import gradio as gr
import numpy as np
from PIL import Image
import cv2
import re
from paddleocr import PaddleOCR
from datetime import datetime

# Load OCR model
ocr = PaddleOCR(use_angle_cls=True, lang='en')

def preprocess_image(image):
    img = np.array(image.convert("RGB"))
    gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
    _, thresh = cv2.threshold(gray, 150, 255, cv2.THRESH_BINARY)
    return Image.fromarray(thresh)

def extract_weight_text(image):
    try:
        results = ocr.ocr(np.array(image), cls=True)
        texts = []
        for line in results[0]:
            text = line[1][0]
            texts.append(text)
            match = re.search(r"\d+\.\d+", text)
            if match:
                return match.group(), texts
        return None, texts
    except Exception as e:
        return f"Error: {str(e)}", []

def detect_weight(image):
    if image is None:
        return "No image uploaded.", "", None, ""
    pre_img = preprocess_image(image)
    weight, texts = extract_weight_text(pre_img)
    if weight and "Error" not in weight:
        return f"Detected Weight: {weight} kg", datetime.now().strftime("Captured At: %Y-%m-%d %H:%M:%S"), pre_img, "\n".join(texts)
    else:
        return "Weight Not Detected", "", pre_img, "\n".join(texts)

gr.Interface(
    fn=detect_weight,
    inputs=gr.Image(type="pil", label="Upload or Capture Image"),
    outputs=[
        gr.Textbox(label="Weight"),
        gr.Textbox(label="Timestamp"),
        gr.Image(label="Preprocessed Image"),
        gr.Textbox(label="Detected Text (Debug)")
    ],
    title="Auto Weight Logger (Debug Mode)",
    description="Upload a clear image of a digital scale. This version shows detected text for debugging."
).launch()