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import pytesseract
import numpy as np
import cv2
import re
import logging
from PIL import Image
# Setup logging
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
def preprocess_strong(img):
"""Sharpen and enhance contrast for blurry weight images."""
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# Resize up for OCR (scale x2)
h, w = gray.shape
gray = cv2.resize(gray, (w * 2, h * 2), interpolation=cv2.INTER_CUBIC)
# CLAHE for contrast enhancement
clahe = cv2.createCLAHE(clipLimit=3.0, tileGridSize=(8, 8))
enhanced = clahe.apply(gray)
# Strong sharpening
kernel = np.array([[0, -1, 0],
[-1, 5, -1],
[0, -1, 0]])
sharpened = cv2.filter2D(enhanced, -1, kernel)
return sharpened
def extract_weight_from_image(pil_img):
"""Extract weight from an image using multiple Tesseract strategies."""
try:
img = np.array(pil_img)
img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
processed = preprocess_strong(img)
# OCR configs
configs = [
r'--oem 3 --psm 6 -c tessedit_char_whitelist=0123456789.',
r'--oem 3 --psm 11 -c tessedit_char_whitelist=0123456789.'
]
for config in configs:
raw_text = pytesseract.image_to_string(processed, config=config)
logging.info(f"[Tesseract Output {config}] Raw text: {raw_text}")
cleaned = raw_text.strip().replace('\n', '').replace(' ', '')
cleaned = re.sub(r"[^\d.]", "", cleaned)
if cleaned.count('.') > 1:
cleaned = cleaned.replace('.', '', cleaned.count('.') - 1)
if cleaned.startswith('.'):
cleaned = '0' + cleaned
if cleaned and re.fullmatch(r"\d*\.?\d*", cleaned):
value = float(cleaned)
if 0.001 <= value <= 5000:
return str(round(value, 2)), 90.0
return "Not detected", 0.0
except Exception as e:
logging.error(f"OCR failed: {e}")
return "Not detected", 0.0
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