &font_stats);
|
||||
let all_bold = !line.items.is_empty() && line.items.iter().all(|i| i.is_bold);
|
||||
let standalone = !in_paragraph;
|
||||
|
||||
let score = rarity * 0.5
|
||||
+ if all_bold { 0.3 } else { 0.0 }
|
||||
+ if standalone { 0.2 } else { 0.0 };
|
||||
|
||||
// Require standalone + at least one other signal
|
||||
if score >= 0.5 && standalone && word_count >= 3 {
|
||||
Some(bold_heading_level(&heading_tiers))
|
||||
} else {
|
||||
None
|
||||
}
|
||||
})
|
||||
} else {
|
||||
None
|
||||
};
|
||||
@@ -699,7 +725,25 @@ pub fn to_markdown_from_lines(lines: Vec<TextLine>, options: MarkdownOptions) ->
|
||||
{
|
||||
let line_font_size = line.items.first().map(|i| i.font_size).unwrap_or(base_size);
|
||||
if let Some(header_level) =
|
||||
detect_header_level(line_font_size, base_size, &heading_tiers)
|
||||
detect_header_level(line_font_size, base_size, &heading_tiers).or_else(|| {
|
||||
if line_font_size < base_size * 0.95 {
|
||||
return None;
|
||||
}
|
||||
let word_count = plain_trimmed.split_whitespace().count();
|
||||
if !(1..=15).contains(&word_count) {
|
||||
return None;
|
||||
}
|
||||
let rarity = font_size_rarity(line_font_size, &font_stats);
|
||||
let all_bold = !line.items.is_empty() && line.items.iter().all(|i| i.is_bold);
|
||||
let standalone = !in_paragraph;
|
||||
let score = rarity * 0.5
|
||||
+ if all_bold { 0.3 } else { 0.0 }
|
||||
+ if standalone { 0.2 } else { 0.0 };
|
||||
if score >= 0.5 && standalone && word_count >= 3 {
|
||||
return Some(bold_heading_level(&heading_tiers));
|
||||
}
|
||||
None
|
||||
})
|
||||
{
|
||||
if in_paragraph {
|
||||
output.push_str("\n\n");
|
||||
|
||||
+70
-5
@@ -601,6 +601,15 @@ pub(crate) fn to_markdown_from_items_with_rects_and_lines(
|
||||
let group = page_groups.get(&page).unwrap();
|
||||
let page_items: Vec<TextItem> = group.iter().map(|(_, item)| (*item).clone()).collect();
|
||||
|
||||
// Detect columns early — on multi-column pages, the merged-band retry
|
||||
// should skip body-font heuristic table detection (which mistakes column
|
||||
// text for tables). Individual band heuristic detection is left enabled
|
||||
// because bands are scoped to single columns.
|
||||
let page_has_columns = {
|
||||
let cols = crate::extractor::detect_columns(&page_items, page, false);
|
||||
cols.len() >= 2
|
||||
};
|
||||
|
||||
// Check for side-by-side layout (e.g. two tables placed left and right)
|
||||
let mut bands = split_side_by_side(&page_items);
|
||||
// Fallback: use rect hint regions to detect side-by-side layout
|
||||
@@ -873,10 +882,7 @@ pub(crate) fn to_markdown_from_items_with_rects_and_lines(
|
||||
run_heuristic(&unclaimed_items, &unclaimed_map, 6);
|
||||
}
|
||||
|
||||
// 4. Column-based table detection: last resort for borderless tabular
|
||||
// layouts (e.g. exam/reference grids) when ALL structural methods
|
||||
// found nothing. Only runs when no rects/lines exist (truly borderless)
|
||||
// and no other detection method found tables in this band.
|
||||
// 4. Column-based table detection for borderless tabular layouts.
|
||||
let band_has_tables = band_items.iter().enumerate().any(|(idx, _)| {
|
||||
band_index_map
|
||||
.get(idx)
|
||||
@@ -903,6 +909,65 @@ pub(crate) fn to_markdown_from_items_with_rects_and_lines(
|
||||
}
|
||||
}
|
||||
|
||||
// 5. Thin-rect border synthesis: last resort for PDFs that draw table
|
||||
// borders as thin filled rectangles (common in spreadsheet exports).
