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import pytesseract | |
import numpy as np | |
import cv2 | |
import re | |
def extract_weight_from_image(pil_img): | |
try: | |
img = np.array(pil_img) | |
# Preprocessing | |
gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY) | |
resized = cv2.resize(gray, None, fx=2, fy=2, interpolation=cv2.INTER_CUBIC) | |
blur = cv2.GaussianBlur(resized, (5, 5), 0) | |
_, thresh = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU) | |
# OCR using pytesseract | |
config = "--psm 6" # Assume a single uniform block of text | |
text = pytesseract.image_to_string(thresh, config=config) | |
print("OCR Output:", text) | |
# Regex to find weight-like numbers | |
match = re.search(r"\b\d{1,4}\.?\d{0,2}\b", text) | |
if match: | |
return match.group(), 95.0 | |
else: | |
return "No weight detected", 0.0 | |
except Exception as e: | |
return f"Error: {str(e)}", 0.0 | |