Compare commits
| Author | SHA1 | Date | |
|---|---|---|---|
 Abimael Martell
|
acebe6f7fa | ||
|
Abimael Martell
|
c248eeff8f |
+1
-1
@@ -1,6 +1,6 @@
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{
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"name": "@firecrawl/pdf-inspector",
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"version": "1.8.6",
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"version": "1.8.2",
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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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@@ -385,7 +385,6 @@ pub(crate) fn extract_page_text_items(
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&font_encodings,
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&encoding_cache,
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&mut cmap_decisions,
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&font_widths,
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) {
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let combined = multiply_matrices(&text_matrix, &ctm);
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let rendered_size = effective_font_size(current_font_size, &combined);
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@@ -534,7 +533,6 @@ pub(crate) fn extract_page_text_items(
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&font_encodings,
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&encoding_cache,
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&mut cmap_decisions,
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&font_widths,
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) {
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current_text.push_str(&text);
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}
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@@ -622,7 +620,6 @@ pub(crate) fn extract_page_text_items(
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&font_encodings,
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&encoding_cache,
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&mut cmap_decisions,
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&font_widths,
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) {
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if !text.trim().is_empty() {
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let combined = multiply_matrices(&text_matrix, &ctm);
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@@ -1015,17 +1012,9 @@ pub(crate) fn extract_page_text_items(
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// producing thousands of identical rects that yield a degenerate grid.
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// After dedup, if too few unique clip rects remain we fall through to
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// fill rects (explicitly drawn visible rectangles).
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//
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// When fill rects substantially outnumber clip rects, the clips are
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// typically section-level wrappers and the fills are the actual table
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// cell backgrounds (e.g. shaded-header tables drawn with `m`/`l`/`h`/`f*`
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// sequences). In that case, prefer fills.
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if rects.is_empty() {
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dedup_rects(&mut clip_rects);
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let prefer_fills = !fill_rects.is_empty() && fill_rects.len() >= clip_rects.len() * 3;
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if prefer_fills {
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rects = fill_rects;
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} else if clip_rects.len() >= 4 {
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if clip_rects.len() >= 4 {
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rects = clip_rects;
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} else if !fill_rects.is_empty() {
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rects = fill_rects;
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+1
-122
@@ -720,11 +720,7 @@ pub(crate) fn extract_text_from_operand(
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font_encodings: &PageFontEncodings,
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encoding_cache: &HashMap<String, Encoding<'_>>,
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cmap_decisions: &mut CMapDecisionCache,
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font_widths: &PageFontWidths,
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) -> Option<String> {
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let is_type0_cid_font = font_widths
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.get(current_font)
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.is_some_and(|info| info.is_cid);
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let result = (|| -> Option<String> {
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if let Object::String(bytes, _) = obj {
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let mut decode_with_entry = |entry: &crate::tounicode::CMapEntry| -> Option<String> {
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@@ -966,31 +962,7 @@ pub(crate) fn extract_text_from_operand(
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return Some(symbol_text);
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}
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// Latin-1 fallback. Safe ONLY for fonts that use single-byte
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// encodings — for these, an unmapped byte is a valid character
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// code in Latin-1/WinAnsi space. CID fonts (Type0 / Identity-H)
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// emit multi-byte CIDs that aren't characters; per-byte Latin-1
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// produces mojibake (e.g. 2-byte CID 0xCDD9 → "ÍÙ" for the
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// production scrape_id 019de78c-... samples).
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//
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// For a CID font (has_cmap is set OR a /ToUnicode reference
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// exists) with any non-ASCII bytes, emit a single U+FFFD per
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// CID instead. This both replaces the mojibake with a proper
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// "decode failed" marker AND keeps `detect_encoding_issues`
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// tripping so the page is flagged for OCR — the existing
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// garbage-detection path that the high-Latin-1 mojibake used
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// to satisfy by accident.
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if is_type0_cid_font && bytes.iter().any(|&b| b > 0x7F) {
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// 2-byte CIDs (Identity-H) are by far the common case; for
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// an odd byte count we still emit at least one marker so
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// detection downstream fires.
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let cid_count = (bytes.len() / 2).max(1);
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return Some("\u{FFFD}".repeat(cid_count));
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}
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// Pure ASCII bytes round-trip safely (Latin-1 == ASCII for
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// 0x00..=0x7F), and non-CID (Type1 / TrueType / Type3) fonts
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// use single-byte encodings where Latin-1 fallback is the
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// canonical interpretation.
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// Latin-1 fallback
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Some(bytes.iter().map(|&b| b as char).collect())
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} else {
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None
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@@ -1241,97 +1213,4 @@ mod tests {
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let bad = "###!!!@@@$$$";
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assert!(score_text(good) > score_text(bad));
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}
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#[test]
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fn cid_font_with_unparseable_cmap_does_not_emit_latin1_mojibake() {
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// Type0/CID font (font_widths reports `is_cid=true`) where the
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// ToUnicode CMap couldn't be parsed (FontCMaps doesn't have the
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// obj_num). Bytes are a 2-byte CID stream containing high bytes
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// that aren't valid UTF-8 — exactly the case in the production
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// samples (Identity-H text where the ToUnicode CMap was missing
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// or malformed, scrape_id 019de78c-..., e.g. "Í Ù Z)¿").
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//
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// Without the guard, the function falls through to the byte-by-byte
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// Latin-1 fallback and produces "ÍÙ" (U+00CD U+00D9). The correct
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// behavior is to emit U+FFFD per CID so downstream
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// `detect_encoding_issues` flags the page for OCR.
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let bytes = vec![0xCD_u8, 0xD9, 0xCD, 0xD9];
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let obj = Object::String(bytes, lopdf::StringFormat::Hexadecimal);
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let font_cmaps = FontCMaps::default();
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let mut font_tounicode_refs: HashMap<String, u32> = HashMap::new();
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font_tounicode_refs.insert("F0".to_string(), 999);
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let inline_cmaps = HashMap::new();
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let font_encodings: PageFontEncodings = HashMap::new();
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let encoding_cache: HashMap<String, Encoding<'_>> = HashMap::new();
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let mut decisions = CMapDecisionCache::new();
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let mut font_widths: PageFontWidths = HashMap::new();
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font_widths.insert("F0".to_string(), make_font_info(&[], 1000, true));
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let result = extract_text_from_operand(
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&obj,
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"F0",
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None,
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&font_cmaps,
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&font_tounicode_refs,
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&inline_cmaps,
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&font_encodings,
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&encoding_cache,
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&mut decisions,
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&font_widths,
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);
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let text = result.expect("CID font fallback should still emit a marker");
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assert!(
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!text.contains('\u{00CD}') && !text.contains('\u{00D9}'),
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"CID font with unparseable CMap leaked Latin-1 mojibake: {text:?}"
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);
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assert!(
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text.contains('\u{FFFD}'),
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"CID font with unparseable CMap should emit U+FFFD so detect_encoding_issues fires: {text:?}"
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);
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}
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#[test]
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fn simple_font_latin1_fallback_passes_high_bytes_through() {
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// A Type1/TrueType simple font (is_cid=false) with a `/ToUnicode`
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// reference but no usable CMap and no `/Differences` map.
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// Per-byte Latin-1 IS the canonical interpretation here — these
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// bytes are character codes, not CIDs. The CID guard must NOT
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// strip them. Reproduces the false positive that an earlier
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// version of the guard introduced for fonts in PDFs like
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// pdf-evals/Navigating-Artificial-Intelligence-..., where bytes
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// like 0xB6 are legitimate Latin-1 character codes.
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let bytes = vec![0x24_u8, 0x47, 0xB6, 0x56]; // "$G¶V"
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let obj = Object::String(bytes, lopdf::StringFormat::Hexadecimal);
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let font_cmaps = FontCMaps::default();
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let mut font_tounicode_refs: HashMap<String, u32> = HashMap::new();
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font_tounicode_refs.insert("F1".to_string(), 999);
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let inline_cmaps = HashMap::new();
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let font_encodings: PageFontEncodings = HashMap::new();
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let encoding_cache: HashMap<String, Encoding<'_>> = HashMap::new();
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let mut decisions = CMapDecisionCache::new();
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let mut font_widths: PageFontWidths = HashMap::new();
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font_widths.insert("F1".to_string(), make_font_info(&[], 1000, false));
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let text = extract_text_from_operand(
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&obj,
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"F1",
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None,
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&font_cmaps,
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&font_tounicode_refs,
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&inline_cmaps,
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&font_encodings,
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&encoding_cache,
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&mut decisions,
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&font_widths,
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)
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.expect("simple font should round-trip Latin-1 bytes");
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assert_eq!(text, "$G\u{00B6}V");
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assert!(
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!text.contains('\u{FFFD}'),
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"simple font fallback must not stamp FFFD over legitimate bytes: {text:?}"
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);
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}
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}
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@@ -373,7 +373,6 @@ fn extract_form_xobject_text_inner(
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&font_encodings,
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&encoding_cache,
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cmap_decisions,
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&font_widths,
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) {
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let combined = multiply_matrices(&text_matrix, &ctm);
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let rendered_size = effective_font_size(current_font_size, &combined);
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@@ -518,7 +517,6 @@ fn extract_form_xobject_text_inner(
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&font_encodings,
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&encoding_cache,
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cmap_decisions,
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&font_widths,
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) {
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current_text.push_str(&text);
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}
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+51
-353
@@ -1035,203 +1035,6 @@ mod vector_grid_tests {
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);
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}
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/// Helper: load a fixture PDF and run the rect-based table detector.
