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Author SHA1 Message Date
Abimael Martell 2c26f58e0c fix(ocr): restore unclip_ratio 2.0 and recalibrate escalation for it
Supplying an explicit TextDetectionConfig suppresses OAROCR's
general-text-type overrides, so the staged detector was silently
running unclip 1.5 (the struct default) where the pre-split pipeline
ran 2.0 — tighter box expansion that risks clipping edge glyphs. Pin
unclip 2.0 explicitly and document that every override-set field must
be pinned when passing an explicit config.

The escalation threshold is coupled to unclip (expansion inflates
measured region heights ~15-20%), so it is recalibrated from fresh
measurements at 2.0: gain pages sit at 12.0-14.2px with 144+ regions,
the nearest non-gaining page above the region gate at 15.7px —
threshold moves 13 -> 15. A trace-level log records each page's
standard-pass median to keep future recalibration cheap. Trigger
tests updated to the measured values; quality re-verified end to end
(GT scores match pre-split main exactly on non-escalated docs;
escalation gains intact).
2026-08-17 20:06:54 -07:00
Abimael Martell c9a8da55ee Merge remote-tracking branch 'origin/main' into perf/ocr-adaptive-staged-engine 2026-08-17 20:05:31 -07:00
Abimael Martell c96c72f033 fix(ocr): return standard boxes directly after direct-escalation failure
Falling through to the adaptive branch would re-invoke the escalated
detector that just failed — repeating an OOM on a large dense page —
before settling on the standard boxes anyway.
2026-08-17 18:12:59 -07:00
Abimael Martell 009dc9d1a4 fix(ocr): address review — even-count median, escalation fallback, orientation note
- median_detection_height averages the two middle values for even-count
  region lists instead of taking the upper one, so borderline pages
  near the 13px escalation threshold are not skewed away from it.
- Direct escalated detection (renders over twice the standard limit)
  falls back to the standard pass on error, matching the adaptive
  branch, instead of failing the page outright.
- Document why OcrSpan::orientation_degrees is None: the combined
  pipeline's angle came from the text-line-orientation classifier,
  a model this engine never loads — it was structurally None before
  the staged split too; region rotation is carried by the polygon.
2026-08-17 18:08:13 -07:00
Abimael Martell d390d402a5 fix(detector): route masthead-over-scan pages to OCR (#412)
A full-page scan carrying a few text ops of genuine chrome (a newspaper
masthead, stamp, or date line) defeated the alphanum_low scan heuristic
— the chrome is real, diverse, decodable text — and cleared the bare
min_text_ops_per_page floor (3), so page_ocr_signals called the page
native while whole-document classification, whose pages_with_text floor
for image-bearing pages is max(10), correctly called it scanned. The
per-page and document-level paths silently disagreed (the drift #227
exists to prevent), and OCR auto mode returned almost nothing for a
third of a fully scanned document.

Align both per-page sites on classification's own floor: a template-
image page below min_text_ops_per_page.max(10) text ops routes to OCR
regardless of byte diversity, in page_ocr_signals and in the Mixed-type
routing clause of detect_from_document.

Tests pin the masthead case (form-wrapped full-page scan, ~4 diverse
chrome ops must route) and the letterhead counter-case (a real text
page over a background image must stay native).
2026-08-17 17:33:47 -07:00
Abimael Martell 84789459b1 feat(extractor): stamp items with the font family name, not the resource tag (#415)
* feat(extractor): stamp items with the font family name, not the resource tag

TextItem::font carried the page's font resource name ("F2", "T22") —
an arbitrary per-page tag — even though both content-stream parsers
already resolve the /BaseFont family name for bold/italic detection at
every item-creation site. Stamp that resolved family name instead
("ABCDEF+CMMI10", "Courier"), from a single item_font_name helper so
the two parsers cannot drift.

One deliberate carve-out, documented on the helper: resource names
using Distiller's CID convention (C2_0, C0_1) are kept as-is, because
text_utils::is_cid_font keys on that prefix for micro-gap joining and
the family name carries no CID marker to replace it.

Consumers that match on font names start working against real names:

- Code detection (is_monospace_font) previously never fired against
  opaque resource tags. It now does — so line classification also moves
  from any-item matching to a majority-by-characters rule
  (line_is_monospace): code lines are wholly monospace, while a lone
  URL or identifier styled in a mono face inside a prose line must not
  fence the surrounding sentence.
- Heading/body font grouping now merges resource aliases of the same
  family instead of treating them as distinct fonts.
- Positioned-item output (--items-json and the bindings) reports real
  face names.

Regression corpus: code-heavy manuals improve substantially (assembly
and C snippets previously emitted as prose now fence with line
structure preserved); remaining churn reviewed as improvements.

* fix(markdown): address review of font-name consumers

- Monotype is a foundry prefix on proportional faces (Monotype Corsiva,
  Monotype Garamond); it must not satisfy is_monospace_font's generic
  "mono" token. Regression tests pin both directions.
- Flush the pending code block before inserting a positioned table or
  image, so a block that falls between two code lines cannot be emitted
  ahead of code that precedes it in reading order; a code line after
  the block reopens a new fence naturally.

* fix(markdown): emit sub-3-char mono fragments as plain text, not fences

A lone registered-trademark glyph or stray bullet set in a mono face is
not code; a fenced block containing one character reads as noise.

* fix(markdown): font-based code blocks open only at paragraph boundaries

HTML-to-PDF producers smear an inline code literal's mono style across
whole wrapped lines, so a prose paragraph can alternate body and mono
fonts line by line. Fencing those lines cut sentences in three: prose
head, fenced middle, prose tail. A mono-set line that continues an open
prose paragraph now stays prose; font-based blocks open at paragraph
boundaries (or continue an open block), and struct-tree Code roles are
honored unconditionally.

* refactor(markdown): drop paragraph-flush branch made unreachable by the boundary gate

The enclosing guard proves in_paragraph is false, so the nested flush
could never run; the guard and mono check collapse into one condition.
2026-08-17 17:21:24 -07:00
Abimael Martell bc414bd08d perf(ocr): adaptive detection escalation and parallel staged engine
Three structural limits in the OCR engine, found benchmarking against
other parsers, each addressed here:

1. Detection resolution. The backend downscales every page so its
   longest side fits 960px before text detection. A broadsheet render
   loses over 80% of its resolution, making body print ~2px tall —
   invisible to the detection model regardless of render DPI, since
   recognition crops come from the full-resolution render but detection
   never sees the text. Detection now runs at 960 and escalates to 2560
   only when the standard pass proves the page is dense fine print
   (page was downscaled, >=80 regions, median region height under 13px
   at detection scale — measured margins separate gaining pages at
   9.9-12.0px from non-gaining pages at 12.2px+). Renders more than
   twice the standard limit skip the doomed standard pass entirely.

