handyhome-ocr-api / extract_sss.py
takomattyy's picture
updating ocr scripts for IDs
4d48737 verified
import sys, json, os, glob, re, requests
from PIL import Image
from io import BytesIO
from datetime import datetime
from contextlib import redirect_stdout, redirect_stderr
# Immediately redirect all output to stderr except for our final JSON
original_stdout = sys.stdout
sys.stdout = sys.stderr
# Suppress all PaddleOCR output
os.environ['PADDLEOCR_LOG_LEVEL'] = 'ERROR'
os.environ['QT_QPA_PLATFORM'] = 'offscreen'
os.environ['DISPLAY'] = ':99'
# Import PaddleOCR after setting environment variables
from paddleocr import PaddleOCR
def dprint(msg, obj=None):
try:
print(f"DEBUG: {msg}" + (f": {obj}" if obj is not None else ""), file=sys.stderr)
except Exception:
pass
def clean_cache():
files = ['temp_image.jpg', 'temp_image_ocr_res_img.jpg', 'temp_image_preprocessed_img.jpg', 'temp_image_res.json']
for f in files:
if os.path.exists(f):
os.remove(f)
dprint("Removed cache file", f)
if os.path.exists("output"):
import shutil
shutil.rmtree("output")
dprint("Removed output directory")
def download_image(url, output_path='temp_image.jpg'):
dprint("Starting download", url)
clean_cache()
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36'
}
r = requests.get(url, headers=headers, timeout=30)
dprint("HTTP status", r.status_code)
r.raise_for_status()
img = Image.open(BytesIO(r.content))
if img.mode == 'RGBA':
bg = Image.new('RGB', img.size, (255, 255, 255))
bg.paste(img, mask=img.split()[-1])
img = bg
elif img.mode != 'RGB':
img = img.convert('RGB')
img.save(output_path, 'JPEG', quality=95)
dprint("Saved image", output_path)
return output_path
def cap_words(s):
return None if not s else ' '.join(w.capitalize() for w in s.split())
def normalize_full_name(s):
if not s:
return None
raw = ' '.join(s.split())
if ',' in raw:
parts = [p.strip() for p in raw.split(',')]
last = parts[0] if parts else ''
given_block = ','.join(parts[1:]).strip() if len(parts) > 1 else ''
tokens = [t for t in given_block.split(' ') if t]
first = tokens[0] if tokens else ''
second = tokens[1] if len(tokens) > 1 else ''
if second:
return f"{first} {second} {last}".strip()
else:
return f"{first} {last}".strip()
else:
tokens = [t for t in raw.split(' ') if t]
if len(tokens) >= 3:
return f"{tokens[0]} {tokens[1]} {tokens[-1]}".strip()
elif len(tokens) == 2:
return f"{tokens[0]} {tokens[1]}".strip()
else:
return raw
def extract_sss_number(text):
sss_pattern = r'\b(\d{2}-\d{7}-\d{1})\b'
match = re.search(sss_pattern, text)
if match:
return match.group(1)
return None
def extract_sss_info(lines):
dprint("Lines to extract", lines)
full_name = None
sss_number = None
sss_id_number = None
name_parts = []
L = [str(x or '').strip() for x in lines]
i = 0
while i < len(L):
line = L[i]
low = line.lower()
dprint("Line", {"i": i, "text": line})
# Look for SSS number pattern (XX-XXXXXXX-X)
if not sss_number:
sss_num = extract_sss_number(line)
if sss_num:
sss_number = sss_num
sss_id_number = sss_num
dprint("Found SSS number", sss_number)
# Collect potential name parts (single words that look like names)
if re.search(r'^[A-Z]{2,}$', line) and not re.search(r'[0-9]', line):
skip_words = ['REPUBLIC', 'PHILIPPINES', 'SOCIAL', 'SECURITY', 'SYSTEM', 'SSS', 'PRESIDENT', 'PROUD', 'FILIPINO', 'CORAZON']
if not any(word in line.upper() for word in skip_words):
name_parts.append(line)
dprint("Added name part", line)
# Look for multi-word names but don't set full_name yet
if len(line.split()) >= 2 and re.search(r'[A-Z]{2,}', line) and not re.search(r'[0-9]{3,}', line):
skip_words = ['REPUBLIC', 'PHILIPPINES', 'SOCIAL', 'SECURITY', 'SYSTEM', 'SSS', 'PRESIDENT', 'PROUD', 'FILIPINO']