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fn detect_rect_tables_in_fixture(path: &str) -> Vec<crate::tables::Table> {
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use crate::extractor::content_stream::extract_page_text_items;
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use crate::tables::detect_tables_from_rects;
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use crate::tounicode::FontCMaps;
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use lopdf::Document;
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use std::collections::HashSet;
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use std::fs;
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let buf = fs::read(path).unwrap();
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let doc = Document::load_mem(&buf).unwrap();
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let pages = doc.get_pages();
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let &page_id = pages.get(&1).unwrap();
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let needed: HashSet<u32> = HashSet::from([1]);
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let cmaps = FontCMaps::from_doc_pages_fast(&doc, Some(&needed));
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let ((items, rects, _lines), _has_gid, _rotated) =
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extract_page_text_items(&doc, page_id, 1, &cmaps, false).unwrap();
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let (rect_tables, _) = detect_tables_from_rects(&items, &rects, 1);
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rect_tables
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}
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/// Regression for the prose-in-a-frame failure mode introduced by the
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/// shaded-header detection lift (PR #76). The accessory_building permit
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/// form has a paragraph of legal text laid out in a 2-column justified
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/// block; the new fill-priority + dedup changes start producing rects
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/// for it, and the rect detector then admits a 10×2 fake table where
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/// every cell holds a sentence fragment ("I agree to comply...", "I",
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/// "It is the property owner's responsibility..."). This test asserts
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/// the detector REJECTS that fake table — only the real 5×3 form data
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/// table (TYPE / SIZE / SETBACKS) should survive. See pdf-evals PR #30
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/// for the original score regression that surfaced this.
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#[test]
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fn accessory_building_rejects_prose_in_frame() {
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let tables = detect_rect_tables_in_fixture(
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"tests/fixtures/accessory_building_permit_prose_frame.pdf",
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);
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// Real form data table (TYPE / SIZE / SETBACKS) must still be detected.
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let data_table = tables.iter().find(|t| t.columns.len() == 3);
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assert!(
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data_table.is_some(),
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"expected to keep the 5×3 TYPE/SIZE/SETBACKS data table; got {:?}",
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tables
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.iter()
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.map(|t| (t.rows.len(), t.columns.len()))
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.collect::<Vec<_>>()
|
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);
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// Prose paragraph laid out in 2 cols must NOT be detected as a table.
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// If the rejection regresses, the 10×2 fake table reappears and
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// produces fragmented markdown like "I agree to comply..." | "I"
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// that fragments mid-sentence.
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let prose_table = tables.iter().find(|t| t.columns.len() == 2);
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assert!(
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prose_table.is_none(),
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"expected the 10×2 prose-in-frame block to be rejected; got rows×cols = {:?}",
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prose_table.map(|t| (t.rows.len(), t.columns.len()))
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);
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}
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/// Wireless table regression: decorative/text-region rects may provide row
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/// bands, but without a real rect-derived column scaffold they must not be
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/// accepted as a vector grid.
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#[test]
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fn wireless_two_col_rejects_rect_grid() {
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let tables = detect_rect_tables_in_fixture("tests/fixtures/wireless_two_col_no_rects.pdf");
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assert!(
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tables.is_empty(),
|
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"expected no rect-detected tables for wireless content; got {:?}",
|
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tables
|
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.iter()
|
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.map(|t| (t.rows.len(), t.columns.len()))
|
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.collect::<Vec<_>>()
|
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);
|
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}
|
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|
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#[test]
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fn wireless_two_col_region_rejects_vector_grid() {
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let buf = std::fs::read("tests/fixtures/wireless_two_col_no_rects.pdf").unwrap();
|
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let crops = [
|
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[49.32_f32, 52.92, 558.72, 214.2],
|
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[49.32_f32, 288.72, 556.56, 378.0],
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[51.48_f32, 478.44, 558.36, 567.36],
|
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];
|
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for crop in crops {
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let detected = crate::detect_vector_grid_in_region_mem(&buf, 0, crop, 200.0).unwrap();
|
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assert!(
|
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detected.is_none(),
|
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"expected no vector grid for wireless crop {crop:?}; got {} cells",
|
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detected.map(|grid| grid.cell_bboxes.len()).unwrap_or(0)
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
/// Wireless dense table regression: text-position columns alone are not
|
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/// enough evidence for a rect-derived grid.
|
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#[test]
|
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fn wireless_dense_rejects_rect_grid() {
|
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let tables = detect_rect_tables_in_fixture("tests/fixtures/wireless_dense_no_rects.pdf");
|
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assert!(
|
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tables.is_empty(),
|
||||
"expected no rect-detected tables for wireless content; got {:?}",
|
||||
tables
|
||||
.iter()
|
||||
.map(|t| (t.rows.len(), t.columns.len()))
|
||||
.collect::<Vec<_>>()
|
||||
);
|
||||
}
|
||||
|
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#[test]
|
||||
fn wireless_dense_region_rejects_vector_grid() {
|
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let buf = std::fs::read("tests/fixtures/wireless_dense_no_rects.pdf").unwrap();
|
||||
let crops = [
|
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[72.36_f32, 177.48, 243.72, 333.36],
|
||||
[72.0_f32, 390.24, 286.92, 417.6],
|
||||
];
|
||||
for crop in crops {
|
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let detected = crate::detect_vector_grid_in_region_mem(&buf, 0, crop, 200.0).unwrap();
|
||||
assert!(
|
||||
detected.is_none(),
|
||||
"expected no vector grid for wireless crop {crop:?}; got {} cells",
|
||||
detected.map(|grid| grid.cell_bboxes.len()).unwrap_or(0)
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
/// Regression for `greencomp_competence.pdf` — a 2-column "Area / Competence"
|
||||
/// glossary with a green-shaded header row and plain (line-drawn) body cells.
|
||||
/// Mirrors the production failure cohort #1 (Contractions glossary) and #6
|
||||
/// (BIO 350 course header): a few colored header rects sit in a horizontal
|
||||
/// strip while body rows are drawn with `m`/`l` operators, so the rect
|
||||
/// cluster has only 2 Y-edges and `try_build_grid` rejects.
|
||||
///
|
||||
/// IGNORED: lifting this shape required the exact-duplicate early-dedup
|
||||
/// (PR #76 first iteration), which had broad collateral damage on
|
||||
/// SEC 10-K TOCs and similar docs that draw rule-rects above + below
|
||||
/// section dividers (production diff: 0001104659-25-093871 lost its
|
||||
/// TOC structure, perf-graph data table, and qualifications matrix).
|
||||
/// Re-enable once a more surgical lift exists in `try_build_grid` or
|
||||
/// `snap_edges` that handles cell-border + inner-fill + text-bg rect
|
||||
/// triplets without page-wide dedup.
|
||||
#[test]
|
||||
#[ignore]
|
||||
fn greencomp_competence_two_cols() {
|
||||
let tables = detect_rect_tables_in_fixture("tests/fixtures/greencomp_competence.pdf");
|
||||
assert!(
|
||||
!tables.is_empty(),
|
||||
"expected at least one rect-detected table for shaded-header + plain-body shape"
|
||||
);
|
||||
let t = tables
|
||||
.iter()
|
||||
.max_by_key(|t| t.rows.len() * t.columns.len())
|
||||
.unwrap();
|
||||
assert_eq!(
|
||||
t.columns.len(),
|
||||
2,
|
||||
"GreenComp competence is a 2-column table; got {}: {:?}",
|
||||
t.columns.len(),
|
||||
t.columns
|
||||
);
|
||||
assert!(
|
||||
t.rows.len() >= 6,
|
||||
"expected at least 6 rows of competences; got {}",
|
||||
t.rows.len()
|
||||
);
|
||||
}
|
||||
|
||||
/// Regression for `upstage_key_functions.pdf` — a 4-column "Service Stage /
|
||||
/// Function Name / Explanation / Expected Benefit" table with a blue-shaded
|
||||
/// header band plus alternating row backgrounds. Mirrors production crops
|
||||
/// #2 (Parameter / Value with alternating blue rows) and #7 (Spanish XML
|
||||
/// schema with shaded header). Currently `pdf2md` returns zero markdown
|
||||
/// table rows.