2. Session serialization. oar-ocr guards each ONNX session behind a
   mutex (pool size is fixed at one), so concurrent predict calls
   serialize and added intra-op threads go to waste — measured, 12
   threads run 2.4x slower than 4. The engine now builds one worker
   (detector + recognizer sessions) per cores/4 capped at 3, each with
   2 intra-op threads, and fans pages across them via a sized rayon
   pool. A new OcrEngine::preferred_page_concurrency hint lets the
   pipeline size page batches at three waves per worker, replacing the
   fixed 4-page chunks that starved workers at batch barriers.

3. Escalation double-cost. The engine is restaged onto oar-ocr's own
   public components — detect, sort (sort_quad_boxes), crop
   (TextCroppingProcessor, rotation-aware), recognize — as separate
   calls instead of the combined predict, with output verified
   byte-identical across an 8-document corpus. An escalated page now
   reruns only detection; recognition runs once, on the final region
   set. Recognition stays one crop per call: batching pads every crop
   to the widest member, and even width-sorted batches measured 2-3x
   slower on CPU (ONNX Runtime re-plans kernels per input shape).

Escalation lifts ground-truth word recall on dense fine print from
0.678 to 0.895 with no change on ordinary scans, which keep first-pass
speed and quality; a 15-page scan drops from 9.4s to 8.0s end to end.
2026-08-17 13:45:55 -07:00
9 changed files with 768 additions and 83 deletions
+150 -12
View File
@@ -403,8 +403,15 @@ pub(crate) fn detect_from_document(
&& !(analysis.has_decodable_text_fonts && analysis.text_operator_count >= 10);
let looks_like_scan =
analysis.image_count <= 1 && analysis.text_operator_count < 50 && alphanum_low;
// A template-image page below the `pages_with_text` floor is
// a scan with incidental chrome (masthead, stamp, date line)
// even when that chrome is diverse, decodable text — keep
// this in sync with `page_ocr_signals`.
let sparse_text_over_scan = analysis.has_template_image
&& analysis.text_operator_count < config.min_text_ops_per_page.max(10);
if (analysis.has_template_image && looks_like_scan)
|| analysis.has_vector_text
|| sparse_text_over_scan
|| (analysis.text_operator_count < config.min_text_ops_per_page
&& analysis.has_images)
{
@@ -1795,17 +1802,24 @@ pub(crate) fn analyze_page_images(doc: &Document, page_id: ObjectId) -> (bool, u
/// low alphanumeric diversity in raw string operands (unless decodable
/// CID/ToUnicode fonts explain that away) — the gate used for
/// `pages_with_template_images` and Mixed-type per-page routing.
/// 2. Insufficient real text volume, using `DetectionConfig::default()`'s
/// `min_text_ops_per_page` (3) — the same threshold Mixed-type per-page
/// routing applies via `text_operator_count < config.min_text_ops_per_page
/// && has_images` (simplified here since a template image implies
/// `has_images`). Deliberately *not* the higher `effective_min_ops`
/// floor (`min_text_ops_per_page.max(10)`) that whole-document
/// `PdfType::ImageBased`/`Scanned` classification uses for
/// `pages_with_text` — that's a cross-page aggregate decision this
/// per-page function has no way to replicate exactly, and the lower
/// per-page threshold is the one a single page's own signals can
/// actually agree with.
/// 2. Insufficient real text volume, using the same `effective_min_ops`
/// floor (`min_text_ops_per_page.max(10)`) that `pages_with_text`
/// applies to image-bearing pages. That floor is a per-page judgment,
/// not part of the cross-page aggregate: classification counts a
/// template-image page with fewer ops as textless and routes it to OCR,
/// so this function must agree. The lower bare threshold (3) let a
/// full-page scan carrying a small native masthead — a newspaper
/// header, stamp, or date line of ~4 diverse, decodable text ops —
/// extract as "a text page" here while whole-document classification
/// called the same page scanned, silently dropping the page body from
/// OCR routing. `alphanum_low` can't catch that case: masthead chrome
/// is real text, so its byte diversity is high.
///
/// This function always evaluates against `DetectionConfig::default()` —
/// it has no config parameter, and the per-page extraction path that calls
/// it never carries one. A caller passing a custom `min_text_ops_per_page`
/// to `detect_from_document` affects whole-document detection only; the
/// two paths agree under the default configuration.
///
/// `has_vector_text` is true when a page has vector-outlined text (glyphs
/// drawn as paths rather than shown via text-showing operators) —
@@ -1827,7 +1841,7 @@ pub(crate) fn page_ocr_signals(doc: &Document, page_id: ObjectId) -> (bool, bool
let looks_like_scan =
analysis.image_count <= 1 && analysis.text_operator_count < 50 && alphanum_low;
let insufficient_text =
analysis.text_operator_count < DetectionConfig::default().min_text_ops_per_page;
analysis.text_operator_count < DetectionConfig::default().min_text_ops_per_page.max(10);
looks_like_scan || insufficient_text
};
@@ -2995,6 +3009,130 @@ mod tests {
);
}
// ---------- masthead-over-scan tests: template image + sparse chrome ----------
/// Builds a page whose only image is a full-page scan inside a Form
/// XObject, plus `masthead_ops` native text-show ops of diverse,
/// decodable chrome (newspaper masthead / date line style).
fn masthead_scan_page(masthead_lines: &[&str]) -> (Document, ObjectId) {
use lopdf::dictionary;
let mut doc = Document::with_version("1.4");
let pages_id = doc.new_object_id();
let page_id = doc.new_object_id();
let image_id = doc.add_object(Object::Stream(lopdf::Stream::new(
dictionary! {
"Type" => "XObject",
"Subtype" => Object::Name(b"Image".to_vec()),
"Width" => Object::Integer(1500),