|
||||
// Only runs when ALL other methods found nothing on this page.
|
||||
if !page_tables.contains_key(&page) {
|
||||
let page_rects: Vec<&crate::types::PdfRect> =
|
||||
rects.iter().filter(|r| r.page == page).collect();
|
||||
let mut synth_lines: Vec<crate::types::PdfLine> = Vec::new();
|
||||
for r in &page_rects {
|
||||
let (mut w, mut h) = (r.width, r.height);
|
||||
let (mut x, mut y) = (r.x, r.y);
|
||||
if w < 0.0 {
|
||||
x += w;
|
||||
w = -w;
|
||||
}
|
||||
if h < 0.0 {
|
||||
y += h;
|
||||
h = -h;
|
||||
}
|
||||
if h < 2.0 && w >= 10.0 {
|
||||
let mid_y = y + h / 2.0;
|
||||
synth_lines.push(crate::types::PdfLine {
|
||||
x1: x,
|
||||
y1: mid_y,
|
||||
x2: x + w,
|
||||
y2: mid_y,
|
||||
page,
|
||||
});
|
||||
} else if w < 2.0 && h >= 10.0 {
|
||||
let mid_x = x + w / 2.0;
|
||||
synth_lines.push(crate::types::PdfLine {
|
||||
x1: mid_x,
|
||||
y1: y,
|
||||
x2: mid_x,
|
||||
y2: y + h,
|
||||
page,
|
||||
});
|
||||
}
|
||||
}
|
||||
if synth_lines.len() >= 10 {
|
||||
let page_text: Vec<TextItem> = text_items
|
||||
.iter()
|
||||
.filter(|i| i.page == page)
|
||||
.cloned()
|
||||
.collect();
|
||||
let line_tables = detect_tables_from_lines(&page_text, &synth_lines, page);
|
||||
for table in &line_tables {
|
||||
for &idx in &table.item_indices {
|
||||
table_items.insert(idx);
|
||||
}
|
||||
let table_y = table.rows.first().copied().unwrap_or(0.0);
|
||||
let table_md = table_to_markdown(table);
|
||||
page_tables
|
||||
.entry(page)
|
||||
.or_default()
|
||||
.push((table_y, table_md));
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Merged-band retry: if we split into bands but found no tables in
|
||||
// any band, retry heuristic detection with all items as a single band.
|
||||
// This catches borderless tables whose text-column alignment was
|
||||
@@ -915,7 +980,7 @@ pub(crate) fn to_markdown_from_items_with_rects_and_lines(
|
||||
band_items.len(),
|
||||
was_split
|
||||
);
|
||||
let heuristic_tables = detect_tables(band_items, base_size, false);
|
||||
let heuristic_tables = detect_tables(band_items, base_size, page_has_columns);
|
||||
for table in &heuristic_tables {
|
||||
for &idx in &table.item_indices {
|
||||
if let Some(&page_idx) = band_index_map.get(idx) {
|
||||
|
||||
+26
-13
@@ -248,21 +248,34 @@ fn convert_text_items(items: Vec<crate::TextItem>) -> Vec<PyTextItem> {
|
||||
.collect()
|
||||
}
|
||||
|
||||
fn parse_page_regions(page_regions: Vec<(u32, Vec<Vec<f64>>)>) -> Vec<(u32, Vec<[f32; 4]>)> {
|
||||
fn parse_page_regions(
|
||||
page_regions: Vec<(u32, Vec<Vec<f64>>)>,
|
||||
) -> PyResult<Vec<(u32, Vec<[f32; 4]>)>> {
|
||||
page_regions
|
||||
.into_iter()
|
||||
.map(|(page, regions)| {
|
||||
let bboxes: Vec<[f32; 4]> = regions
|
||||
.iter()
|
||||
.map(|r| {
|
||||
if r.len() != 4 {
|