|
||||
#[test]
|
||||
fn upstage_key_functions_four_cols() {
|
||||
let tables = detect_rect_tables_in_fixture("tests/fixtures/upstage_key_functions.pdf");
|
||||
assert!(
|
||||
!tables.is_empty(),
|
||||
"expected at least one rect-detected table for shaded-header + alt-row shape"
|
||||
);
|
||||
let t = tables
|
||||
.iter()
|
||||
.max_by_key(|t| t.rows.len() * t.columns.len())
|
||||
.unwrap();
|
||||
assert_eq!(
|
||||
t.columns.len(),
|
||||
4,
|
||||
"Service Flow is a 4-column table; got {}: {:?}",
|
||||
t.columns.len(),
|
||||
t.columns
|
||||
);
|
||||
assert!(
|
||||
t.rows.len() >= 8,
|
||||
"expected at least 8 visible body rows; got {}",
|
||||
t.rows.len()
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_crop_px_bbox_is_plausible_bounds() {
|
||||
let crop = [10.0, 20.0, 110.0, 220.0];
|
||||
@@ -1753,32 +1556,26 @@ pub fn extract_tables_with_structure_cells_mem(
|
||||
|
||||
normalize_cell_bands(&mut cells);
|
||||
|
||||
// Stage 1: exclusive per-token assignment. Each PDF text item is
|
||||
// first split into whitespace-separated tokens with estimated x
|
||||
// positions (see `split_item_into_token_subitems`). For each token
|
||||
// we find the cell(s) whose (band-clamped) bbox satisfies the
|
||||
// strict membership rule (`tsr_region_contains_item`: center
|
||||
// inside OR >=60% overlap on both axes). If multiple cells
|
||||
// qualify, the closest-center wins. Tokens that don't land in any
|
||||
// cell are eligible for stage-2 orphan recovery.
|
||||
// Stage 1: exclusive per-item assignment. For each PDF text item,
|
||||
// find the cell(s) whose (band-clamped) bbox satisfies the strict
|
||||
// membership rule (`tsr_region_contains_item`: center inside OR
|
||||
// >=60% overlap on both axes). If multiple cells qualify, assign
|
||||
// the item to the cell whose center is geometrically closest. If
|
||||
// exactly one qualifies, assign to that. If none, the item is an
|
||||
// orphan and stage 2 below tries to recover it.
|
||||
//
|
||||
// Per-token (rather than per-item) routing is what prevents the
|
||||
// dense-grid collapse bug: a row rendered as one wide Tj
|
||||
// ("Marshall Islands 0.9 0.9 0.9") produces one TextItem whose
|
||||
// CENTER lies in only one cell, so per-item routing parks the
|
||||
// whole row in that single cell and leaves the rest of the row
|
||||
// empty. Per-token routing distributes the words to whichever
|
||||
// cells their (estimated) positions fall into. Single-token items
|
||||
// collapse to a one-element token list and behave exactly as
|
||||
// before.
|
||||
//
|
||||
// The token-level exclusivity (one token → one cell) still
|
||||
// prevents the cell-overlap bug where SLANet emits cells whose
|
||||
// y-extents overlap between rows. Closest-center disambiguation
|
||||
// routes each token to the correct row.
|
||||
// The exclusivity (one item → one cell) prevents the cell-overlap
|
||||
// bug where SLANet emits cells whose y-extents overlap between
|
||||
// rows: under the previous "for each cell, gather items" approach,
|
||||
// an item whose center fell in two cells' overlap got duplicated
|
||||
// into both. Closest-center disambiguation routes it to the
|
||||
// correct row.
|
||||
let mut claimed: std::collections::HashSet<usize> = std::collections::HashSet::new();
|
||||
let mut item_to_cell: std::collections::HashMap<usize, usize> =
|
||||
std::collections::HashMap::new();
|
||||
|
||||
// Pre-compute each cell's bounds + center (in PDF-pt-flipped space)
|
||||
// so we don't redo the work per token.
|
||||
// so we don't redo the work per item.
|
||||
let cell_meta: Vec<Option<(RegionBounds, f32, f32)>> = cells
|
||||
.iter()
|
||||
.map(|cell| {
|
||||
@@ -1793,53 +1590,44 @@ pub fn extract_tables_with_structure_cells_mem(
|
||||
})
|
||||
.collect();
|
||||
|
||||
let mut per_cell_items: Vec<Vec<TextItem>> = vec![Vec::new(); cells.len()];
|
||||
// Tokens of an item that did NOT land in any cell during stage 1.
|
||||
// These are the orphan candidates handed to `tsr_assign_orphan_items`.
|
||||
// Using token-grain orphan candidates (rather than the original wide
|
||||
// item) lets stage 2 recover individual words that fell just outside
|
||||
// their cell's clamped band, without re-attributing already-claimed
|
||||
// tokens.
|
||||
let mut orphan_token_subitems: Vec<TextItem> = Vec::new();
|
||||
|
||||
for item in items.iter() {
|
||||
let token_subitems = split_item_into_token_subitems(item);
|
||||
for token_item in token_subitems {
|
||||
let token_w = text_utils::effective_width(&token_item);
|
||||
let token_cx = token_item.x + token_w * 0.5;
|
||||
let token_cy = token_item.y + token_item.height * 0.5;
|
||||
let mut best: Option<(usize, f32)> = None;
|
||||
for (cell_idx, meta) in cell_meta.iter().enumerate() {
|
||||
let Some((bounds, ccx, ccy)) = meta else {
|
||||
continue;
|
||||
};
|
||||
if !tsr_region_contains_item(&token_item, *bounds) {
|
||||
continue;
|
||||
}
|
||||
let dx = token_cx - ccx;
|
||||
let dy = token_cy - ccy;
|
||||
let dist_sq = dx * dx + dy * dy;
|
||||
if best.is_none_or(|(_, d)| dist_sq < d) {
|
||||
best = Some((cell_idx, dist_sq));
|
||||
}
|
||||
for (item_idx, item) in items.iter().enumerate() {
|
||||
let item_w = text_utils::effective_width(item);
|
||||
let item_cx = item.x + item_w * 0.5;
|
||||
let item_cy = item.y + item.height * 0.5;
|
||||
let mut best: Option<(usize, f32)> = None;
|
||||
for (cell_idx, meta) in cell_meta.iter().enumerate() {
|
||||
let Some((bounds, ccx, ccy)) = meta else {
|
||||
continue;
|
||||
};
|
||||
if !tsr_region_contains_item(item, *bounds) {
|
||||
continue;
|
||||
}
|
||||
if let Some((ci, _)) = best {
|
||||
per_cell_items[ci].push(token_item);
|
||||
} else {
|
||||
orphan_token_subitems.push(token_item);
|
||||
let dx = item_cx - ccx;
|
||||
let dy = item_cy - ccy;
|
||||
let dist_sq = dx * dx + dy * dy;
|
||||
if best.is_none_or(|(_, d)| dist_sq < d) {
|
||||
best = Some((cell_idx, dist_sq));
|
||||
}
|
||||
}
|
||||
if let Some((ci, _)) = best {
|
||||
claimed.insert(item_idx);
|
||||
item_to_cell.insert(item_idx, ci);
|
||||
}
|
||||
}
|
||||
|
||||
// Build per-cell text from the assigned tokens. Markdown cells must
|
||||
// Build per-cell text from the assigned items. Markdown cells must
|
||||
// be one line — collapse line breaks from the line-grouping pass.
|
||||
let mut per_cell_items: Vec<Vec<TextItem>> = vec![Vec::new(); cells.len()];
|
||||
for (&item_idx, &cell_idx) in &item_to_cell {
|
||||
per_cell_items[cell_idx].push(items[item_idx].clone());
|
||||
}
|
||||
for (cell_idx, matched) in per_cell_items.into_iter().enumerate() {
|
||||
cells[cell_idx].text = collect_text_from_matched_items(matched, adaptive_threshold)
|
||||
.replace(['\n', '\r'], " ");
|
||||
}
|
||||
|
||||
// Stage 2: orphan assignment — tokens that didn't land in any cell
|
||||
// during stage 1 get assigned to their nearest *empty* cell,
|
||||
// Stage 2: orphan assignment — text items that didn't land in any
|
||||
// cell during stage 1 get assigned to their nearest *empty* cell,
|
||||
// clamped by a plausibility cap derived from cell geometry.