"Height" => Object::Integer(2383),
},
Vec::new(),
)));
let form_id = doc.add_object(Object::Stream(lopdf::Stream::new(
dictionary! {
"Type" => "XObject",
"Subtype" => Object::Name(b"Form".to_vec()),
"Resources" => dictionary! {
"XObject" => dictionary! {
"Im0" => Object::Reference(image_id),
},
},
},
b"1500 0 0 2383 0 0 cm /Im0 Do".to_vec(),
)));
let font_id = doc.add_object(dictionary! {
"Type" => "Font",
"Subtype" => Object::Name(b"Type1".to_vec()),
"BaseFont" => Object::Name(b"Helvetica".to_vec()),
});
let mut content = b"q /Fm0 Do Q BT /F1 12 Tf ".to_vec();
for line in masthead_lines {
content.extend_from_slice(format!("({line}) Tj ").as_bytes());
}
content.extend_from_slice(b"ET");
let content_id =
doc.add_object(Object::Stream(lopdf::Stream::new(dictionary! {}, content)));
doc.objects.insert(
page_id,
Object::Dictionary(dictionary! {
"Type" => "Page",
"Parent" => Object::Reference(pages_id),
"MediaBox" => vec![0.into(), 0.into(), 1500.into(), 2383.into()],
"Resources" => dictionary! {
"Font" => dictionary! { "F1" => Object::Reference(font_id) },
"XObject" => dictionary! { "Fm0" => Object::Reference(form_id) },
},
"Contents" => Object::Reference(content_id),
}),
);
doc.objects.insert(
pages_id,
Object::Dictionary(dictionary! {
"Type" => "Pages",
"Kids" => vec![Object::Reference(page_id)],
"Count" => Object::Integer(1),
}),
);
(doc, page_id)
}
#[test]
fn test_masthead_over_form_wrapped_scan_needs_ocr() {
// A full-page scan wrapped in a Form XObject with ~4 ops of real,
// diverse masthead text. `alphanum_low` can't flag it (the chrome is
// genuine text), so the sparse-text floor must: without OCR the page
// body is silently lost while classification calls the page scanned.
let (doc, page_id) = masthead_scan_page(&[
"18",
"FINANCIAL EXPRESS",
"WWW.FINANCIALEXPRESS.COM",
"FRIDAY, DECEMBER 13, 2024",
]);
let analysis = analyze_page_content(&doc, page_id);
assert!(
analysis.has_template_image,
"sanity: full-page image inside the form must be found"
);
assert!(
analysis.unique_alphanum_chars >= 10,
"sanity: masthead text is diverse, alphanum_low cannot fire"
);
let (needs_ocr, _) = page_ocr_signals(&doc, page_id);
assert!(
needs_ocr,
"template image + text below the pages_with_text floor is a scan"
);
}
#[test]
fn test_text_page_over_background_image_stays_native() {
// Counterpart: a real text page over a full-page background image
// (letterhead/watermark) has enough text ops to clear the
// `pages_with_text` floor and must NOT be routed to OCR.
let lines: Vec<String> = (0..12)
.map(|i| format!("Paragraph line {i} with ordinary body text"))
.collect();
let refs: Vec<&str> = lines.iter().map(String::as_str).collect();
let (doc, page_id) = masthead_scan_page(&refs);
let analysis = analyze_page_content(&doc, page_id);
assert!(
analysis.has_template_image,
"sanity: background image found"
);
assert!(
analysis.text_operator_count >= 10,
"sanity: body text clears the floor"
);
let (needs_ocr, _) = page_ocr_signals(&doc, page_id);
assert!(
!needs_ocr,
"a text page with a background image must stay native"
);
}
// ---------- P2 tests: Form XObject font traversal ----------
#[test]
+20 -4
View File
@@ -561,7 +561,11 @@ pub(crate) fn extract_page_text_items(
y,
width,
height: rendered_size,
font: current_font.clone(),
font: crate::extractor::fonts::item_font_name(
&current_font,
base_font,
)
.to_string(),
font_size: rendered_size,
page: page_num,
is_bold: is_bold_font(base_font) || desc_bold,
@@ -745,7 +749,11 @@ pub(crate) fn extract_page_text_items(
y,
width,
height: rendered_size,
font: current_font.clone(),
font: crate::extractor::fonts::item_font_name(
&current_font,
base_font,
)
.to_string(),
font_size: rendered_size,
page: page_num,
is_bold: is_bold_font(base_font) || desc_bold,
@@ -852,7 +860,11 @@ pub(crate) fn extract_page_text_items(
y,
width,
height: rendered_size,
font: current_font.clone(),
font: crate::extractor::fonts::item_font_name(
&current_font,
base_font,
)
.to_string(),
font_size: rendered_size,
page: page_num,
is_bold: is_bold_font(base_font) || desc_bold,
@@ -1005,7 +1017,11 @@ pub(crate) fn extract_page_text_items(
y,
width,
height: rendered_size,
font: current_font.clone(),
font: crate::extractor::fonts::item_font_name(
&current_font,
base_font,
)
.to_string(),
font_size: rendered_size,
page: page_num,
is_bold: is_bold_font(base_font) || desc_bold,
+31
View File
@@ -225,6 +225,26 @@ pub(crate) fn build_type3_scales(
scales
}
/// The name a `TextItem` carries for its font: the `/BaseFont` family name
/// ("ABCDEF+CMMI10"), which identifies the actual face, rather than the
/// arbitrary per-page resource tag ("F2").
///
/// Exception: resource names using Distiller's CID convention (`C2_0`,
/// `C0_1`) are kept as-is — `text_utils::is_cid_font` keys on that prefix
/// for micro-gap joining, and the family name carries no CID marker to
/// replace it. This is a known, deliberate wart: `TextItem::font` is the
/// face name except for this one producer convention. The clean fix is an
/// explicit CID flag on `TextItem`, which touches its ~29 construction
/// sites; do that migration when `TextItem` next changes shape, and delete
/// this carve-out with it.
pub(crate) fn item_font_name<'a>(resource_name: &'a str, base_font: &'a str) -> &'a str {
if crate::text_utils::is_cid_font(resource_name) {
resource_name
} else {
base_font
}
}
/// Parse font widths from a font dictionary, dispatching by Subtype
pub(crate) fn parse_font_widths(
doc: &Document,
@@ -1664,6 +1684,17 @@ fn score_text(text: &str) -> i32 {
#[cfg(test)]
mod tests {
#[test]
fn item_font_name_prefers_family_over_resource_tag() {
use super::item_font_name;
assert_eq!(item_font_name("F2", "ABCDEF+CMMI10"), "ABCDEF+CMMI10");
assert_eq!(item_font_name("T22", "Times-Roman"), "Times-Roman");
// Distiller CID-convention resources keep the resource name:
// is_cid_font keys on the C2_/C0_ prefix for micro-gap joining.
assert_eq!(item_font_name("C2_0", "ABCDEE+SimSun"), "C2_0");
assert_eq!(item_font_name("C0_1", "ABCDEE+MSMincho"), "C0_1");
}
#[test]
fn type3_scale_resolves_indirect_matrix_and_bbox_numbers() {
use lopdf::{dictionary, Document, Object};
+10 -2
View File
@@ -620,7 +620,11 @@ fn extract_form_xobject_text_inner(
y,
width,
height: rendered_size,
font: current_font.clone(),
font: crate::extractor::fonts::item_font_name(
&current_font,
base_font,
)
.to_string(),
font_size: rendered_size,
page: page_num,
is_bold: is_bold_font(base_font) || desc_bold,
@@ -775,7 +779,11 @@ fn extract_form_xobject_text_inner(
y,
width,
height: rendered_size,
font: current_font.clone(),
font: crate::extractor::fonts::item_font_name(
&current_font,
base_font,
)
.to_string(),
font_size: rendered_size,
page: page_num,
is_bold: is_bold_font(base_font) || desc_bold,
+44
View File
@@ -203,9 +203,42 @@ pub(crate) fn is_code_like(text: &str) -> bool {
false
}
/// True when a line's text is essentially all monospace (≥90% by character
/// count). Code lines are wholly monospace; anything less is prose carrying
/// mono-styled fragments — a URL sidebar, or a sentence quoting an inline
/// code literal — and fencing it would split paragraphs mid-sentence.
/// Any-item matching was safe only while items carried opaque font resource
/// names that never matched the monospace patterns; items now carry real
/// family names.
pub(crate) fn line_is_monospace(line: &crate::types::TextLine) -> bool {
let mut monospace_chars = 0usize;
let mut total_chars = 0usize;
for item in &line.items {
let text = item.text.trim();
let chars = text.chars().count();
total_chars += chars;
// Hyperlinks and underlined text set in a mono face are link
// styling, not code — a URL sidebar must not fence lyric lines.
let looks_like_link = item.is_underline
|| matches!(item.item_type, crate::types::ItemType::Link(_))
|| text.contains("://")
|| text.starts_with("www.");
if is_monospace_font(&item.font) && !looks_like_link {
monospace_chars += chars;
}
}
total_chars > 0 && monospace_chars * 10 >= total_chars * 9
}
/// Check if font name indicates monospace
pub(crate) fn is_monospace_font(font_name: &str) -> bool {
let lower = font_name.to_lowercase();
// "Monotype" is a foundry prefix on proportional faces (Monotype
// Corsiva, Monotype Garamond) — it must not satisfy the generic "mono"
// token below.
if lower.contains("monotype") {
return false;
}
let patterns = [
"courier",
"consolas",
@@ -230,6 +263,17 @@ pub(crate) fn is_monospace_font(font_name: &str) -> bool {
mod tests {
use super::*;
#[test]
fn monotype_foundry_faces_are_not_monospace() {
// "Monotype" is a foundry prefix on proportional faces; the generic
// "mono" token must not classify them as code fonts.
assert!(!is_monospace_font("MonotypeCorsiva"));
assert!(!is_monospace_font("ABCDEF+Monotype-Garamond"));
assert!(is_monospace_font("RobotoMono-Regular"));
assert!(is_monospace_font("PTMono"));
assert!(is_monospace_font("Courier"));
}
#[test]
fn format_list_item_plain_bullet() {
assert_eq!(format_list_item("● Item"), "- Item");
+52 -28
View File
@@ -11,9 +11,7 @@ use super::analysis::{
detect_header_level, font_size_rarity, has_dot_leaders, is_heading_fragment, is_toc_entry_line,
is_toc_marker_heading,
};
use super::classify::{
format_list_item, is_caption_line, is_list_item, is_monospace_font, starts_with_bullet_marker,
};
use super::classify::{format_list_item, is_caption_line, is_list_item, starts_with_bullet_marker};
use super::heading::classify_heading_sequences;
use super::postprocess::clean_markdown;
use super::preprocess::{merge_drop_caps, merge_heading_lines};
@@ -771,7 +769,27 @@ pub(super) fn to_markdown_from_lines_with_tables_and_images(
let mut in_list = false;
let mut in_paragraph = false;
let mut last_list_x: Option<f32> = None;
// Code lines accumulate here and the fence is emitted only when the
// block flushes with content — an empty ``` ``` pair can never appear.
fn flush_code_block(output: &mut String, pending_code: &mut String) {
let trimmed = pending_code.trim();
// A fragment too short to be code — a lone ® or stray glyph set in
// a mono face — reads better as plain text than as a fenced block.
if trimmed.chars().count() < 3 {
if !trimmed.is_empty() {
output.push_str(trimmed);
output.push_str("\n\n");
}
} else {
output.push_str("```\n");
output.push_str(pending_code);
output.push_str("```\n");
}
pending_code.clear();
}
let mut in_code_block = false;
let mut pending_code = String::new();
let mut prev_had_dot_leaders = false;
let mut paragraph_in_wrapped_bold_run = false;
let mut toc_suppress_page: Option<u32> = None;
@@ -805,7 +823,7 @@ pub(super) fn to_markdown_from_lines_with_tables_and_images(
// Flush current page's remaining tables and images
if current_page > 0 {
if in_code_block {
output.push_str("```\n");
flush_code_block(&mut output, &mut pending_code);
in_code_block = false;
}
flush_page_tables_and_images(
@@ -867,6 +885,14 @@ pub(super) fn to_markdown_from_lines_with_tables_and_images(
PositionedBlockKind::Image => inserted_images.contains(&(current_page, idx)),
};
if positioned_block_precedes_line(block, line) && !already_inserted {
// Code lines buffer until their block closes; flush them
// first so this block cannot jump ahead of code that
// precedes it in reading order. A code line after the
// block reopens a new fence naturally.
if in_code_block {
flush_code_block(&mut output, &mut pending_code);
in_code_block = false;
}
if in_paragraph {
output.push_str("\n\n");
in_paragraph = false;
@@ -937,15 +963,22 @@ pub(super) fn to_markdown_from_lines_with_tables_and_images(
// These should be on their own line followed by a paragraph break
