cd /home/daytona/workspace && python3 -c " import pdfplumber pdf_path = '/home/daytona/workspace/attachments/d6a8d7dd-559f-4af4-b47f-00b216cd9de0/SRI SIR SLIDE14-6.pdf' with pdfplumber.open(pdf_path) as pdf: print(f'Total pages: {len(pdf.pages)}') for i, page in enumerate(pdf.pages): print(f'\n========== PAGE {i+1} ==========') text = page.extract_text() if text: print(text) else: print('[No extractable text on this page]') "
cd /home/daytona/workspace && python3 -c " from pdf2image import convert_from_path import os pdf_path = '/home/daytona/workspace/attachments/d6a8d7dd-559f-4af4-b47f-00b216cd9de0/SRI SIR SLIDE14-6.pdf' output_dir = '/home/daytona/workspace/attachments/d6a8d7dd-559f-4af4-b47f-00b216cd9de0/' images = convert_from_path(pdf_path, dpi=200) for i, img in enumerate(images): out_path = os.path.join(output_dir, f'slide_page_{i+1}.png') img.save(out_path, 'PNG') print(f'Saved: {out_path}') print('Done') "
cd /home/daytona/workspace && python3 -c " import base64, json with open('/home/daytona/workspace/attachments/d6a8d7dd-559f-4af4-b47f-00b216cd9de0/slide_page_1.png', 'rb') as f: data = f.read() print(f'File size: {len(data)} bytes') print('File exists and is readable') "
cd /home/daytona/workspace && python3 -c " import pytesseract from PIL import Image img = Image.open('/home/daytona/workspace/attachments/d6a8d7dd-559f-4af4-b47f-00b216cd9de0/slide_page_1.png') text = pytesseract.image_to_string(img, config='--psm 6') print(text) "
cd /home/daytona/workspace && python3 -c " from PIL import Image # Resize and compress for easier viewing img = Image.open('/home/daytona/workspace/attachments/d6a8d7dd-559f-4af4-b47f-00b216cd9de0/slide_page_1.png') print(f'Original size: {img.size}') # Resize to smaller img_small = img.resize((1600, int(img.height * 1600 / img.width)), Image.LANCZOS) img_small.save('/home/daytona/workspace/attachments/d6a8d7dd-559f-4af4-b47f-00b216cd9de0/slide_small.jpg', 'JPEG', quality=85) print(f'Saved compressed version') import os size = os.path.getsize('/home/daytona/workspace/attachments/d6a8d7dd-559f-4af4-b47f-00b216cd9de0/slide_small.jpg') print(f'Compressed size: {size} bytes') "
cd /home/daytona/workspace && python3 -c " from PIL import Image import os # Make it even smaller img = Image.open('/home/daytona/workspace/attachments/d6a8d7dd-559f-4af4-b47f-00b216cd9de0/slide_page_1.png') img_small = img.resize((800, int(img.height * 800 / img.width)), Image.LANCZOS) img_small.save('/home/daytona/workspace/attachments/d6a8d7dd-559f-4af4-b47f-00b216cd9de0/slide_tiny.jpg', 'JPEG', quality=75) size = os.path.getsize('/home/daytona/workspace/attachments/d6a8d7dd-559f-4af4-b47f-00b216cd9de0/slide_tiny.jpg') print(f'Tiny size: {size} bytes') "
Face developmental anomalies

| Prominence | Structures it forms |
|---|---|
| Frontonasal | Forehead, bridge of nose, medial & lateral nasal prominences |
| Medial nasal | Philtrum of upper lip, premaxilla, nasal tip & septum |
| Lateral nasal | Alae of nose |
| Maxillary | Cheeks, lateral upper lip, secondary palate |
| Mandibular | Lower jaw, lower lip |




| Feature | Cleft Lip ± Palate | Isolated Cleft Palate |
|---|---|---|
| Incidence | ~1/700 births | ~1/1500 births |
| Sex | More in males (65%) | More in females (55%) |
| Ethnicity | Highest: Asian, Native American (3.5/1000); Lowest: African American (1/1000) | - |