import cv2
import numpy as np
import gradio as gr
import requests
import re
from paddleocr import PaddleOCR

# Initialize PaddleOCR with angle classification enabled
ocr = PaddleOCR(use_angle_cls=True, lang='en')  # Use 'en|hi' or 'en|ta' if regional scripts are needed

def extract_plate_text_all(raw_texts):
    combined_text = ' '.join(raw_texts).upper()
    cleaned = re.sub(r'[^A-Z0-9 ]', '', combined_text)  # Keep spaces
    pattern = r'[A-Z]{2}\s*\d{1,2}\s*[A-Z]{0,3}\s*\d{3,4}'
    match = re.search(pattern, cleaned.replace(' ', ''))
    if match:
        return match.group(0)
    else:
        return "No valid license plate detected"

def detect_plate(image):
    if image is None:
        return "No image uploaded", None

    img_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
    results = ocr.predict(img_rgb)  # Remove `cls=True` here

    if not results or not isinstance(results[0], list) or len(results[0]) == 0:
        return "License plate not detected", image

    # Extract all detected texts
    texts = [line[1][0] for line in results[0]]
    plate_number = extract_plate_text_all(texts)

    if len(plate_number) < 6:  # Some threshold to check validity
        return "License plate not detected or low confidence", image

    # Find box corresponding to plate number (optional: draw box around all detected boxes)
    for line in results[0]:
        if isinstance(line[0], list) and all(isinstance(coord, (int, float)) for coord in line[0]):
            box = np.array(line[0]).astype(int)  # Convert the coordinates to integers
            cv2.polylines(image, [box], isClosed=True, color=(0, 255, 0), thickness=2)
        else:
            continue

    # Put plate number text
    cv2.putText(image, plate_number, (10, 30),
                cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)

    # Send to backend
    url = "https://abyssinian-heartbreaking-tuck.glitch.me/adds"
    try:
        response = requests.post(url, data={'lno': plate_number})
        if response.status_code == 200:
            print("POST request successful")
        else:
            print(f"Request failed with status code {response.status_code}")
    except Exception as e:
        print(f"POST request failed: {e}")

    return f"Number plate number is: {plate_number}", image

# Gradio Interface
demo = gr.Interface(
    fn=detect_plate,
    inputs=gr.Image(type="numpy"),
    outputs=["text", "image"],
    title="License Plate Detector (PaddleOCR + Indian Format)"
)

if __name__ == "__main__":
    demo.launch()