cd /home/daytona/workspace/attachments/02e56429-6de7-4c33-8078-5e2e4bcf0381 && python3 -c " import pdfplumber with pdfplumber.open('physiology practical charts.pdf') as pdf: print(f'Total pages: {len(pdf.pages)}') for i, page in enumerate(pdf.pages): text = page.extract_text() print(f'\\n=== PAGE {i+1} ===') if text: print(text[:2000]) else: print('[No extractable text - may be image/scan]') "

python3 -c " import subprocess import os pdf_path = '/home/daytona/workspace/attachments/02e56429-6de7-4c33-8078-5e2e4bcf0381/physiology practical charts.pdf' # Convert first few pages to images using pdftoppm os.makedirs('/home/daytona/workspace/physio_pages', exist_ok=True) # Convert pages 1-5 first to check content result = subprocess.run( ['pdftoppm', '-r', '150', '-l', '5', pdf_path, '/home/daytona/workspace/physio_pages/page'], capture_output=True, text=True ) print('Return code:', result.returncode) print('STDOUT:', result.stdout) print('STDERR:', result.stderr) print('Files created:') for f in sorted(os.listdir('/home/daytona/workspace/physio_pages')): print(f) "

python3 -c " import subprocess import os # Run OCR on all 123 pages using tesseract pdf_path = '/home/daytona/workspace/attachments/02e56429-6de7-4c33-8078-5e2e4bcf0381/physiology practical charts.pdf' pages_dir = '/home/daytona/workspace/physio_pages' # Convert ALL pages to images result = subprocess.run( ['pdftoppm', '-r', '150', pdf_path, pages_dir + '/page'], capture_output=True, text=True, timeout=300 ) print('Conversion done. Return code:', result.returncode) files = sorted(os.listdir(pages_dir)) print(f'Total images: {len(files)}') " 2>&1

python3 -c " import subprocess import os pages_dir = '/home/daytona/workspace/physio_pages' ocr_dir = '/home/daytona/workspace/physio_ocr' os.makedirs(ocr_dir, exist_ok=True) files = sorted([f for f in os.listdir(pages_dir) if f.endswith('.ppm')]) print(f'Running OCR on {len(files)} pages...') all_text = {} for i, fname in enumerate(files): page_num = i + 1 img_path = os.path.join(pages_dir, fname) out_base = os.path.join(ocr_dir, f'page_{page_num:03d}') result = subprocess.run( ['tesseract', img_path, out_base, '-l', 'eng'], capture_output=True, text=True ) txt_path = out_base + '.txt' if os.path.exists(txt_path): with open(txt_path) as f: text = f.read().strip() all_text[page_num] = text if page_num % 20 == 0: print(f'Done {page_num}/123') # Save combined combined_path = '/home/daytona/workspace/physio_ocr/all_pages_ocr.txt' with open(combined_path, 'w') as f: for pg, txt in sorted(all_text.items()): f.write(f'\\n\\n=== PAGE {pg} ===\\n') f.write(txt) print('OCR complete. Combined file written.') print(f'Total pages with text: {sum(1 for t in all_text.values() if len(t) > 20)}') " 2>&1

ls -la /home/daytona/workspace/physio_ocr/ && rm -rf /home/daytona/workspace/physio_ocr && mkdir -p /home/daytona/workspace/physio_ocr && ls -la /home/daytona/workspace/physio_ocr/

# Use pytesseract with PIL for OCR - more reliable approach python3 << 'EOF' import subprocess import os pages_dir = '/home/daytona/workspace/physio_pages' ocr_out = '/home/daytona/workspace/physio_ocr_all.txt' files = sorted([f for f in os.listdir(pages_dir) if f.endswith('.ppm')]) print(f'Total pages: {len(files)}') all_text = [] for i, fname in enumerate(files): page_num = i + 1 img_path = os.path.join(pages_dir, fname) result = subprocess.run( ['tesseract', img_path, 'stdout', '-l', 'eng', '--psm', '6'], capture_output=True, text=True ) text = result.stdout.strip() all_text.append(f'\n\n=== PAGE {page_num} ===\n{text}') if page_num % 25 == 0: print(f'Done {page_num}/123') with open(ocr_out, 'w') as f: f.write('\n'.join(all_text)) print(f'Done! Written to {ocr_out}') pages_with_text = sum(1 for t in all_text if len(t) > 30) print(f'Pages with content: {pages_with_text}') EOF

wc -l /home/daytona/workspace/physio_ocr_all.txt && wc -c /home/daytona/workspace/physio_ocr_all.txt

python3 -c " from PIL import Image import os pages_dir = '/home/daytona/workspace/physio_pages' png_dir = '/home/daytona/workspace/physio_png' os.makedirs(png_dir, exist_ok=True) # Convert selected pages to PNG for visual analysis # Sample pages: 1, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 123 sample_pages = [1, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 123] for pg in sample_pages: ppm_file = os.path.join(pages_dir, f'page-{pg:03d}.ppm') png_file = os.path.join(png_dir, f'page_{pg:03d}.png') if os.path.exists(ppm_file): img = Image.open(ppm_file) img.save(png_file) print(f'Converted page {pg}: {img.size}') print('Done converting sample pages to PNG') "

python3 -c " # Try reading later pages where charts might have cleaner text import subprocess, os pages_dir = '/home/daytona/workspace/physio_pages' # Try rotating pages 90 degrees and re-OCRing - charts are often landscape # Also try with different PSM modes files = sorted([f for f in os.listdir(pages_dir) if f.endswith('.ppm')]) # Sample every 10th page, with auto-rotation for pg in [5, 11, 15, 25, 35, 45, 55, 65, 75, 85, 95, 105, 115]: fname = f'page-{pg:03d}.ppm' img_path = os.path.join(pages_dir, fname) if not os.path.exists(img_path): continue result = subprocess.run( ['tesseract', img_path, 'stdout', '-l', 'eng', '--psm', '3', '--oem', '3'], capture_output=True, text=True ) text = result.stdout.strip() if len(text) > 50: print(f'\\n=== PAGE {pg} ===') print(text[:600]) print('...') " 2>&1 | head -300

python3 << 'EOF' import subprocess import os pages_dir = '/home/daytona/workspace/physio_pages' ocr_out = '/home/daytona/workspace/physio_ocr_v2.txt' files = sorted([f for f in os.listdir(pages_dir) if f.endswith('.ppm')]) print(f'Total pages: {len(files)}') all_text = [] for i, fname in enumerate(files): page_num = i + 1 img_path = os.path.join(pages_dir, fname) result = subprocess.run( ['tesseract', img_path, 'stdout', '-l', 'eng', '--psm', '3', '--oem', '3'], capture_output=True, text=True ) text = result.stdout.strip() all_text.append((page_num, text)) if page_num % 25 == 0: print(f'Done {page_num}/123') with open(ocr_out, 'w') as f: for pg, txt in all_text: f.write(f'\n\n=== PAGE {pg} ===\n{txt}') print(f'Done! Written to {ocr_out}') pages_with_text = sum(1 for _, t in all_text if len(t) > 50) print(f'Pages with substantial text: {pages_with_text}') EOF