import easyocr
import numpy as np
import cv2
import re

reader = easyocr.Reader(['en'], gpu=False)

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

        # Resize and grayscale
        img = cv2.resize(img, None, fx=3.5, fy=3.5, interpolation=cv2.INTER_LINEAR)
        gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)

        # Denoise and threshold
        gray = cv2.bilateralFilter(gray, 11, 17, 17)
        thresh = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C,
                                       cv2.THRESH_BINARY_INV, 11, 2)

        results = reader.readtext(thresh)
        all_texts = [text for _, text, _ in results]

        weight_candidates = []
        for _, text, conf in results:
            cleaned = text.lower()
            cleaned = cleaned.replace("kg", "").replace("kgs", "")
            cleaned = cleaned.replace("o", "0").replace("O", "0")
            cleaned = cleaned.replace("s", "5").replace("S", "5")
            cleaned = cleaned.replace("g", "9").replace("G", "6")
            cleaned = re.sub(r"[^\d\.]", "", cleaned)

            if re.fullmatch(r"\d{2,4}(\.\d{1,2})?", cleaned):
                weight_candidates.append((cleaned, conf))

        if not weight_candidates:
            return "Not detected", 0.0, "\n".join(all_texts)

        best_weight, best_conf = sorted(weight_candidates, key=lambda x: -x[1])[0]
        return best_weight, round(best_conf * 100, 2), "\n".join(all_texts)

    except Exception as e:
        return f"Error: {str(e)}", 0.0, "OCR failed"