0a52cff8a7
- Added extract_meaning_kernels.py for processing PDF diagrams - Extracts text using OCR (Tesseract) when available - Analyzes diagram structure (type, dimensions, orientation) - Generates structured meaning kernels with metadata - Outputs JSON (machine-readable) and Markdown (human-readable) - Includes test pipeline and documentation - Supports single files and batch processing Pipeline components: - DiagramProcessor: Main processing engine - MeaningKernel: Structured kernel representation - PDF to image conversion - OCR text extraction - Structure analysis - Kernel generation with confidence scoring Acceptance criteria met: ✓ Processes academic PDF diagrams ✓ Extracts structured text meaning kernels ✓ Generates machine-readable JSON output ✓ Includes human-readable reports ✓ Supports batch processing ✓ Provides confidence scoring
26 lines
477 B
Plaintext
26 lines
477 B
Plaintext
# Multimodal Meaning Kernel Extraction Pipeline
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# Required Python dependencies
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# Image processing
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Pillow>=10.0.0
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# OCR (Optical Character Recognition)
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pytesseract>=0.3.10
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# PDF processing
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pdf2image>=1.16.3
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# Optional: Enhanced computer vision
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# opencv-python>=4.8.0
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# numpy>=1.24.0
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# Optional: Machine learning for diagram classification
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# scikit-learn>=1.3.0
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# torch>=2.0.0
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# torchvision>=0.15.0
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# Development and testing
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# pytest>=7.4.0
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# black>=23.0.0
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# flake8>=6.0.0
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