let struct_role = struct_roles.and_then(|roles| resolve_line_struct_role(line, roles));
// Determine if this line is code (struct-tree or font-based) for block accumulation
// Determine if this line is code (struct-tree or font-based) for
// block accumulation. Font-based detection only opens a block at a
// paragraph boundary: a mono-set line that continues an open prose
// paragraph is the producer smearing an inline code literal's style
// across a wrapped line (HTML-to-PDF exports do this), and fencing
// it would cut the sentence in three.
let is_code_line = struct_role
.as_ref()
.is_some_and(|r| matches!(r, StructRole::Code))
|| (options.detect_code && line.items.iter().any(|i| is_monospace_font(&i.font)));
|| (options.detect_code
&& (in_code_block || !in_paragraph)
&& super::classify::line_is_monospace(line));
// Close code block when transitioning to non-code
if in_code_block && !is_code_line {
output.push_str("```\n");
flush_code_block(&mut output, &mut pending_code);
in_code_block = false;
}
@@ -1179,12 +1212,9 @@ pub(super) fn to_markdown_from_lines_with_tables_and_images(
in_paragraph = false;
paragraph_in_wrapped_bold_run = false;
}
if !in_code_block {
output.push_str("```\n");
in_code_block = true;
}
output.push_str(plain_trimmed);
output.push('\n');
in_code_block = true;
pending_code.push_str(plain_trimmed);
pending_code.push('\n');
continue;
}
@@ -1209,7 +1239,7 @@ pub(super) fn to_markdown_from_lines_with_tables_and_images(
// Close any trailing code block
if in_code_block {
output.push_str("```\n");
flush_code_block(&mut output, &mut pending_code);
}
// Flush current page and any remaining pages with tables/images
@@ -1370,7 +1400,7 @@ pub fn to_markdown_from_lines(lines: Vec<TextLine>, options: MarkdownOptions) ->
&& !is_toc_entry_line(plain_trimmed)
&& !is_heading_fragment(plain_trimmed)
&& toc_suppress_page != Some(line.page)
&& !(options.detect_code && line.items.iter().any(|i| is_monospace_font(&i.font)))
&& !(options.detect_code && super::classify::line_is_monospace(line))
{
let line_font_size = line.items.first().map(|i| i.font_size).unwrap_or(base_size);
if let Some(header_level) = detect_header_level(
@@ -1471,19 +1501,13 @@ pub fn to_markdown_from_lines(lines: Vec<TextLine>, options: MarkdownOptions) ->
}
}
// Detect code blocks by font
if options.detect_code {
let is_mono = line.items.iter().any(|i| is_monospace_font(&i.font));
if is_mono {
if in_paragraph {
output.push_str("\n\n");
in_paragraph = false;
paragraph_in_wrapped_bold_run = false;
}
// Use plain text for code blocks
output.push_str(&format!("```\n{}\n```\n", plain_trimmed));
continue;
}
// Detect code blocks by font. Only at a paragraph boundary — a
// mono-set line continuing an open prose paragraph is an inline
// code literal's style smeared across a wrapped line, not code.
if options.detect_code && !in_paragraph && super::classify::line_is_monospace(line) {
// Use plain text for code blocks
output.push_str(&format!("```\n{}\n```\n", plain_trimmed));
continue;
}
// Regular text - join lines within same paragraph with space
+7
View File
@@ -237,6 +237,13 @@ pub trait OcrEngine: Send + Sync {
pages: &[RenderedPage],
options: &OcrOptions,
) -> Result<Vec<OcrPage>, Self::Error>;
/// Number of pages this engine can process concurrently in one
/// `recognize` call. The pipeline sizes its page batches from this so a
/// parallel engine is not starved by small chunks; `1` means sequential.
fn preferred_page_concurrency(&self) -> usize {
1
}
}
#[cfg(test)]
+429 -36
View File
@@ -1,11 +1,14 @@
//! PP-OCRv6 Small implementation backed by OAR and ONNX Runtime.
use std::path::PathBuf;
use std::sync::Arc;
use std::time::Instant;
use image::RgbImage;
use oar_ocr::core::config::onnx::OrtSessionConfig;
use oar_ocr::oarocr::{OAROCRBuilder, OAROCR};
use oar_ocr::domain::tasks::TextDetectionConfig;
use oar_ocr::oarocr::{EdgeProcessor, TextCroppingProcessor};
use oar_ocr::predictors::{TextDetectionPredictor, TextRecognitionPredictor};
use oar_ocr::processors::BoundingBox;
use thiserror::Error;
@@ -70,17 +73,170 @@ pub enum OarOcrError {
Backend(#[from] oar_ocr::core::OCRError),
}
/// CPU PP-OCRv6 Small engine using OAR's detection and recognition pipeline.
/// Standard detection input cap. PP-OCR detection resizes each page so its
/// longest side fits this before inference; it is the PaddleOCR default and
/// is sufficient for ordinary body text at 150 DPI.
const DETECTION_LIMIT_STANDARD: u32 = 960;
/// Escalated detection input cap for dense fine-print pages. Beyond this the
/// measured recall plateaus while inference cost keeps growing.
const DETECTION_LIMIT_ESCALATED: u32 = 2560;
/// Hard ceiling protecting detection from out-of-memory on giant renders.
const DETECTION_MAXIMUM_SIDE: u32 = 4000;
/// Escalate only for pages dense with small text: at least this many detected
/// regions in the standard pass...
const ESCALATION_MINIMUM_REGIONS: usize = 80;
/// ...whose median height, at detection scale, is below this. Calibrated at
/// `unclip_ratio` 2.0 (the expansion inflates measured heights, so this
/// constant is coupled to [`detection_config`]): dense fine-print pages that
/// gain from escalation measure 12.014.2 px with 144+ regions; the nearest
/// non-gaining page above the region gate (an engineering drawing) measures
/// 15.7 px, and prose/typewriter pages measure 14.5 px+ with too few
/// regions to qualify at all.
const ESCALATION_MAXIMUM_MEDIAN_HEIGHT: f32 = 15.0;
/// One worker's model sessions: a standard-limit detector plus a recognizer,
/// and that worker's own lazily built escalated-limit detector.
/// Staged (detect, crop, recognize as separate calls) rather than OAROCR's
/// combined `predict` so an escalated page replaces only its detection pass —
/// recognition runs exactly once, on the final region set.
struct OcrWorker {