||||
[0.0, 0.0, 0.0, 0.0]
|
||||
} else {
|
||||
[r[0] as f32, r[1] as f32, r[2] as f32, r[3] as f32]
|
||||
}
|
||||
})
|
||||
.collect();
|
||||
(page, bboxes)
|
||||
let mut bboxes: Vec<[f32; 4]> = Vec::with_capacity(regions.len());
|
||||
for (idx, region) in regions.into_iter().enumerate() {
|
||||
if region.len() != 4 {
|
||||
return Err(PyValueError::new_err(format!(
|
||||
"Invalid region at page {page}, index {idx}: expected [x1, y1, x2, y2], got {} values",
|
||||
region.len()
|
||||
)));
|
||||
}
|
||||
let [x1, y1, x2, y2] = [region[0], region[1], region[2], region[3]];
|
||||
if !(x1.is_finite() && y1.is_finite() && x2.is_finite() && y2.is_finite()) {
|
||||
return Err(PyValueError::new_err(format!(
|
||||
"Invalid region at page {page}, index {idx}: coordinates must be finite numbers"
|
||||
)));
|
||||
}
|
||||
if x2 < x1 || y2 < y1 {
|
||||
return Err(PyValueError::new_err(format!(
|
||||
"Invalid region at page {page}, index {idx}: expected x2>=x1 and y2>=y1, got [{x1}, {y1}, {x2}, {y2}]"
|
||||
)));
|
||||
}
|
||||
bboxes.push([x1 as f32, y1 as f32, x2 as f32, y2 as f32]);
|
||||
}
|
||||
Ok((page, bboxes))
|
||||
})
|
||||
.collect()
|
||||
}
|
||||
@@ -424,7 +437,7 @@ fn extract_text_in_regions_bytes(
|
||||
data: &[u8],
|
||||
page_regions: Vec<(u32, Vec<Vec<f64>>)>,
|
||||
) -> PyResult<Vec<PyPageRegionTexts>> {
|
||||
let regions = parse_page_regions(page_regions);
|
||||
let regions = parse_page_regions(page_regions)?;
|
||||
let results = crate::extract_text_in_regions_mem(data, ®ions).map_err(to_py_err)?;
|
||||
Ok(convert_region_results(results))
|
||||
}
|
||||
|
||||
@@ -219,7 +219,7 @@ pub fn detect_tables(items: &[TextItem], base_font_size: f32, skip_body_font: bo
|
||||
body_font_low,
|
||||
body_font_high,
|
||||
);
|
||||
if body_candidates.len() >= 9 {
|
||||
if body_candidates.len() >= 6 {
|
||||
let regions = find_table_regions_strict(&body_candidates);
|
||||
log::debug!("body-font: {} strict regions found", regions.len());
|
||||
|
||||
@@ -241,7 +241,7 @@ pub fn detect_tables(items: &[TextItem], base_font_size: f32, skip_body_font: bo
|
||||
body_candidates.len()
|
||||
);
|
||||
|
||||
if region_items.len() < 9 {
|
||||
if region_items.len() < 6 {
|
||||
continue;
|
||||
}
|
||||
|
||||
@@ -801,7 +801,25 @@ fn has_table_like_content(cells: &[Vec<String>], mode: TableDetectionMode) -> bo
|
||||
// Bypass content check for wide tables (3+ columns) — text-only tables
|
||||
// (category lists, program descriptions) are legitimate if they passed
|
||||
// all structural validations (alignment, consistency, not key-value).
|
||||
pct_data > min_pct || num_cols >= 3
|
||||
// Also bypass for 2-column body-font tables with short cells (avg ≤40 chars),
|
||||
// which are likely definition/category lists, not paragraph text.
