Give answers to these clinical questions with reasons
~/
clinical biochemistry case interpretation laboratory diagnosis reference overview
mkdir -p "/tmp/workspace/biochem-clinical-longs/output" && python -c "import pdfplumber; p='/tmp/workspace/attachments/b7b680e7-8d68-4c76-8cde-a9928d1593da/BIOCHEM CLINICAL LONGS .pdf'; out='/tmp/workspace/biochem-clinical-longs/output/extracted.txt'; pdf=pdfplumber.open(p); print('pages',len(pdf.pages)); open(out,'w',encoding='utf-8').write('\\n\\n'.join('--- PAGE %d ---\\n%s' % (i+1,(page.extract_text() or '')) for i,page in enumerate(pdf.pages))); pdf.close()"
python -c "import fitz, os; p='/tmp/workspace/attachments/b7b680e7-8d68-4c76-8cde-a9928d1593da/BIOCHEM CLINICAL LONGS .pdf'; d='/tmp/workspace/biochem-clinical-longs/output/rendered'; os.makedirs(d,exist_ok=True); doc=fitz.open(p); [doc[i].get_pixmap(matrix=fitz.Matrix(1.7,1.7),alpha=False).save(f'{d}/page_{i+1:02d}.png') for i in range(len(doc))]; print(len(doc))"
python -c "from pypdf import PdfReader; from PIL import Image; import io,os; p='/tmp/workspace/attachments/b7b680e7-8d68-4c76-8cde-a9928d1593da/BIOCHEM CLINICAL LONGS .pdf'; d='/tmp/workspace/biochem-clinical-longs/output/rendered'; os.makedirs(d,exist_ok=True); r=PdfReader(p); print('pages',len(r.pages)); for n,page in enumerate(r.pages,1): ims=list(page.images); print(n,len(ims),[(x.name,len(x.data)) for x in ims]); for j,x in enumerate(ims,1): open(f'{d}/p{n:02d}_{j}.{x.name.split(".")[-1]}','wb').write(x.data)"
python -c "from pypdf import PdfReader; import os; p='/tmp/workspace/attachments/b7b680e7-8d68-4c76-8cde-a9928d1593da/BIOCHEM CLINICAL LONGS .pdf'; d='/tmp/workspace/biochem-clinical-longs/output/rendered'; os.makedirs(d,exist_ok=True); r=PdfReader(p); print('pages',len(r.pages)); for n,page in enumerate(r.pages,1): ims=list(page.images); print(n,len(ims),[(x.name,len(x.data)) for x in ims]); for j,x in enumerate(ims,1): open(os.path.join(d,'p%02d_%d_%s'%(n,j,x.name.replace('/','_'))),'wb').write(x.data)"
python -c "from PIL import Image; import os,glob; src='/tmp/workspace/biochem-clinical-longs/output/rendered'; dst='/tmp/workspace/biochem-clinical-longs/output/downsized'; os.makedirs(dst,exist_ok=True); files=glob.glob(src+'/*.jpg'); for f in files: im=Image.open(f); im.thumbnail((1200,1600)); im.convert('RGB').save(os.path.join(dst,os.path.basename(f)),quality=60,optimize=True) print([(os.path.basename(f),os.path.getsize(f)) for f in glob.glob(dst+'/*')])"
python -c "import importlib.util as u; print('easyocr',bool(u.find_spec('easyocr')),'paddleocr',bool(u.find_spec('paddleocr')),'keras_ocr',bool(u.find_spec('keras_ocr')),'cv2',bool(u.find_spec('cv2')))"
which tesseract || true; python -c "from PIL import Image; im=Image.open('/tmp/workspace/biochem-clinical-longs/output/downsized/p01_1_img0.jpg'); print(im.size,im.mode)"