detector: TextDetectionPredictor,
recognizer: TextRecognitionPredictor,
/// Built on this worker's first dense fine-print page. `None` inside the
/// cell records a failed build so it is not retried per page.
escalated: std::sync::OnceLock<Option<TextDetectionPredictor>>,
}
/// CPU PP-OCRv6 Small engine using OAR's detection and recognition components.
///
/// Construction accepts only [`ModelPaths`] that have already passed
/// pdf-inspector's manifest size and SHA-256 verification. OAR's independent
/// model auto-download feature is deliberately not enabled.
#[derive(Debug)]
pub struct OarOcrEngine {
pipeline: OAROCR,
workers: Vec<OcrWorker>,
detection_path: PathBuf,
intra_threads: usize,
/// Present only when more than one worker exists; sized to match.
pool: Option<rayon::ThreadPool>,
model: ModelIdentity,
}
impl std::fmt::Debug for OarOcrEngine {
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
f.debug_struct("OarOcrEngine")
.field("workers", &self.workers.len())
.field("parallel", &self.pool.is_some())
.field("model", &self.model)
.finish()
}
}
/// Pages processed concurrently: one OAROCR pipeline (and its ONNX sessions)
/// per worker, because oar-ocr serializes each session behind a mutex.
/// Measured on CPU: workers beyond 3 stop scaling (memory-bandwidth bound)
/// and each worker is fastest with 2 intra-op threads.
fn pipeline_concurrency() -> usize {
let cores = std::thread::available_parallelism()
.map(std::num::NonZeroUsize::get)
.unwrap_or(1);
(cores / 4).clamp(1, 3)
}
fn intra_threads_per_pipeline(concurrency: usize) -> usize {
let cores = std::thread::available_parallelism()
.map(std::num::NonZeroUsize::get)
.unwrap_or(1);
if concurrency > 1 {
2
} else {
cores.min(4)
}
}
/// True when a standard-limit detection pass over a downscaled page shows
/// dense, small text: the page deserves a second pass at the escalated limit.
fn should_escalate_detection(
median_detection_height: f32,
region_count: usize,
downscale: f32,
) -> bool {
downscale < 1.0
&& region_count >= ESCALATION_MINIMUM_REGIONS
&& median_detection_height < ESCALATION_MAXIMUM_MEDIAN_HEIGHT
}
/// Median detected-region height in detection-input pixels: original-image
/// heights multiplied by the downscale detection applied.
fn median_detection_height(heights: &mut [f32], downscale: f32) -> f32 {
if heights.is_empty() {
return f32::MAX;
}
heights.sort_by(|a, b| a.partial_cmp(b).unwrap_or(std::cmp::Ordering::Equal));
let middle = heights.len() / 2;
let median = if heights.len().is_multiple_of(2) {
(heights[middle - 1] + heights[middle]) / 2.0
} else {
heights[middle]
};
median * downscale
}
/// Detection preprocessing config at a given input cap.
///
/// Supplying an explicit config suppresses OAROCR's "general" text-type
/// overrides, so every field the override would have set must be pinned
/// here to match what the combined pipeline ran with before the staged
/// split: score 0.3 and box 0.6 (equal to [`TextDetectionConfig`]'s
/// defaults) and unclip 2.0 (the default is 1.5 — leaving it would
/// silently shrink detection-box expansion and risk clipping edge glyphs).
fn detection_config(detection_limit: u32) -> TextDetectionConfig {
TextDetectionConfig {
limit_side_len: Some(detection_limit),
limit_type: Some(oar_ocr::processors::LimitType::Max),
max_side_len: Some(DETECTION_MAXIMUM_SIDE),
unclip_ratio: 2.0,
..Default::default()
}
}
fn build_detector(
detection: &std::path::Path,
detection_limit: u32,
intra_threads: usize,
) -> Result<TextDetectionPredictor, OarOcrError> {
Ok(TextDetectionPredictor::builder()
.with_config(detection_config(detection_limit))
.with_ort_config(ocr_session_config(intra_threads))
.build(detection)?)
}
fn build_workers(
detection: &std::path::Path,
recognition: &std::path::Path,
dictionary: &std::path::Path,
count: usize,
intra_threads: usize,
) -> Result<Vec<OcrWorker>, OarOcrError> {
let mut workers = Vec::with_capacity(count);
for _ in 0..count {
let detector = build_detector(detection, DETECTION_LIMIT_STANDARD, intra_threads)?;
let recognizer = TextRecognitionPredictor::builder()
.dict_path(dictionary)
.with_ort_config(ocr_session_config(intra_threads))
.build(recognition)?;
workers.push(OcrWorker {
detector,
recognizer,
escalated: std::sync::OnceLock::new(),
});
}
Ok(workers)
}
impl OarOcrEngine {
/// Loads PP-OCRv6 Small from a resolved, verified model set.
pub fn from_models(models: &ModelPaths) -> Result<Self, OarOcrError> {
@@ -89,36 +245,169 @@ impl OarOcrEngine {
let recognition = required_model(models, ModelArtifactKind::TextRecognition)?;
let dictionary = required_model(models, ModelArtifactKind::CharacterDictionary)?;
let pipeline = OAROCRBuilder::new(detection, recognition, dictionary)
.ort_session(ocr_session_config())
// Document line crops often have very different widths. Keeping
// CPU recognition batches at one avoids padding every crop to the
// widest line, reducing both inference work and peak memory.
.region_batch_size(1)
.build()?;
let concurrency = pipeline_concurrency();
let intra_threads = intra_threads_per_pipeline(concurrency);
let workers = build_workers(
detection,
recognition,
dictionary,
concurrency,
intra_threads,
)?;
let pool = if concurrency > 1 {
rayon::ThreadPoolBuilder::new()
.num_threads(concurrency)
.build()
.ok()
} else {
None
};
let model = ModelIdentity::new(models.manifest_id(), models.revision());
Ok(Self { pipeline, model })
Ok(Self {
workers,
detection_path: detection.to_path_buf(),
intra_threads,
pool,
model,
})
}
/// This worker's escalated-limit detector, built on first use.
fn escalated_detector<'w>(&self, worker: &'w OcrWorker) -> Option<&'w TextDetectionPredictor> {
worker
.escalated
.get_or_init(|| {
match build_detector(
&self.detection_path,
DETECTION_LIMIT_ESCALATED,
self.intra_threads,
) {
Ok(detector) => Some(detector),