|
||||
if pct_data > min_pct || num_cols >= 3 {
|
||||
return true;
|
||||
}
|
||||
if num_cols == 2 && matches!(mode, TableDetectionMode::BodyFont) {
|
||||
let non_empty: Vec<usize> = cells
|
||||
.iter()
|
||||
.skip(1)
|
||||
.flat_map(|row| row.iter())
|
||||
.filter(|c| !c.trim().is_empty())
|
||||
.map(|c| c.trim().len())
|
||||
.collect();
|
||||
if !non_empty.is_empty() {
|
||||
let avg_len = non_empty.iter().sum::<usize>() / non_empty.len();
|
||||
return avg_len <= 25;
|
||||
}
|
||||
}
|
||||
false
|
||||
}
|
||||
|
||||
/// Check if a cell value looks like table data
|
||||
|
||||
@@ -243,9 +243,11 @@ pub fn detect_tables_from_lines(items: &[TextItem], lines: &[PdfLine], page: u32
|
||||
.map(|s| (s - mean_spacing).powi(2))
|
||||
.sum::<f32>()
|
||||
/ spacings.len() as f32;
|
||||
let cv = variance.sqrt() / mean_spacing; // coefficient of variation
|
||||
// CV < 0.05 means nearly identical spacing — chart grid
|
||||
if cv < 0.05 {
|
||||
let cv = variance.sqrt() / mean_spacing;
|
||||
// CV < 0.02 means nearly identical spacing — likely chart grid.
|
||||
// Spreadsheet-exported tables often have uniform rows (CV 0.03-0.05),
|
||||
// so we use a tighter threshold to avoid false negatives.
|
||||
if cv < 0.02 {
|
||||
return Vec::new();
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1232,6 +1232,55 @@ fn test_extract_regions_mem_not_a_pdf() {
|
||||
assert!(result.is_err(), "Non-PDF input should return an error");
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_extract_regions_mem_rotated_page_not_false_empty() {
|
||||
let buf = std::fs::read("tests/fixtures/tnagriculture_06_12.pdf").unwrap();
|
||||
let regions =
|
||||
extract_text_in_regions_mem(&buf, &[(0, vec![[0.0, 0.0, 1200.0, 1200.0]])]).unwrap();
|
||||
assert_eq!(regions.len(), 1);
|
||||
assert_eq!(regions[0].regions.len(), 1);
|
||||
let region = ®ions[0].regions[0];
|
||||
assert!(
|
||||
!region.text.trim().is_empty(),
|
||||
"Rotated page full-region extraction should not be empty"
|
||||
);
|
||||
assert!(
|
||||
!region.needs_ocr,
|
||||
"Rotated page with native text should not be flagged for OCR fallback"
|
||||
);
|
||||
assert!(
|
||||
region
|
||||
.text
|
||||
.contains("DISTRICT WISE PRODUCTION OF SPICES AND CONDIMENTS"),
|
||||
"Expected known title from rotated fixture in extracted region text"
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_collect_text_in_region_keeps_partial_overlap_items() {
|
||||
let item = make_text_item("EdgeWord", 100.0, 700.0, 12.0, 1);
|
||||
// Region intersects only the left edge of the item. Center x=124 falls
|
||||
// outside x=[95,120], so center-only containment would drop it.