|
||||
//
|
||||
// This recovers two failure modes left by `normalize_cell_bands`:
|
||||
@@ -1851,13 +1639,7 @@ pub fn extract_tables_with_structure_cells_mem(
|
||||
// Empty-cell-only is the safety net: a cell already filled by stage 1
|
||||
// is never overwritten or augmented, so the cell-bleed case PR #62
|
||||
// closed cannot regress.
|
||||
tsr_assign_orphan_items(
|
||||
&orphan_token_subitems,
|
||||
&mut cells,
|
||||
&std::collections::HashSet::new(),
|
||||
page_h,
|
||||
coords,
|
||||
);
|
||||
tsr_assign_orphan_items(items, &mut cells, &claimed, page_h, coords);
|
||||
|
||||
results.push(cells);
|
||||
}
|
||||
@@ -1865,70 +1647,6 @@ pub fn extract_tables_with_structure_cells_mem(
|
||||
Ok(results)
|
||||
}
|
||||
|
||||
/// Split a `TextItem` into one virtual sub-item per whitespace-separated
|
||||
/// token, with each token's `x` / `width` estimated from the original item's
|
||||
/// effective width and the token's character offset.
|
||||
///
|
||||
/// PDFs often render an entire row's content as a single Tj — e.g.
|
||||
/// "Marshall Islands 0.9 0.9 0.9" — producing one wide TextItem whose
|
||||
/// center sits in only one of the model-emitted cells. Per-item routing
|
||||
/// then parks the whole row in that one cell. Splitting on whitespace
|
||||
/// gives each word its own approximate position so per-cell routing can
|
||||
/// distribute the words to whichever cells their estimated centers fall
|
||||
/// into.
|
||||
///
|
||||
/// The character-width estimate is `effective_width / char_count`.
|
||||
/// `effective_width` returns the explicit `item.width` when known and
|
||||
/// otherwise falls back to `char_count * font_size * 0.5`. Either way the
|
||||
/// estimate is uniform across the item — fine for routing, since we only
|
||||
/// need to know which cell each token's center lands in, not its exact
|
||||
/// position. Single-token items collapse to a one-element vector
|
||||
/// equivalent to the input item, making this a no-op for the common case.
|
||||
fn split_item_into_token_subitems(item: &TextItem) -> Vec<TextItem> {
|
||||
let total_chars = item.text.chars().count();
|
||||
if total_chars == 0 {
|
||||
return Vec::new();
|
||||
}
|
||||
let item_w = text_utils::effective_width(item);
|
||||
let char_w = item_w / total_chars as f32;
|
||||
|
||||
let mut tokens: Vec<TextItem> = Vec::new();
|
||||
let mut current_token = String::new();
|
||||
let mut current_start_idx: Option<usize> = None;
|
||||
|
||||
let push_token =
|
||||
|tokens: &mut Vec<TextItem>, text: String, start_idx: usize, end_idx: usize| {
|
||||
if text.is_empty() {
|
||||
return;
|
||||
}
|
||||
let mut sub = item.clone();
|
||||
sub.text = text;
|
||||
sub.x = item.x + start_idx as f32 * char_w;
|
||||
sub.width = (end_idx - start_idx) as f32 * char_w;
|
||||
tokens.push(sub);
|
||||
};
|
||||
|
||||
for (idx, ch) in item.text.chars().enumerate() {
|
||||
if ch.is_whitespace() {
|
||||
if let Some(start_idx) = current_start_idx.take() {
|
||||
let text = std::mem::take(&mut current_token);
|
||||
push_token(&mut tokens, text, start_idx, idx);
|
||||
}
|
||||
} else {
|
||||
if current_start_idx.is_none() {
|
||||
current_start_idx = Some(idx);
|
||||
}
|
||||
current_token.push(ch);
|
||||
}
|
||||
}
|
||||
if let Some(start_idx) = current_start_idx {
|
||||
let text = std::mem::take(&mut current_token);
|
||||
push_token(&mut tokens, text, start_idx, total_chars);
|
||||
}
|
||||
|
||||
tokens
|
||||
}
|
||||
|
||||
/// Compute plausibility caps for the orphan-assignment pass. Returns
|
||||
/// `(cap_x, cap_y)` — the maximum x/y distance from a text item's center
|
||||
/// to a candidate empty cell's bbox before the candidate is rejected.
|
||||
@@ -2434,15 +2152,13 @@ fn try_expand_multi_row_cells(
|
||||
/// * `phantom_empty_row` — a row whose every cell is empty, surrounded
|
||||
/// above and below by rows with content. SLANet sometimes emits an
|
||||
/// extra row that doesn't correspond to any visible PDF row.
|
||||
/// * `multi_row_in_cell` — at least one non-label `rowspan==1` cell
|
||||
/// encloses PDF text items that cluster into two distinct visual lines
|
||||
/// * `multi_row_in_cell` — at least one `rowspan==1` cell encloses
|
||||
/// PDF text items that cluster into two distinct visual lines
|
||||
/// separated by a whitespace gap larger than the line height. Cells
|
||||
/// declared as `rowspan>1` are excluded since they are *expected*
|
||||
/// to span multiple lines. First-row/first-column wraps are ignored
|
||||
/// unless the in-place row expansion has enough support to repair them,
|
||||
/// because those are often legitimate wrapped headers or row labels.
|
||||
/// SLANet's row under-detection on tightly-packed tables produces the
|
||||
/// rowspan==1-but-multi-line pattern (the FNBO failure mode).
|
||||
/// to span multiple lines. SLANet's row under-detection on
|
||||
/// tightly-packed tables produces the rowspan==1-but-multi-line
|
||||
/// pattern (the FNBO failure mode).
|
||||
fn detect_tsr_quality_issue(
|
||||
buffer: &[u8],
|
||||
input: &TsrTableInput,
|
||||
@@ -2500,8 +2216,6 @@ fn detect_tsr_quality_issue(
|
||||
};
|
||||
let expanded_cells =
|
||||
try_expand_multi_row_cells(cells, &items, page_h, coords, adaptive_threshold);
|
||||
let first_row = cells.iter().map(|cell| cell.row).min().unwrap_or(0);
|
||||
let first_col = cells.iter().map(|cell| cell.col).min().unwrap_or(0);
|
||||
|
||||
for cell in cells {
|
||||
// rowspan>1 cells are intentionally multi-line — skip them.
|
||||
@@ -2515,30 +2229,14 @@ fn detect_tsr_quality_issue(
|
||||
if cell_items.len() < 2 {
|
||||
continue;
|
||||
}
|
||||
if cluster_tsr_cell_text_lines(cell_items).len() < 2 {
|
||||
continue;
|
||||
}
|
||||
if expanded_cells.is_some() {
|
||||
if cluster_tsr_cell_text_lines(cell_items).len() >= 2 {
|
||||
return Ok(Some(TsrQualityIssue::MultiRowInCell { expanded_cells }));
|
||||
}
|
||||
if !is_wrapped_tsr_label_cell(cell, first_row, first_col) {
|
||||
return Ok(Some(TsrQualityIssue::MultiRowInCell {
|
||||
expanded_cells: None,
|
||||
}));
|
||||
}
|
||||
}
|
||||
|
||||
Ok(None)
|
||||
}
|
||||
|
||||
fn is_wrapped_tsr_label_cell(
|
||||
cell: &tables::StructuredCell,
|
||||
first_row: usize,
|
||||
first_col: usize,
|
||||
) -> bool {
|
||||
cell.is_header || cell.row == first_row || cell.col == first_col
|
||||
}
|
||||
|
||||
/// Auto-fallback variant of [`extract_tables_with_structure_mem`]:
|
||||
/// runs the TSR-hybrid path, checks the resulting cells for known
|
||||
/// SLANet detection pathologies (phantom rows, multi-row-in-cell text),
|
||||
|
||||
+15
-151
@@ -285,11 +285,7 @@ pub fn detect_tables_from_rects(
|
||||
//
|
||||
// Only remove when the container is a similarly-sized cell (height
|
||||
// ratio < 4×), NOT when the container is a table-wide background
|
||||
// that dwarfs the sub-rect. Origin-anchored page-background rects
|
||||
// also disqualify as containers — they normally exceed the 4× ratio,
|
||||
// but when the sub-rect is itself a tall table-frame the ratio can
|
||||
// fall under the gate, and dropping the frame collapses cluster
|
||||
// adjacency between adjacent column-cell groups.
