fix: sort panic and missing CID garbage check in extract_text_in_regions_mem

Two bugs in collect_text_in_region / extract_text_in_regions_mem:

1. The threshold-based sort comparator in collect_text_in_region was not
   transitive, causing Rust's sort to panic on certain PDFs. Replaced with
   strict total_cmp ordering — the line-grouping phase already handles
   fuzzy Y matching via threshold.

2. The needs_ocr check was missing is_cid_garbage, so Identity-H fonts
   with CID garbage (C1 control chars, high Latin mojibake) could pass
   all quality checks and be served as real text with needs_ocr=false.

Also adds 7 integration tests for extract_text_in_regions_mem (previously
had zero coverage): basic extraction, Identity-H needs_ocr, multiple
regions, nonexistent page, empty region, invalid input, and a fast-vs-normal
comparison test across all text-based fixtures.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Abimael Martell
2026-04-02 18:13:11 -07:00
co-authored by Claude Opus 4.6
parent 57673ebb69
commit 30244078d8
2 changed files with 195 additions and 24 deletions
+5 -22
View File
@@ -406,6 +406,7 @@ pub fn extract_text_in_regions_mem(
let needs_ocr = text.trim().is_empty()
|| page_has_gid
|| is_garbage_text(&text)
|| is_cid_garbage(&text)
|| detect_encoding_issues(&text);
page_results.push(RegionText { text, needs_ocr });
@@ -482,29 +483,11 @@ pub fn collect_text_in_region(
}
// Sort top→bottom (descending Y in bottom-left coords), then left→right.
// Uses total_cmp to avoid panics on NaN values from bogus font metrics.
// Uses strict total_cmp ordering to guarantee transitivity (required by
// Rust's sort). The line-grouping phase below handles fuzzy Y matching.
matched.sort_by(|a, b| {
let fs_a = if a.font_size.is_finite() {
a.font_size
} else {
0.0
};
let fs_b = if b.font_size.is_finite() {
b.font_size
} else {
0.0
};
let line_threshold = fs_a.max(fs_b) * 0.5;
let ay = if a.y.is_finite() { a.y } else { 0.0 };
let by = if b.y.is_finite() { b.y } else { 0.0 };
let y_diff = by - ay; // descending Y = top to bottom
if y_diff.abs() < line_threshold {
let ax = if a.x.is_finite() { a.x } else { 0.0 };
let bx = if b.x.is_finite() { b.x } else { 0.0 };
ax.total_cmp(&bx)
} else {
by.total_cmp(&ay)
}
b.y.total_cmp(&a.y) // descending Y = top to bottom
.then(a.x.total_cmp(&b.x)) // ascending X = left to right
});
// Group into lines and join
+190 -2
View File
@@ -4,9 +4,11 @@ use pdf_inspector::detector::{DetectionConfig, ScanStrategy};
use pdf_inspector::extractor::group_into_lines;
use pdf_inspector::types::TextLine;
use pdf_inspector::{
detect_pdf_type, extract_text, extract_text_with_positions, process_pdf_with_options,
to_markdown, MarkdownOptions, PdfError, PdfOptions, PdfType, TextItem,
detect_pdf_type, extract_text, extract_text_in_regions_mem, extract_text_with_positions,
process_pdf_mem, process_pdf_with_options, to_markdown, MarkdownOptions, PdfError, PdfOptions,
PdfType, TextItem,
};
use std::collections::HashSet;
// Helper to create test TextItems
fn make_text_item(text: &str, x: f32, y: f32, font_size: f32, page: u32) -> TextItem {
@@ -1107,3 +1109,189 @@ fn test_rotated_table_layout_correction() {
"District data should be in a markdown table row"
);
}
// =========================================================================
// extract_text_in_regions_mem tests
// =========================================================================
/// Build full-page region args for `page_count` pages.
/// Uses a generously large bbox (1200x1200) to capture any page size.
fn full_page_regions(page_count: u32) -> Vec<(u32, Vec<[f32; 4]>)> {
(0..page_count)
.map(|p| (p, vec![[0.0, 0.0, 1200.0, 1200.0]]))
.collect()
}
/// Normalize text for comparison: lowercase, strip non-alphanumeric, split into words.
fn normalize_words(text: &str) -> HashSet<String> {
text.split(|c: char| !c.is_alphanumeric())
.map(|w| w.to_lowercase())
.filter(|w| w.len() > 3)
.collect()
}
/// Fraction of normalized words in `a` that also appear in `b`.
fn word_overlap_ratio(a: &str, b: &str) -> f64 {
let words_a = normalize_words(a);
if words_a.is_empty() {
return if normalize_words(b).is_empty() {
1.0
} else {
0.0
};
}
let words_b = normalize_words(b);
let overlap = words_a.intersection(&words_b).count();
overlap as f64 / words_a.len() as f64
}
#[test]
fn test_extract_regions_mem_basic_text_pdf() {
let buf = std::fs::read("tests/fixtures/nexo-price-en.pdf").unwrap();
let result = process_pdf_mem(&buf).unwrap();