|
||||
let text = pdf_inspector::collect_text_in_region(&[item], 95.0, 80.0, 120.0, 110.0, 800.0);
|
||||
assert!(
|
||||
text.contains("EdgeWord"),
|
||||
"Partially overlapping items should be retained in region extraction"
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_collect_text_in_region_uses_rtl_sorting() {
|
||||
let items = vec![
|
||||
make_text_item("بكم", 240.0, 700.0, 12.0, 1),
|
||||
make_text_item("مرحبا", 300.0, 700.0, 12.0, 1),
|
||||
];
|
||||
let text = pdf_inspector::collect_text_in_region(&items, 0.0, 0.0, 600.0, 800.0, 800.0);
|
||||
assert_eq!(
|
||||
text, "مرحبا بكم",
|
||||
"Region path should reuse RTL-aware line sorting"
|
||||
);
|
||||
}
|
||||
|
||||
// =========================================================================
|
||||
// Fast vs normal extraction comparison
|
||||
// =========================================================================
|
||||
|
||||
@@ -8,7 +8,9 @@ Department of the Treasury **Internal Revenue Service**
|
||||
|
||||
# and Report to Employer
|
||||
|
||||
**This publication contains:** **Form 4070A, Employee’s Daily Record of** Tips **Form 4070, Employee’s Report of Tips to** Employer
|
||||
### This publication contains:
|
||||
|
||||
**Form 4070A, Employee’s Daily Record of** Tips **Form 4070, Employee’s Report of Tips to** Employer
|
||||
|
||||
For the period
|
||||
|
||||
|
||||
@@ -6,9 +6,7 @@
|
||||
|
||||
8 4 Z E L L / L U R I E R E A L E S T A T E C E N T E R
|
||||
|
||||
**Table I: Cap rate correlations**
|
||||
|
||||
**Cap Rate Correlation With:*** **BBB Corp** **10-Year Bond Yield S&P Dividend** **Treasury (10-15 yr) Yield** Multifamily 0.187 0.771 0.068 Industrial-0.221 0.748-0.307 CBD Office-0.449 0.694-0.458 Retail-0.181 0.649-02.58
|
||||
**Table I: Cap rate correlations** **Cap Rate Correlation With:*** **BBB Corp** **10-Year Bond Yield S&P Dividend** **Treasury (10-15 yr) Yield** Multifamily 0.187 0.771 0.068 Industrial-0.221 0.748-0.307 CBD Office-0.449 0.694-0.458 Retail-0.181 0.649-02.58
|
||||
|
||||
* Based on 25 years of data for the 10-yrT & S&P DivYld; and 14 years for BBB.
|
||||
**Figure 1:** NCREIF cap rates vs. 10-yearTreasury
|
||||
@@ -34,9 +32,7 @@ R E V I E W 8 5
|
||||
|
||||
1982 1986 1990 1994 1998 2002 2006
|
||||
|
||||
**Table II: Correlationsofspreadsbypropertytype**
|
||||
|
||||
**Correlation of Cap Rate Spreads Over Treasury** **Multifamily Industrial CBD Office**
|
||||
**Table II: Correlationsofspreadsbypropertytype** **Correlation of Cap Rate Spreads Over Treasury** **Multifamily Industrial CBD Office**
|
||||
|
||||
||Multifamily|Industrial|CBD Office|
|
||||
|---|---|---|---|
|
||||
|
||||
@@ -26,19 +26,16 @@ S = Entropy (kJ/kg.K)
|
||||
|
||||
**Physical Properties**
|
||||
|
||||
Chemical Formula CCl2F2
|
||||
|Chemical Formula|CCl2F2|
|
||||
|---|---|
|
||||
|Molecular mass|120.91|
|
||||
|Boiling Point At one atmosphere|-29.75°C|
|
||||
|Critical Temperature|111.97°C|
|
||||
|Critical Pressure|4136 kPa|
|
||||
|Critical Density|565.0 kg/m|
|
||||
|Critical Volume|0.0018 m|
|
||||
|
||||
Molecular mass 120.91
|
||||
|
||||
Boiling Point-29.75°C At one atmosphere
|
||||
|
||||
Critical Temperature 111.97°C
|
||||
|
||||
Critical Pressure 4136 kPa
|
||||
|
||||
3 Critical Density 565.0 kg/m
|
||||
|
||||
Critical Volume 0.0018 m /kg
|
||||
/kg
|
||||
|
||||
l
|
||||
|
||||
|
||||
@@ -262,6 +262,13 @@ class TestExtractTextInRegions:
|
||||
assert results[0].page == 0
|
||||
assert results[1].page == 1
|
||||
|
||||
def test_malformed_region_raises_value_error(self):
|
||||
with pytest.raises(ValueError, match="Invalid region"):
|
||||
pdf_inspector.extract_text_in_regions(
|
||||
fixture_path("thermo-freon12.pdf"),
|
||||
[(0, [[0.0, 0.0, 600.0]])],
|
||||
)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Error handling
|
||||
|
||||
Reference in New Issue
Block a user