|
||||
// that dwarfs the sub-rect.
|
||||
//
|
||||
// Skip this O(n²) dedup when there are too many rects — pages with
|
||||
// thousands of vector-drawing rects won't benefit from cell dedup.
|
||||
@@ -299,11 +295,9 @@ pub fn detect_tables_from_rects(
|
||||
page_rects.retain(|&(ax, ay, aw, ah)| {
|
||||
let tol = 2.0;
|
||||
!snapshot.iter().any(|&(bx, by, bw, bh)| {
|
||||
let container_is_page_bg = bx < 5.0 && by < 5.0;
|
||||
// b must strictly contain a (b is larger in area)
|
||||
bw * bh > aw * ah * 1.2
|
||||
&& bh < ah * 4.0 // container must be similarly sized, not a table background
|
||||
&& !container_is_page_bg
|
||||
&& bx <= ax + tol
|
||||
&& (bx + bw) >= (ax + aw) - tol
|
||||
&& by <= ay + tol
|
||||
@@ -1632,17 +1626,17 @@ fn detect_row_stripe_table_from_cell_rects(
|
||||
}
|
||||
};
|
||||
|
||||
let (col_edges, columns_from_text) = match (rect_col_edges, text_col_edges) {
|
||||
let col_edges = match (rect_col_edges, text_col_edges) {
|
||||
(Some(rect_edges), Some(text_edges)) if rect_edges.len() <= text_edges.len() => {
|
||||
debug!(
|
||||
" cell-rect using {} rect-derived columns over {} text clusters",
|
||||
rect_edges.len() - 1,
|
||||
text_edges.len() - 1
|
||||
);
|
||||
(rect_edges, false)
|
||||
rect_edges
|
||||
}
|
||||
(_, Some(text_edges)) => (text_edges, true),
|
||||
(Some(rect_edges), None) => (rect_edges, false),
|
||||
(_, Some(text_edges)) => text_edges,
|
||||
(Some(rect_edges), None) => rect_edges,
|
||||
(None, None) => {
|
||||
debug!(
|
||||
" cell-rect rejected: only {} columns from text clustering",
|
||||
@@ -1731,36 +1725,13 @@ fn detect_row_stripe_table_from_cell_rects(
|
||||
|
||||
// Reject "tables" that are actually prose in a framed region.
|
||||
// Columns here come from text X-position clustering; when prose wraps
|
||||
// inside a bounding-box rect (e.g. chat-transcript figures, two-column
|
||||
// legal-text blocks in forms) the word-boundary gaps cluster into
|
||||
// spurious columns, and the resulting cells hold sentence fragments
|
||||
// riddled with common English function words.
|
||||
//
|
||||
// Apply at any column count >= 2. The 2-col case is the bite — a
|
||||
// paragraph wrapped into 2 justified columns produces the same
|
||||
// surface signal as a real "label / value" table in the
|
||||
// well-distributed-cols check (both cols populated), so we need a
|
||||
// content-based signal to tell them apart.
|
||||
//
|
||||
// Layered checks combine after the 20%-of-cells prose-word
|
||||
// trigger fires:
|
||||
// (a) Long-cell content: prose-in-a-frame averages ~70-100 chars
|
||||
// per non-empty cell (sentence fragments); real data tables
|
||||
// are typically <30 chars, occasionally up to ~55 for
|
||||
// descriptive 4-col tables. The 65-char threshold cleanly
|
||||
// separates them on observed fixtures (accessory_building
|
||||
// prose=74 chars, upstage data=53, greencomp=20). This
|
||||
// overrides the well-distributed relaxation — long cells
|
||||
// are the strongest prose signal even when both cols are
|
||||
// populated.
|
||||
// (b) Two-column text-only scaffold: when both columns were inferred
|
||||
// from text starts rather than rect edges, prose fragments can look
|
||||
// perfectly balanced. Require rect evidence for this relaxed shape.
|
||||
// (c) Well-distributed columns: ≥75% of cols hold ≥2 non-empty
|
||||
// cells. Catches the prose-paragraph-as-many-cols shape
|
||||
// while admitting real "label / value / description /
|
||||
// benefit"-style tables.
|
||||
if num_cols >= 2 {
|
||||
// inside a bounding-box rect (e.g. chat-transcript figures) the
|
||||
// word-boundary gaps cluster into many spurious columns, and the
|
||||
// resulting cells hold sentence fragments riddled with common English
|
||||
// function words. Count cells with any such word and reject when
|
||||
// 20%+ of non-empty cells match — real tabular data (labels, units,
|
||||
// numbers) rarely contains these words.
|
||||
if num_cols >= 4 {
|
||||
const PROSE_WORDS: &[&str] = &[
|
||||
"a", "an", "the", "of", "to", "is", "was", "are", "were", "be", "been", "in", "on",
|
||||
"at", "with", "for", "by", "as", "and", "or", "but", "this", "that", "these", "those",
|
||||
@@ -1770,7 +1741,6 @@ fn detect_row_stripe_table_from_cell_rects(
|
||||
];
|
||||
let mut prose_cells = 0usize;
|
||||
let mut counted = 0usize;
|
||||
let mut total_chars = 0usize;
|
||||
for row in &cells {
|
||||
for cell in row {
|
||||
let t = cell.trim();
|
||||
@@ -1778,7 +1748,6 @@ fn detect_row_stripe_table_from_cell_rects(
|
||||
continue;
|
||||
}
|
||||
counted += 1;
|
||||
total_chars += t.chars().count();
|
||||
let lower = t.to_ascii_lowercase();
|
||||
let has_prose_word = lower
|
||||
.split(|c: char| !c.is_ascii_alphabetic() && c != '\'')
|
||||
@@ -1789,60 +1758,11 @@ fn detect_row_stripe_table_from_cell_rects(
|
||||
}
|
||||
}
|
||||
if counted > 0 && prose_cells * 5 >= counted {
|
||||
// (a) Long-cell content: overrides the well-distributed
|
||||
// relaxation. The 2-col prose-in-a-frame case populates
|
||||
// both cols (passes well-distributed) but every cell
|
||||
// holds a sentence fragment, so mean cell length is the
|
||||
// discriminator.
|
||||
const PROSE_MEAN_CHAR_THRESHOLD: usize = 65;
|
||||
let mean_chars = total_chars / counted;
|
||||
if mean_chars > PROSE_MEAN_CHAR_THRESHOLD {
|
||||
debug!(
|
||||
" cell-rect rejected: prose-in-frame, mean non-empty cell {} chars > {} (prose words {}/{})",
|
||||
mean_chars, PROSE_MEAN_CHAR_THRESHOLD, prose_cells, counted
|
||||
);
|
||||
return None;
|
||||
}
|
||||
|
||||
// (b) Two text-derived columns are not enough vector evidence once
|
||||
// the content looks prose-like. Real 2-col rect tables still pass
|
||||
// when the column scaffold comes from drawn cell geometry.
|
||||
if columns_from_text && num_cols == 2 {
|
||||
debug!(
|
||||
" cell-rect rejected: prose-in-frame with text-derived 2-col scaffold (mean {} chars, prose words {}/{})",
|
||||
mean_chars, prose_cells, counted
|
||||
);
|
||||
return None;
|
||||
}
|
||||
|
||||
// (c) Well-distributed columns.