let page_count = result.page_count;
let regions = extract_text_in_regions_mem(&buf, &full_page_regions(page_count)).unwrap();
assert_eq!(regions.len(), page_count as usize);
// Each result should have exactly 1 region (we passed one per page)
for r in &regions {
assert_eq!(r.regions.len(), 1);
}
// First page should have non-empty text
let first = &regions[0].regions[0];
assert!(!first.text.trim().is_empty(), "First page should have text");
assert_eq!(regions[0].page, 0);
}
#[test]
fn test_extract_regions_mem_identity_h_needs_ocr() {
let buf = std::fs::read("tests/fixtures/shinagawa_identity_h.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!(
regions[0].regions[0].needs_ocr,
"Identity-H font without ToUnicode should trigger needs_ocr"
);
}
#[test]
fn test_extract_regions_mem_multiple_regions_per_page() {
let buf = std::fs::read("tests/fixtures/nexo-price-en.pdf").unwrap();
let regions = extract_text_in_regions_mem(
&buf,
&[(
0,
vec![
[0.0, 0.0, 300.0, 100.0], // small top-left
[0.0, 0.0, 1200.0, 1200.0], // full page
],
)],
)
.unwrap();
assert_eq!(regions.len(), 1);
assert_eq!(regions[0].regions.len(), 2);
let small_len = regions[0].regions[0].text.len();
let full_len = regions[0].regions[1].text.len();
assert!(
full_len >= small_len,
"Full-page region ({full_len}) should have at least as much text as small region ({small_len})"
);
}
#[test]
fn test_extract_regions_mem_nonexistent_page() {
let buf = std::fs::read("tests/fixtures/nexo-price-en.pdf").unwrap();
let regions =
extract_text_in_regions_mem(&buf, &[(9999, vec![[0.0, 0.0, 1200.0, 1200.0]])]).unwrap();
assert_eq!(regions.len(), 1);
assert!(
regions[0].regions[0].needs_ocr,
"Nonexistent page should trigger needs_ocr"
);
}
#[test]
fn test_extract_regions_mem_empty_region() {
let buf = std::fs::read("tests/fixtures/nexo-price-en.pdf").unwrap();
let regions = extract_text_in_regions_mem(&buf, &[(0, vec![[0.0, 0.0, 0.0, 0.0]])]).unwrap();
assert_eq!(regions.len(), 1);
assert!(
regions[0].regions[0].needs_ocr,
"Zero-area region should trigger needs_ocr"
);
}
#[test]
fn test_extract_regions_mem_not_a_pdf() {
let result = extract_text_in_regions_mem(b"not a pdf", &[(0, vec![[0.0, 0.0, 100.0, 100.0]])]);
assert!(result.is_err(), "Non-PDF input should return an error");
}
// =========================================================================
// Fast vs normal extraction comparison
// =========================================================================
/// For each text-based fixture PDF, compare `extract_text_in_regions_mem` (fast path)
/// against `process_pdf_mem` (normal path). If the fast path claims needs_ocr=false
/// for a page, verify the extracted text has meaningful overlap with the normal
/// markdown output — catching silent quality regressions.
#[test]
fn test_extract_regions_fast_vs_normal_comparison() {
let fixtures = [
"tests/fixtures/nexo-price-en.pdf",
"tests/fixtures/td9264.pdf",
"tests/fixtures/p1244-1996.pdf",
"tests/fixtures/real-estate-pricing.pdf",
"tests/fixtures/2013-app2.pdf",
"tests/fixtures/firecrawl_docs_tagged.pdf",
"tests/fixtures/thermo-freon12.pdf",
];
for fixture in &fixtures {
let buf = std::fs::read(fixture).unwrap();
let normal = process_pdf_mem(&buf).unwrap();
let normal_md = normal.markdown.as_deref().unwrap_or("");
let page_count = normal.page_count;
let ocr_pages: HashSet<u32> = normal.pages_needing_ocr.iter().copied().collect();
let regions = extract_text_in_regions_mem(&buf, &full_page_regions(page_count)).unwrap();
assert_eq!(
regions.len(),
page_count as usize,
"{fixture}: result count should match page count"
);
for pr in &regions {
let region = &pr.regions[0];
if !region.needs_ocr && !region.text.trim().is_empty() {
// Fast path claims this text is trustworthy.
// Check that its words appear in the normal markdown output.
let overlap = word_overlap_ratio(&region.text, normal_md);
assert!(
overlap >= 0.3,
"{fixture} page {}: fast path says needs_ocr=false but only {:.0}% word \
overlap with normal extraction (threshold 30%). \
Fast text sample: {:?}",
pr.page,
overlap * 100.0,
&region.text[..region.text.len().min(200)],
);
}
// If fast path flags needs_ocr but normal path didn't, that's overly
// conservative but not a bug — just worth knowing.
if region.needs_ocr && !ocr_pages.contains(&(pr.page + 1)) {
eprintln!(
"INFO: {fixture} page {}: fast path says needs_ocr=true but normal path extracted fine (conservative, not a bug)",
pr.page,
);
}
}
}
}