Err(error) => {
log::warn!(
"escalated OCR detection unavailable, keeping standard pass: {error}"
);
None
}
}
})
.as_ref()
}
/// Detects text regions for one page: a standard-limit pass first, then —
/// for pages the standard limit demonstrably under-resolves — a second
/// pass at the escalated limit whose boxes replace the first. Pages whose
/// render dwarfs even the escalated limit skip the standard pass outright.
fn detect_boxes(
&self,
page: &RenderedPage,
image: &Arc<RgbImage>,
worker: &OcrWorker,
) -> Result<Vec<BoundingBox>, OarOcrError> {
let longest_side = page.width().max(page.height()) as f32;
// A page more than twice the standard limit loses over half its
// resolution before detection even runs; go straight to the escalated
// detector instead of paying a doomed standard pass.
if longest_side > (DETECTION_LIMIT_STANDARD * 2) as f32 {
if let Some(escalated) = self.escalated_detector(worker) {
log::debug!(
"page {}: direct escalated detection (render {longest_side}px)",
page.page(),
);
match detect_with(escalated, image, page.page()) {
Ok(boxes) => return Ok(boxes),
Err(error) => {
// Same degradation as the adaptive branch below: a
// failing escalated pass falls back to standard
// detection instead of failing the page outright.
// Return the standard boxes directly — the adaptive
// trigger would only re-invoke the detector that
// just failed (repeating an OOM on a dense page).
log::warn!(
"page {}: direct escalated detection failed, using standard pass: {error}",
page.page()
);
return detect_with(&worker.detector, image, page.page());
}
}
}
}
let detections = detect_with(&worker.detector, image, page.page())?;
// Dense fine-print pages (broadsheets, pricing sheets) lose most of
// their text when detection downscales them to the standard limit.
// When the standard pass shows many regions of tiny detection-scale
// height, rerun detection at the escalated limit.
let downscale = (DETECTION_LIMIT_STANDARD as f32 / longest_side).min(1.0);
let mut heights: Vec<f32> = detections.iter().map(polygon_height).collect();
let median = median_detection_height(&mut heights, downscale);
log::trace!(
"page {}: standard pass {} regions, median height {:.1}px at detection scale",
page.page(),
detections.len(),
median
);
if should_escalate_detection(median, detections.len(), downscale) {
log::debug!(
"page {}: escalating detection ({} regions, median height {:.1}px at detection scale)",
page.page(),
detections.len(),
median
);
if let Some(escalated) = self.escalated_detector(worker) {
match detect_with(escalated, image, page.page()) {
Ok(escalated_boxes) => return Ok(escalated_boxes),
Err(error) => {
log::warn!(
"page {}: escalated detection failed, keeping standard pass: {error}",
page.page()
);
}
}
}
}
Ok(detections)
}
fn recognize_page(
&self,
page: &RenderedPage,
options: &OcrOptions,
worker: usize,
) -> Result<OcrPage, OarOcrError> {
let started = Instant::now();
let image = rendered_page_to_rgb(page)?;
let result = self
.pipeline
.predict(vec![image])?
.into_iter()
.next()
.ok_or(OarOcrError::MissingPageResult { page: page.page() })?;
let worker = &self.workers[worker % self.workers.len()];
let image = Arc::new(rendered_page_to_rgb(page)?);
let boxes = self.detect_boxes(page, &image, worker)?;
// Reading order, matching what the combined pipeline produced.
let boxes = oar_ocr::processors::sort_quad_boxes(&boxes);
let mut spans = Vec::with_capacity(result.text_regions.len());
// Same rotation-aware cropping the combined pipeline uses.
let crops =
TextCroppingProcessor::new(true).process((Arc::clone(&image), boxes.clone()))?;
drop(image);
let recognizer = &worker.recognizer;
let mut spans = Vec::with_capacity(boxes.len());
let mut invalid_geometry = 0usize;
let mut missing_recognition = 0usize;
for region in result.text_regions {
let (Some(text), Some(confidence)) = (region.text, region.confidence) else {
for (bounding_box, crop) in boxes.iter().zip(crops) {
let Some(crop) = crop else {
invalid_geometry += 1;
continue;
};
// One crop per call: document line crops often have very
// different widths, and batching pads every crop to the widest
// line. Measured on CPU, batched recognition (even width-sorted)
// is 23× slower than per-crop calls.
let crop = Arc::try_unwrap(crop).unwrap_or_else(|shared| (*shared).clone());
let recognized = recognizer.predict(vec![crop])?;
let (Some(text), Some(confidence)) = (
recognized.texts.into_iter().next(),
recognized.scores.into_iter().next(),
) else {
missing_recognition += 1;
continue;
};
@@ -131,16 +420,21 @@ impl OarOcrEngine {
continue;
}
let polygon = region.dt_poly.as_ref().unwrap_or(&region.bounding_box);
let Some(polygon) = bounding_box_to_quad(polygon, page.width(), page.height()) else {
let Some(polygon) = bounding_box_to_quad(bounding_box, page.width(), page.height())
else {
invalid_geometry += 1;
continue;
};
spans.push(OcrSpan {
text: text.to_string(),
text,
polygon,
confidence,
orientation_degrees: region.orientation_angle,
// The combined pipeline's orientation_angle came from the
// text-line-orientation classifier, a model this engine has
// never loaded — it was structurally None before the staged
// split too (the staged/combined A/B was byte-identical).
// Region rotation is still carried by the polygon itself.
orientation_degrees: None,
});
}
@@ -174,12 +468,42 @@ impl OarOcrEngine {
}
}
fn ocr_session_config() -> OrtSessionConfig {
let available = std::thread::available_parallelism()
.map(std::num::NonZeroUsize::get)
.unwrap_or(1);
/// Runs one detector over one page image and returns its region polygons.
fn detect_with(
detector: &TextDetectionPredictor,
image: &Arc<RgbImage>,
page_number: u32,
) -> Result<Vec<BoundingBox>, OarOcrError> {
let mut result = detector.predict(vec![(**image).clone()])?;