|
||||
let filled_cols = (0..num_cols)
|
||||
.filter(|&c| {
|
||||
cells
|
||||
.iter()
|
||||
.filter(|row| {
|
||||
!row.get(c)
|
||||
.map(String::as_str)
|
||||
.unwrap_or("")
|
||||
.trim()
|
||||
.is_empty()
|
||||
})
|
||||
.count()
|
||||
>= 2
|
||||
})
|
||||
.count();
|
||||
let well_distributed = filled_cols * 4 >= num_cols * 3;
|
||||
if !well_distributed {
|
||||
debug!(
|
||||
" cell-rect rejected: {}/{} cells contain prose function words — likely prose ({}/{} cols filled, mean {} chars)",
|
||||
prose_cells, counted, filled_cols, num_cols, mean_chars
|
||||
);
|
||||
return None;
|
||||
}
|
||||
debug!(
|
||||
" cell-rect prose check relaxed: {}/{} cols filled, mean {} chars — table-with-description-col",
|
||||
filled_cols, num_cols, mean_chars
|
||||
" cell-rect rejected: {}/{} cells contain prose function words — likely prose",
|
||||
prose_cells, counted
|
||||
);
|
||||
return None;
|
||||
}
|
||||
}
|
||||
|
||||
@@ -3053,62 +2973,6 @@ mod tests {
|
||||
// If tables were detected, that's also acceptable
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn text_derived_two_col_prose_is_not_cell_rect_table() {
|
||||
let page = 1;
|
||||
let mut rects = Vec::new();
|
||||
for row in 0..8 {
|
||||
rects.push(PdfRect {
|
||||
x: 50.0,
|
||||
y: 100.0 + row as f32 * 20.0,
|
||||
width: 180.0,
|
||||
height: 18.0,
|
||||
page,
|
||||
});
|
||||
}
|
||||
|
||||
let mut items = Vec::new();
|
||||
let left = [
|
||||
"the annual plan was revised",
|
||||
"and the team noted changes",
|
||||
"this section explains limits",
|
||||
"with additional notes below",
|
||||
"the policy was reviewed",
|
||||
"and results are summarized",
|
||||
"this appendix describes scope",
|
||||
"with examples for reference",
|
||||
];
|
||||
let right = [
|
||||
"for each area in the review",
|
||||
"as part of the assessment",
|
||||
"that were applied in context",
|
||||
"to support the conclusion",
|
||||
"for use by the committee",
|
||||
"as shown in the narrative",
|
||||
"that remain under discussion",
|
||||
"to clarify the method",
|
||||
];
|
||||
for row in 0..8 {
|
||||
let y = 104.0 + row as f32 * 20.0;
|
||||
let mut left_item = make_item(left[row], 60.0, y, 9.0);
|
||||
left_item.width = 50.0;
|
||||
items.push(left_item);
|
||||
let mut right_item = make_item(right[row], 150.0, y, 9.0);
|
||||
right_item.width = 50.0;
|
||||
items.push(right_item);
|
||||
}
|
||||
|
||||
let (tables, _hints) = detect_tables_from_rects(&items, &rects, page);
|
||||
assert!(
|
||||
tables.is_empty(),
|
||||
"text-derived two-column prose must not be accepted as a rect table; got {:?}",
|
||||
tables
|
||||
.iter()
|
||||
.map(|t| (t.rows.len(), t.columns.len()))
|
||||
.collect::<Vec<_>>()
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn failed_cluster_no_hint_without_items() {
|
||||
// Rects with no text items inside → no failed-cluster hint generated.
|
||||
|
||||
Binary file not shown.
BIN
Binary file not shown.
BIN
Binary file not shown.
BIN
Binary file not shown.
BIN
Binary file not shown.
BIN
Binary file not shown.
+2
-421
@@ -1189,38 +1189,9 @@ fn test_firecrawl_tagged_pdf_struct_tree() {
|
||||
#[test]
|
||||
fn test_identity_h_no_tounicode_suppresses_garbage() {
|
||||
// shinagawa_identity_h.pdf uses YuGothic with Identity-H encoding and no
|
||||
// usable ToUnicode CMap. The raw CID bytes (e.g. 0x08 0x37, 0x0E 0x0F)
|
||||
// contain non-ASCII high bytes and previously fell through to the
|
||||
// per-byte Latin-1 fallback, producing high-Latin-1 mojibake that
|
||||
// `is_cid_garbage` flagged. The Type0/CID guard in
|
||||
// `extract_text_from_operand` now emits one U+FFFD per CID instead of
|
||||
// mojibake; `detect_encoding_issues` trips on that and suppresses the
|
||||
// markdown / flags the page for OCR — so we still pass this test, but
|
||||
// via the deliberate marker path rather than by accident.
|
||||
// ToUnicode CMap. The raw CID values look like random Latin characters.
|
||||
// We should suppress the garbage and flag the page for OCR.
|
||||
let buf = std::fs::read("tests/fixtures/shinagawa_identity_h.pdf").unwrap();
|
||||
|
||||
// Pre-suppression check: the raw text items must contain the U+FFFD
|
||||
// markers that prove the Type0/CID fallback fired. This pins the
|
||||
// mechanism so a future regression that re-enables Latin-1 mojibake
|
||||
// would fail loudly here, not just silently change the suppression
|
||||
// chain to one that depends on `is_cid_garbage` + high-Latin-1 chars.
|
||||
let items = pdf_inspector::extractor::extract_text_with_positions_mem(&buf).unwrap();
|
||||
let combined: String = items.iter().map(|i| i.text.as_str()).collect();
|
||||
assert!(
|
||||
combined.contains('\u{FFFD}'),
|
||||
"Type0/CID font with unparseable ToUnicode CMap should emit U+FFFD per CID; \
|
||||
got {} chars: {:?}",
|
||||
combined.len(),
|
||||
&combined[..combined.len().min(100)]
|
||||
);
|
||||
assert!(
|
||||
!combined
|
||||
.chars()
|
||||
.any(|c| ('\u{0080}'..='\u{00FF}').contains(&c)),
|
||||
"Latin-1 mojibake (high bytes) must not leak from Type0/CID fallback; got: {:?}",
|
||||
&combined[..combined.len().min(100)]
|
||||
);
|
||||
|
||||
let result = pdf_inspector::process_pdf_mem(&buf).unwrap();
|
||||
|
||||
// Page 1 should be flagged for OCR
|
||||
@@ -2561,61 +2532,6 @@ fn test_auto_expands_under_counted_vector_grid_rows() {
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_auto_keeps_wrapped_header_vector_grid_doc51() {
|
||||
use pdf_inspector::{extract_tables_with_structure_auto_mem, TsrTableInput};
|
||||
|
||||
let buf = std::fs::read("tests/fixtures/government_positions_women.pdf").unwrap();
|
||||
let crop = [0.0, 0.0, 612.0, 792.0];
|
||||
let grid = detect_vector_grid_in_region_mem(&buf, 0, crop, 200.0)
|
||||
.unwrap()
|
||||
.expect("expected doc 51 vector grid");
|
||||
assert_eq!(
|
||||
grid.cell_bboxes.len(),
|
||||
36,
|
||||
"doc 51 should have a 9x4 vector grid"
|
||||
);
|
||||
|
||||
let results = extract_tables_with_structure_auto_mem(
|
||||
&buf,
|
||||
&[TsrTableInput {
|
||||
page: 0,
|
||||
crop_pdf_pt_bbox: crop,
|
||||
render_dpi: 200.0,
|
||||
structure_tokens: grid.structure_tokens,
|
||||
cell_bboxes: grid.cell_bboxes,
|
||||
}],
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
assert_eq!(results.len(), 1);
|
||||
let r = &results[0];
|
||||
assert!(
|
||||
r.fallback_reason.is_none(),
|
||||
"wrapped header/label text should not trigger heuristic fallback: {:?}\n{}",
|
||||
r.fallback_reason,
|
||||
r.markdown
|
||||
);
|
||||
let md = &r.markdown;
|
||||
assert!(md.contains("Government Position"), "missing header: {md}");
|
||||
assert!(
|
||||
md.contains("Aquino Administration"),
|
||||
"missing Aquino header: {md}"
|
||||
);
|
||||
assert!(
|
||||
md.contains("Ramos Administration"),
|
||||
"missing Ramos header: {md}"
|
||||
);
|
||||
assert!(
|
||||
md.contains("City Municipal Councilor"),
|
||||
"row label was truncated: {md}"
|
||||
);
|
||||
assert!(
|
||||
!md.contains("|Position||Administration"),
|
||||
"heuristic fallback split the header row: {md}"
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_auto_returns_empty_inputs() {
|
||||
use pdf_inspector::extract_tables_with_structure_auto_mem;
|
||||
@@ -3029,338 +2945,3 @@ fn test_extract_pages_markdown_path_none_returns_all_pages() {
|
||||
let result = extract_pages_markdown(path, None).unwrap();
|
||||
assert_eq!(result.pages.len() as u32, page_count);
|
||||
}
|
||||
|
||||
// ============================================================================
|
||||
// PROBE: investigate dense-cell text-assignment failure mode (failure mode 2)
|
||||
// ============================================================================
|
||||
|
||||
fn synthetic_wide_row_pdf() -> Vec<u8> {
|
||||
use lopdf::content::{Content, Operation};
|
||||
use lopdf::{dictionary, Document, Object, Stream};
|
||||
|
||||
let mut doc = Document::with_version("1.5");
|
||||
let pages_id = doc.new_object_id();
|
||||
let page_id = doc.new_object_id();
|
||||
let font_id = doc.new_object_id();
|
||||
let content_id = doc.new_object_id();
|
||||
|
||||
doc.objects.insert(
|
||||
font_id,
|
||||
dictionary! {
|
||||
"Type" => "Font",
|
||||
"Subtype" => "Type1",
|
||||
"BaseFont" => "Helvetica",
|
||||
}
|
||||
.into(),
|
||||
);
|
||||
|
||||
let operations = vec![
|
||||
Operation::new("BT", vec![]),
|
||||
Operation::new("Tf", vec!["F1".into(), 10.into()]),
|
||||
Operation::new("Td", vec![20.into(), 700.into()]),
|
||||
// A single Tj that visually spans multiple cells. This mirrors PDFs
|
||||
// where a row's address/role/email columns are emitted as one literal
|
||||
// string with embedded spaces, producing one wide TextItem.
