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import easyocr
import re
import cv2
import numpy as np
from PIL import Image
# Initialize EasyOCR reader (only once)
reader = easyocr.Reader(['en'], gpu=False)
def preprocess_image(image):
# Convert to grayscale
gray = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
# Apply thresholding (adaptive works well for 7-seg)
thresh = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_MEAN_C,
cv2.THRESH_BINARY_INV, 15, 10)
# Dilation to strengthen numbers
kernel = np.ones((2, 2), np.uint8)
dilated = cv2.dilate(thresh, kernel, iterations=1)
return dilated
def extract_weight_from_image(pil_image):
try:
# Convert PIL to OpenCV
image = np.array(pil_image.convert("RGB"))
processed = preprocess_image(image)
# OCR
result = reader.readtext(processed)
# Filter and extract digits like weight (e.g., 75.5)
weight = None
confidence = 0.0
for detection in result:
text = detection[1]
conf = detection[2]
match = re.search(r"\d{2,4}(\.\d{1,2})?", text) # match 2-4 digit decimal
if match:
weight = match.group()
confidence = conf
break
if weight:
return weight, round(confidence * 100, 2)
else:
return "No weight detected", 0.0
except Exception as e:
return f"Error: {str(e)}", 0.0
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