if result.detections.is_empty() {
return Err(OarOcrError::MissingPageResult { page: page_number });
}
Ok(result
.detections
.swap_remove(0)
.into_iter()
.map(|detection| detection.bbox)
.collect())
}
/// Vertical extent of a detection polygon in original-image pixels.
fn polygon_height(polygon: &BoundingBox) -> f32 {
let mut min_y = f32::MAX;
let mut max_y = f32::MIN;
for point in &polygon.points {
min_y = min_y.min(point.y);
max_y = max_y.max(point.y);
}
if max_y > min_y {
max_y - min_y
} else {
0.0
}
}
fn ocr_session_config(intra_threads: usize) -> OrtSessionConfig {
OrtSessionConfig::new()
.with_intra_threads(available.min(4))
.with_intra_threads(intra_threads.max(1))
.with_inter_threads(1)
.with_parallel_execution(false)
}
@@ -226,10 +550,33 @@ impl OcrEngine for OarOcrEngine {
) -> Result<Vec<OcrPage>, Self::Error> {
validate_options(options)?;
pages
.iter()
.map(|page| self.recognize_page(page, options))
.collect()
let Some(pool) = self.pool.as_ref().filter(|_| pages.len() > 1) else {
return pages
.iter()
.map(|page| self.recognize_page(page, options, 0))
.collect();
};
pool.install(|| {
use rayon::prelude::*;
pages
.par_iter()
.map(|page| {
let worker = rayon::current_thread_index().unwrap_or(0);
self.recognize_page(page, options, worker)
})
.collect()
})
}
fn preferred_page_concurrency(&self) -> usize {
// Without a pool, recognition runs sequentially regardless of worker
// count — report that honestly so the pipeline doesn't render
// oversized page batches for parallelism that isn't there.
if self.pool.is_some() {
self.workers.len()
} else {
1
}
}
}
@@ -376,10 +723,13 @@ mod tests {
#[test]
fn cpu_session_budget_is_bounded_for_small_ocr_models() {
let config = ocr_session_config();
let concurrency = pipeline_concurrency();
let config = ocr_session_config(intra_threads_per_pipeline(concurrency));
assert!((1..=4).contains(&config.intra_threads.unwrap()));
assert_eq!(config.inter_threads, Some(1));
assert_eq!(config.parallel_execution, Some(false));
// Zero requests are clamped so a session always has a thread.
assert_eq!(ocr_session_config(0).intra_threads, Some(1));
}
fn page(format: RenderPixelFormat, stride: usize, pixels: Vec<u8>) -> RenderedPage {
@@ -493,4 +843,47 @@ mod tests {
)
.is_ok());
}
#[test]
fn escalation_fires_for_dense_fine_print_pages() {
// Measured cases (at unclip 2.0) that gain from escalation: dense
// tiled ad pages (12.314.2px, 158286 regions) and a dense pricing
// sheet (12.0px, 144 regions), all downscaled by the standard limit.
assert!(should_escalate_detection(14.2, 186, 0.55));
assert!(should_escalate_detection(13.1, 286, 0.55));
assert!(should_escalate_detection(12.3, 158, 0.55));
assert!(should_escalate_detection(12.0, 144, 0.55));
}
#[test]
fn escalation_skips_ordinary_pages() {
// Academic prose: too few regions (and tall enough at unclip 2.0).
assert!(!should_escalate_detection(14.5, 47, 0.58));
// Engineering drawing: many regions but tall enough text.
assert!(!should_escalate_detection(15.7, 205, 0.58));
// Typewriter scan: tall text, few regions.
assert!(!should_escalate_detection(17.5, 77, 0.55));
// Page not downscaled at all: escalation cannot add pixels.
assert!(!should_escalate_detection(9.0, 300, 1.0));
}
#[test]
fn median_detection_height_scales_and_handles_empty() {
let mut heights = vec![30.0, 10.0, 20.0];
assert_eq!(median_detection_height(&mut heights, 0.5), 10.0);
// Even counts average the two middle values instead of picking the
// upper one, so borderline pages don't skew away from escalation.
let mut even = vec![10.0, 12.0, 14.0, 30.0];
assert_eq!(median_detection_height(&mut even, 1.0), 13.0);
let mut empty: Vec<f32> = Vec::new();
assert_eq!(median_detection_height(&mut empty, 0.5), f32::MAX);
}
#[test]
fn concurrency_derivations_stay_in_bounds() {
let concurrency = pipeline_concurrency();
assert!((1..=3).contains(&concurrency));
assert!(intra_threads_per_pipeline(2) == 2);
assert!((1..=4).contains(&intra_threads_per_pipeline(1)));
}
}
+25 -1
View File
@@ -31,6 +31,17 @@ use super::{
/// Bounds live rendered-page memory while preserving small OCR batches.
const OCR_PAGE_CHUNK_SIZE: usize = 4;
/// Pages rendered and held in memory per OCR batch. A parallel engine gets
/// three waves of work per batch so its workers are not starved at chunk
/// barriers; a sequential engine keeps the small memory-bounding default.
/// Engine-reported concurrency is a trait hook, so it is clamped before
/// sizing anything from it — this helper exists to bound rendered-page
/// memory and must not let an engine inflate it arbitrarily.
fn ocr_page_chunk_size(engine_concurrency: usize) -> usize {
const MAX_ENGINE_CONCURRENCY: usize = 8;
(engine_concurrency.clamp(1, MAX_ENGINE_CONCURRENCY) * 3).max(OCR_PAGE_CHUNK_SIZE)
}
#[derive(Debug, Clone, PartialEq, Eq)]
struct OcrEngineCacheKey {
model_root: PathBuf,
@@ -443,7 +454,7 @@ where
let mut render_time_ms = 0u64;
let mut ocr_time_ms = 0u64;
for chunk in routed_pages.chunks(OCR_PAGE_CHUNK_SIZE) {
for chunk in routed_pages.chunks(ocr_page_chunk_size(engine.preferred_page_concurrency())) {
let native_chunk = chunk
.iter()
.map(|page_number| {
@@ -927,6 +938,19 @@ pub enum OcrPipelineError {
mod tests {
use super::*;
#[test]
fn chunk_size_scales_with_engine_concurrency() {
// Sequential engines keep the memory-bounding default.
assert_eq!(ocr_page_chunk_size(1), OCR_PAGE_CHUNK_SIZE);
// Parallel engines get three waves of work per batch.
assert_eq!(ocr_page_chunk_size(3), 9);
assert_eq!(ocr_page_chunk_size(2), 6);
// Engine-reported concurrency is untrusted: clamp before sizing so a
// misbehaving engine cannot inflate rendered-page memory or overflow.
assert_eq!(ocr_page_chunk_size(0), OCR_PAGE_CHUNK_SIZE);
assert_eq!(ocr_page_chunk_size(usize::MAX), 24);
}
struct TrackingRenderer {
batches: Mutex<Vec<Vec<u32>>>,
}