|
||||
Operation::new(
|
||||
"Tj",
|
||||
vec![Object::string_literal("Name JobTitle Email Phone")],
|
||||
),
|
||||
Operation::new("ET", vec![]),
|
||||
];
|
||||
let content = Content { operations }.encode().unwrap();
|
||||
doc.objects
|
||||
.insert(content_id, Stream::new(dictionary! {}, content).into());
|
||||
|
||||
doc.objects.insert(
|
||||
page_id,
|
||||
dictionary! {
|
||||
"Type" => "Page",
|
||||
"Parent" => pages_id,
|
||||
"MediaBox" => vec![0.into(), 0.into(), 200.into(), 800.into()],
|
||||
"Resources" => dictionary! {
|
||||
"Font" => dictionary! {
|
||||
"F1" => font_id,
|
||||
},
|
||||
},
|
||||
"Contents" => content_id,
|
||||
}
|
||||
.into(),
|
||||
);
|
||||
doc.objects.insert(
|
||||
pages_id,
|
||||
dictionary! {
|
||||
"Type" => "Pages",
|
||||
"Kids" => vec![page_id.into()],
|
||||
"Count" => 1,
|
||||
}
|
||||
.into(),
|
||||
);
|
||||
let catalog_id = doc.add_object(dictionary! {
|
||||
"Type" => "Catalog",
|
||||
"Pages" => pages_id,
|
||||
});
|
||||
doc.trailer.set("Root", catalog_id);
|
||||
|
||||
let mut bytes = Vec::new();
|
||||
doc.save_to(&mut bytes).unwrap();
|
||||
bytes
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_extract_tables_with_structure_distributes_wide_item_across_cells() {
|
||||
use pdf_inspector::{extract_tables_with_structure_cells_mem, TsrTableInput};
|
||||
|
||||
// Reproduces failure mode 2: a row of multi-token text rendered as one
|
||||
// Tj produces a single wide TextItem that visually spans multiple cells.
|
||||
// The current first-match-by-center routing parks the entire item in
|
||||
// whichever cell holds the item's center, leaving the other cells empty.
|
||||
// See production samples in scrape_id 019de788-ff41-... where 10-column
|
||||
// grids ended up with row text packed into one cell.
|
||||
let buf = synthetic_wide_row_pdf();
|
||||
|
||||
// Helvetica 10pt with width=0 falls back to char_count*font_size*0.5.
|
||||
// "Name JobTitle Email Phone" is 25 chars → effective_width 125pt,
|
||||
// text starts at PDF (20, 700), top-down y=[90, 100], char_w≈5pt.
|
||||
// Tokens land at:
|
||||
// "Name" chars 0-3 center≈x=30
|
||||
// "JobTitle" chars 5-12 center≈x=65
|
||||
// "Email" chars 14-18 center≈x=100
|
||||
// "Phone" chars 20-24 center≈x=130
|
||||
let cell_bboxes = vec![
|
||||
poly(15.0, 88.0, 50.0, 102.0),
|
||||
poly(50.0, 88.0, 85.0, 102.0),
|
||||
poly(85.0, 88.0, 120.0, 102.0),
|
||||
poly(120.0, 88.0, 155.0, 102.0),
|
||||
];
|
||||
|
||||
let tokens: Vec<String> = [
|
||||
"<table>",
|
||||
"<tbody>",
|
||||
"<tr>",
|
||||
"<td></td>",
|
||||
"<td></td>",
|
||||
"<td></td>",
|
||||
"<td></td>",
|
||||
"</tr>",
|
||||
"</tbody>",
|
||||
"</table>",
|
||||
]
|
||||
.into_iter()
|
||||
.map(String::from)
|
||||
.collect();
|
||||
|
||||
let cells_lists = extract_tables_with_structure_cells_mem(
|
||||
&buf,
|
||||
&[TsrTableInput {
|
||||
page: 0,
|
||||
crop_pdf_pt_bbox: [0.0, 0.0, 200.0, 800.0],
|
||||
render_dpi: 72.0,
|
||||
structure_tokens: tokens,
|
||||
cell_bboxes,
|
||||
}],
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
let cells = &cells_lists[0];
|
||||
assert_eq!(cells.len(), 4);
|
||||
assert_eq!(
|
||||
cells[0].text, "Name",
|
||||
"cell 0 should hold 'Name', got {:?}",
|
||||
cells[0].text
|
||||
);
|
||||
assert_eq!(
|
||||
cells[1].text, "JobTitle",
|
||||
"cell 1 should hold 'JobTitle', got {:?}",
|
||||
cells[1].text
|
||||
);
|
||||
assert_eq!(
|
||||
cells[2].text, "Email",
|
||||
"cell 2 should hold 'Email', got {:?}",
|
||||
cells[2].text
|
||||
);
|
||||
assert_eq!(
|
||||
cells[3].text, "Phone",
|
||||
"cell 3 should hold 'Phone', got {:?}",
|
||||
cells[3].text
|
||||
);
|
||||
}
|
||||
|
||||
// ============================================================================
|
||||
// PROPER TEST: synthetic Type0/Identity-H PDF with malformed ToUnicode CMap
|
||||
// ============================================================================
|
||||
//
|
||||
// Complements the existing real-PDF fixture `shinagawa_identity_h.pdf` by
|
||||
// building a minimal Type0 / Identity-H font in process. We control:
|
||||
// * the byte stream emitted by Tj (a 2-byte CID containing one high byte),
|
||||
// * the malformed ToUnicode contents (junk bytes that won't parse), and
|
||||
// * the DescendantFonts shape (just enough for `parse_type0_widths` to set
|
||||
// `is_cid=true`, which is what the new guard in `extract_text_from_operand`
|
||||
// keys off of).
|
||||
// No fixture file or external license to worry about.
|
||||
|
||||
fn synthetic_type0_broken_tounicode_pdf() -> Vec<u8> {
|
||||
use lopdf::content::{Content, Operation};
|
||||
use lopdf::{dictionary, Document, Object, Stream};
|
||||
|
||||
let mut doc = Document::with_version("1.5");
|
||||
let pages_id = doc.new_object_id();
|
||||
let page_id = doc.new_object_id();
|
||||
let font_id = doc.new_object_id();
|
||||
let cid_font_id = doc.new_object_id();
|
||||
let descriptor_id = doc.new_object_id();
|
||||
let tounicode_id = doc.new_object_id();
|
||||
let cid_system_info_id = doc.new_object_id();
|
||||
let content_id = doc.new_object_id();
|
||||
|
||||
// Type0 font with Identity-H encoding and a broken ToUnicode reference.
|
||||
doc.objects.insert(
|
||||
font_id,
|
||||
dictionary! {
|
||||
"Type" => "Font",
|
||||
"Subtype" => "Type0",
|
||||
"BaseFont" => "AAAAAA+SyntheticCID",
|
||||
"Encoding" => "Identity-H",
|
||||
"DescendantFonts" => vec![cid_font_id.into()],
|
||||
"ToUnicode" => tounicode_id,
|
||||
}
|
||||
.into(),
|
||||
);
|
||||
|
||||
// CIDSystemInfo and a minimal CIDFontType2 descendant. parse_type0_widths
|
||||
// walks DescendantFonts → returns FontWidthInfo with is_cid=true. That's
|
||||
// the only thing the new Latin-1 guard needs to see.