if not any(word in line.upper() for word in skip_words):
# Add multi-word names to name_parts instead of setting full_name directly
name_parts.append(line)
dprint("Added multi-word name part", line)
i += 1
# Now compose the full name from all collected parts
if name_parts:
# Combine all name parts
combined_name = ' '.join(name_parts)
full_name = normalize_full_name(combined_name)
dprint("Composed name from all parts", {"parts": name_parts, "result": full_name})
result = {
"id_type": "SSS ID",
"sss_number": sss_number,
"id_number": sss_id_number,
"full_name": full_name,
"birth_date": None,
"address": None,
"sex": None,
"nationality": "Filipino"
}
dprint("Final result", result)
return result
def extract_ocr_lines(image_path):
os.makedirs("output", exist_ok=True)
dprint("Initializing PaddleOCR")
with redirect_stdout(sys.stderr), redirect_stderr(sys.stderr):
ocr = PaddleOCR(
use_doc_orientation_classify=False,
use_doc_unwarping=False,
use_textline_orientation=False,
lang='en'
)
dprint("OCR initialized")
dprint("Running OCR predict", image_path)
try:
results = ocr.predict(image_path)
except Exception as e:
dprint("predict() failed, trying ocr()", str(e))
if hasattr(ocr, 'ocr'):
results = ocr.ocr(image_path)
else:
results = None
try:
count = len(results[0]) if results and isinstance(results, list) and len(results) > 0 and isinstance(results[0], list) else (len(results) if results else 0)
except Exception:
count = 0
dprint("OCR done, results_count", count)
# Process OCR results - handle both old format (list) and new format (OCRResult object)
all_text = []
try:
# Handle both old format (list) and new format (OCRResult object)
if results and isinstance(results, list) and len(results) > 0:
first_item = results[0]
item_type_name = type(first_item).__name__
is_ocr_result = 'OCRResult' in item_type_name or 'ocr_result' in str(type(first_item)).lower()
if is_ocr_result:
dprint("Detected OCRResult object format", f"type: {item_type_name}")
# Access OCRResult as dictionary
try:
if hasattr(first_item, 'keys'):
ocr_dict = dict(first_item)
# Look for rec_texts key
if 'rec_texts' in ocr_dict:
rec_texts = ocr_dict['rec_texts']
if isinstance(rec_texts, list):
all_text = [str(t) for t in rec_texts if t]
dprint("Extracted text lines from rec_texts", len(all_text))
except Exception as e:
dprint("Error accessing OCRResult", str(e))
else:
# Old format - list of lists
lines = results[0] if results and isinstance(results[0], list) else results
for item in lines:
if isinstance(item, (list, tuple)) and len(item) >= 2:
meta = item[1]
if isinstance(meta, (list, tuple)) and len(meta) >= 1:
all_text.append(str(meta[0]))
except Exception as e:
dprint("Error processing OCR results", str(e))
import traceback
dprint("Traceback", traceback.format_exc())
dprint("All direct texts", all_text)
return extract_sss_info(all_text) if all_text else {
"id_type": "SSS ID",
"sss_number": None,
"id_number": None,
"full_name": None,
"birth_date": None
}
if len(sys.argv) < 2:
sys.stdout = original_stdout
print(json.dumps({"error": "No image URL provided"}))
sys.exit(1)
image_url = sys.argv[1]
dprint("Processing image URL", image_url)
try:
image_path = download_image(image_url)
dprint("Image downloaded to", image_path)
ocr_results = extract_ocr_lines(image_path)
dprint("OCR results ready")
# Restore stdout and print only the JSON response
sys.stdout = original_stdout
sys.stdout.write(json.dumps({"success": True, "ocr_results": ocr_results}))
sys.stdout.flush()
except Exception as e:
dprint("Exception", str(e))
# Restore stdout for error JSON
sys.stdout = original_stdout
sys.stdout.write(json.dumps({"error": str(e)}))
sys.stdout.flush()
sys.exit(1)
finally:
# Clean up
try:
clean_cache()
except:
pass