I will send you a pdf of previous year question paper bank. It is of physiology for mbbs 1st year. As per the marks distribution can you please solve that paper for me with relevant flowcharts and diagrams wherever needed and then convert it into a downloadable pdf format and then send it tome?
Do it
cd /home/daytona/workspace/attachments/212f3d7e-ee35-4762-8af1-90f97a443895/ && python3 -c " import pdfplumber with pdfplumber.open('inbound6454457852390801075.pdf') as pdf: print(f'Pages: {len(pdf.pages)}') for i, page in enumerate(pdf.pages): print(f'--- PAGE {i+1} ---') print(page.extract_text()) "
python3 -c " import subprocess result = subprocess.run(['tesseract', '--version'], capture_output=True, text=True) print(result.stdout) print(result.stderr) "
mkdir -p /home/daytona/workspace/physio-qp/ocr_pages && cd /home/daytona/workspace/physio-qp && convert -density 200 /home/daytona/workspace/attachments/212f3d7e-ee35-4762-8af1-90f97a443895/inbound6454457852390801075.pdf -quality 90 ocr_pages/page_%03d.png 2>&1 | head -5 && echo "DONE" && ls ocr_pages/ | head -10
python3 -c " from pdf2image import convert_from_path pages = convert_from_path('/home/daytona/workspace/attachments/212f3d7e-ee35-4762-8af1-90f97a443895/inbound6454457852390801075.pdf', dpi=200, first_page=1, last_page=5) for i, p in enumerate(pages): p.save(f'/home/daytona/workspace/physio-qp/ocr_pages/page_{i+1:03d}.png') print('done', len(pages)) "
python3 -c " import pytesseract from PIL import Image import os pages_dir = '/home/daytona/workspace/physio-qp/ocr_pages' all_text = '' for i in range(1, 6): img_path = f'{pages_dir}/page_{i:03d}.png' img = Image.open(img_path) text = pytesseract.image_to_string(img) all_text += f'\n\n=== PAGE {i} ===\n' + text print(all_text) "
python3 -c " from pdf2image import convert_from_path pages = convert_from_path('/home/daytona/workspace/attachments/212f3d7e-ee35-4762-8af1-90f97a443895/inbound6454457852390801075.pdf', dpi=200, first_page=6, last_page=39) for i, p in enumerate(pages): p.save(f'/home/daytona/workspace/physio-qp/ocr_pages/page_{i+6:03d}.png') print('done', len(pages)) "
python3 -c " from pdf2image import convert_from_path import pytesseract from PIL import Image pdf_path = '/home/daytona/workspace/attachments/212f3d7e-ee35-4762-8af1-90f97a443895/inbound6454457852390801075.pdf' all_text = '' # Process in batches of 5 for batch_start in range(6, 40, 5): batch_end = min(batch_start+4, 39) pages = convert_from_path(pdf_path, dpi=150, first_page=batch_start, last_page=batch_end) for i, p in enumerate(pages): page_num = batch_start + i text = pytesseract.image_to_string(p) all_text += f'\n\n=== PAGE {page_num} ===\n' + text print(f'Batch {batch_start}-{batch_end} done') with open('/home/daytona/workspace/physio-qp/all_questions.txt', 'w') as f: f.write(all_text) print('Saved') "
Ok