|
||||
doc.objects.insert(
|
||||
cid_system_info_id,
|
||||
dictionary! {
|
||||
"Registry" => Object::string_literal("Adobe"),
|
||||
"Ordering" => Object::string_literal("Identity"),
|
||||
"Supplement" => 0,
|
||||
}
|
||||
.into(),
|
||||
);
|
||||
doc.objects.insert(
|
||||
cid_font_id,
|
||||
dictionary! {
|
||||
"Type" => "Font",
|
||||
"Subtype" => "CIDFontType2",
|
||||
"BaseFont" => "AAAAAA+SyntheticCID",
|
||||
"CIDSystemInfo" => cid_system_info_id,
|
||||
"FontDescriptor" => descriptor_id,
|
||||
"DW" => 1000,
|
||||
}
|
||||
.into(),
|
||||
);
|
||||
doc.objects.insert(
|
||||
descriptor_id,
|
||||
dictionary! {
|
||||
"Type" => "FontDescriptor",
|
||||
"FontName" => "AAAAAA+SyntheticCID",
|
||||
"Flags" => 4,
|
||||
"FontBBox" => vec![Object::Integer(-100), Object::Integer(-100), 1000.into(), 1000.into()],
|
||||
"ItalicAngle" => 0,
|
||||
"Ascent" => 800,
|
||||
"Descent" => Object::Integer(-200),
|
||||
"CapHeight" => 700,
|
||||
"StemV" => 80,
|
||||
}
|
||||
.into(),
|
||||
);
|
||||
|
||||
// Intentionally malformed ToUnicode stream — just junk bytes. ToUnicode
|
||||
// CMap parsing will fail, so `font_cmaps.get_by_obj` returns None and
|
||||
// `has_cmap` stays false. The reference still exists in the font dict,
|
||||
// so `font_tounicode_refs` contains the entry — but the new guard now
|
||||
// routes off `is_cid` from font_widths instead, which is robust to a
|
||||
// failed CMap parse.
|
||||
doc.objects.insert(
|
||||
tounicode_id,
|
||||
Stream::new(dictionary! {}, b"this is not a valid CMap stream".to_vec()).into(),
|
||||
);
|
||||
|
||||
// Tj with a 2-byte CID stream containing a non-ASCII high byte.
|
||||
// Pre-fix this would have decoded as Latin-1 to "\u{00CD}\u{00D9}" ("ÍÙ").
|
||||
// Post-fix it should produce U+FFFD per CID.
|
||||
let cid_bytes = vec![0xCD_u8, 0xD9, 0xCD, 0xD9];
|
||||
let operations = vec![
|
||||
Operation::new("BT", vec![]),
|
||||
Operation::new("Tf", vec!["F0".into(), 12.into()]),
|
||||
Operation::new("Td", vec![50.into(), 100.into()]),
|
||||
Operation::new(
|
||||
"Tj",
|
||||
vec![Object::String(cid_bytes, lopdf::StringFormat::Hexadecimal)],
|
||||
),
|
||||
Operation::new("ET", vec![]),
|
||||
];
|
||||
let content = Content { operations }.encode().unwrap();
|
||||
doc.objects
|
||||
.insert(content_id, Stream::new(dictionary! {}, content).into());
|
||||
|
||||
doc.objects.insert(
|
||||
page_id,
|
||||
dictionary! {
|
||||
"Type" => "Page",
|
||||
"Parent" => pages_id,
|
||||
"MediaBox" => vec![0.into(), 0.into(), 200.into(), 200.into()],
|
||||
"Resources" => dictionary! {
|
||||
"Font" => dictionary! {
|
||||
"F0" => font_id,
|
||||
},
|
||||
},
|
||||
"Contents" => content_id,
|
||||
}
|
||||
.into(),
|
||||
);
|
||||
doc.objects.insert(
|
||||
pages_id,
|
||||
dictionary! {
|
||||
"Type" => "Pages",
|
||||
"Kids" => vec![page_id.into()],
|
||||
"Count" => 1,
|
||||
}
|
||||
.into(),
|
||||
);
|
||||
let catalog_id = doc.add_object(dictionary! {
|
||||
"Type" => "Catalog",
|
||||
"Pages" => pages_id,
|
||||
});
|
||||
doc.trailer.set("Root", catalog_id);
|
||||
|
||||
let mut bytes = Vec::new();
|
||||
doc.save_to(&mut bytes).unwrap();
|
||||
bytes
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_synthetic_type0_broken_tounicode_emits_fffd_not_latin1_mojibake() {
|
||||
let buf = synthetic_type0_broken_tounicode_pdf();
|
||||
|
||||
let items = pdf_inspector::extractor::extract_text_with_positions_mem(&buf).unwrap();
|
||||
let combined: String = items.iter().map(|i| i.text.as_str()).collect();
|
||||
|
||||
// Mojibake leak check: 2-byte CID 0xCDD9 must NOT come out as "ÍÙ"
|
||||
// (U+00CD U+00D9). That was the production scrape symptom.
|
||||
assert!(
|
||||
!combined.contains('\u{00CD}'),
|
||||
"Latin-1 mojibake leaked from Type0 font: {combined:?}"
|
||||
);
|
||||
assert!(
|
||||
!combined.contains('\u{00D9}'),
|
||||
"Latin-1 mojibake leaked from Type0 font: {combined:?}"
|
||||
);
|
||||
|
||||
// Marker presence: Type0/CID + non-ASCII bytes must produce U+FFFD so
|
||||
// `detect_encoding_issues` can flag the page for OCR downstream.
|
||||
assert!(
|
||||
combined.contains('\u{FFFD}'),
|
||||
"Type0 font with malformed ToUnicode CMap should emit U+FFFD per CID; got: {combined:?}"
|
||||
);
|
||||
|
||||
// End-to-end check: the page is correctly routed to OCR.
|
||||
let result = pdf_inspector::process_pdf_mem(&buf).unwrap();
|
||||
assert!(
|
||||
result.pages_needing_ocr.contains(&1),
|
||||
"Type0 page with broken ToUnicode + non-ASCII bytes must be flagged for OCR; \
|
||||
pages_needing_ocr={:?}",
|
||||
result.pages_needing_ocr
|
||||
);
|
||||
}
|
||||
|
||||
@@ -54,14 +54,9 @@ company other than a life insurance company shall make a return on Form 1120PC.
|
||||
|
||||
annual statement (or a pro forma annual statement), including the underwriting and investment exhibit for the year covered by such return.
|
||||
|
||||
(3) Foreign insurance companies. The provisions of paragraphs (c)(1) and
|
||||
(c)(2) of this section concerning the returns and statements of insurance companies subject to tax under section 801 or section 831 also apply to foreign insurance companies subject to tax under those sections, except that the copy of the annual statement required to be submitted with the return shall, in the case of a foreign insurance company that is not required to file an annual statement, be a copy of the pro forma annual statement relating to the United States business of such company.
|
||||
(4) Exception for insurance companies filing their Federal income tax returns
|
||||
electronically. If an insurance company described in paragraph (c)(1), (c)(2), or
|
||||
|
||||
(c)(3) of this section files its Federal income tax return electronically, it should not include on or with such return its annual statement (or pro forma annual statement), or any portion thereof. Such statement must be available at all times for inspection by authorized Internal Revenue Service officers or employees and retained for so long as such statements may be material in the administration of any internal revenue law. See §1.6001-1(e).
|
||||
(5) Definition. For purposes of this section, the term annual statement means
|
||||
the annual statement, the form of which is approved by the National Association of Insurance Commissioners (NAIC), which is filed by an insurance company for the year with the insurance departments of States, Territories, and the District of
|
||||
||(3) Foreign insurance companies. The provisions of paragraphs (c)(1) and|
|
||||
|---|---|
|
||||
||(c)(2) of this section concerning the returns and statements of insurance companies subject to tax under section 801 or section 831 also apply to foreign insurance companies subject to tax under those sections, except that the copy of the annual statement required to be submitted with the return shall, in the case of a foreign insurance company that is not required to file an annual statement, be a copy of the pro forma annual statement relating to the United States business of such company. (4) Exception for insurance companies filing their Federal income tax returns electronically. If an insurance company described in paragraph (c)(1), (c)(2), or (c)(3) of this section files its Federal income tax return electronically, it should not include on or with such return its annual statement (or pro forma annual statement), or any portion thereof. Such statement must be available at all times for inspection by authorized Internal Revenue Service officers or employees and retained for so long as such statements may be material in the administration of any internal revenue law. See §1.6001-1(e). (5) Definition. For purposes of this section, the term annual statement means the annual statement, the form of which is approved by the National Association of Insurance Commissioners (NAIC), which is filed by an insurance company for the year with the insurance departments of States, Territories, and the District of|
|
||||
|
||||
Columbia. The term annual statement also includes a pro forma annual statement if the insurance company is not required to file the NAIC annual statement.
|
||||
|
||||
@@ -206,4 +201,3 @@ CFR part or section where Current OMB identified or described control No.
|
||||
Deputy Commissioner for Services and Enforcement.
|
||||
|
||||
Approved: May 19, 2006 Eric Solomon Acting Deputy Assistant Secretary of the Treasury (Tax Policy).
|
||||
|
||||
|
||||
Reference in New Issue
Block a user