import easyocr
import numpy as np
import cv2
import re

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

def enhance_image(img):
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

    # CLAHE (adaptive histogram equalization for better contrast)
    clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8, 8))
    contrast = clahe.apply(gray)

    # Sharpen image
    kernel = np.array([[0, -1, 0], [-1, 5, -1], [0, -1, 0]])
    sharpened = cv2.filter2D(contrast, -1, kernel)

    # Resize if very small
    h, w = sharpened.shape
    if max(h, w) < 500:
        sharpened = cv2.resize(sharpened, None, fx=2, fy=2, interpolation=cv2.INTER_CUBIC)

    return sharpened

def extract_weight_from_image(pil_img):
    try:
        img = np.array(pil_img)
        img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)  # convert from PIL to OpenCV BGR

        # Preprocess image
        processed = enhance_image(img)

        results = reader.readtext(processed)

        best_weight = None
        best_conf = 0.0

        for (bbox, text, conf) in results:
            original_text = text
            text = text.lower().strip()

            # Fix common OCR errors
            text = text.replace(",", ".")
            text = text.replace("o", "0").replace("O", "0")
            text = text.replace("s", "5").replace("S", "5")
            text = text.replace("g", "9").replace("G", "6")
            text = text.replace("kgs", "").replace("kg", "")
            text = re.sub(r"[^\d\.]", "", text)

            if re.fullmatch(r"\d{1,4}(\.\d{1,3})?", text):
                if conf > best_conf:
                    best_weight = text
                    best_conf = conf

        if not best_weight:
            return "Not detected", 0.0

        # Format output
        if "." in best_weight:
            int_part, dec_part = best_weight.split(".")
            int_part = int_part.lstrip("0") or "0"
            best_weight = f"{int_part}.{dec_part}"
        else:
            best_weight = best_weight.lstrip("0") or "0"

        return best_weight, round(best_conf * 100, 2)

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