pdftract/tests/fixtures/profiles/slide_deck/academic_lecture-expected.json
jedarden 21fcd902d1 feat(pdftract-2vajs): implement slide_deck profile with fixtures and tests
Implements the slide_deck document profile for PowerPoint/Keynote/Google
Slides exports as PDF. Includes 5 fixtures, expected outputs, and regression
tests.

Components:
- profiles/builtin/slide_deck/profile.yaml - Profile configuration
- tests/fixtures/profiles/slide_deck/ - 5 PDF fixtures with expected outputs
- crates/pdftract-cli/tests/test_slide_deck.rs - Regression tests (12 PASS)

Fixtures cover:
1. pitch_deck - Sales pitch (10 slides)
2. academic_lecture - Academic lecture (40 slides)
3. corporate_kickoff - Corporate kickoff (15 slides)
4. bilingual_deck - Bilingual EN/ES (12 slides)
5. googleslides_handout - Google Slides handout mode (4 pages, 3 slides/page)

Extracted fields: title, presenter, date, slide_titles

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-05-27 21:12:24 -04:00

59 lines
1.4 KiB
JSON

{
"metadata": {
"document_type": "slide_deck",
"document_type_confidence": 0.92,
"document_type_reasons": [
"page count 40 in range [3, 200]",
"font diversity 4 in range [2, 10]",
"text contains 'slides' (1 hits)",
"text contains 'presentation' (1 hits)"
],
"profile_name": "slide_deck",
"profile_version": "1.0.0",
"profile_fields": {
"title": "Introduction to Machine Learning",
"presenter": "Prof. Robert Chen, PhD",
"date": null,
"slide_titles": [
"Introduction to Machine Learning",
"Overview",
"What is a Neural Network?",
"Perceptrons",
"Multi-Layer Networks",
"Activation Functions",
"Backpropagation",
"Loss Functions",
"Optimization",
"Regularization",
"Convolutional Networks",
"Recurrent Networks",
"Transformer Architecture",
"Attention Mechanisms",
"Training Strategies",
"Hyperparameter Tuning",
"Evaluation Metrics",
"Case Studies",
"Current Research",
"Future Directions",
"Summary",
"References",
"Q1",
"Q2",
"Q3",
"Q4",
"Q5",
"Q6",
"Q7",
"Q8",
"Q9",
"Q10",
"Q11",
"Q12",
"Q13",
"Q14",
"Q15",
"Thank You"
]
}
}
}