ocr_engine.py

import easyocr
import numpy as np
import cv2
import re

# Initialize OCR reader once
reader = easyocr.Reader(['en'], gpu=False)

def extract_weight_from_image(pil_img):
    try:
        img = np.array(pil_img)

        # Convert to grayscale
        gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)

        # Resize for better accuracy
        gray = cv2.resize(gray, None, fx=2, fy=2, interpolation=cv2.INTER_LINEAR)

        # Gaussian blur to reduce noise
        blurred = cv2.GaussianBlur(gray, (3, 3), 0)

        # Invert colors: useful for LCD display images
        inverted = cv2.bitwise_not(blurred)

        # Normalize brightness
        norm_img = cv2.normalize(inverted, None, 0, 255, cv2.NORM_MINMAX)

        # Perform OCR
        result = reader.readtext(norm_img, detail=0)
        combined_text = " ".join(result)
        print("OCR Text:", combined_text)

        # Regex to detect numbers (e.g. 25, 75.45, 100.00)
        match = re.search(r"\b\d{1,4}(\.\d{1,2})?\b", combined_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