from PIL import Image, ImageDraw, ImageFont, ImageFilter
import cv2
import numpy as np

def apply_watermark(image_cv: np.ndarray) -> np.ndarray:
    """
    Applies the 'AuraLens' professional text watermark to the bottom-center 
    of the image using a clean minimalist typography style.
    """
    # Convert OpenCV image (BGR) to PIL Image (RGB)
    img_pil = Image.fromarray(cv2.cvtColor(image_cv, cv2.COLOR_BGR2RGB))
    
    # Create a transparent overlay for the watermark
    overlay = Image.new('RGBA', img_pil.size, (255, 255, 255, 0))
    draw = ImageDraw.Draw(overlay)
    
    width, height = img_pil.size
    
    # Scale font size based on image height
    font_size = max(int(height * 0.03), 16)
    
    # Try to use a good default font, fallback to default if not available
    try:
        font = ImageFont.truetype("arial.ttf", font_size)
    except IOError:
        font = ImageFont.load_default()
        # default font is very small, we manually scale the text layer if needed
        # but for safety we'll just use what we get
    
    text = "A U R A L E N S"
    
    # Get text bounding box to calculate position
    if hasattr(font, 'getbbox'):
        bbox = font.getbbox(text)
        text_width = bbox[2] - bbox[0]
        text_height = bbox[3] - bbox[1]
    else:
        # Fallback for older Pillow versions
        text_width, text_height = draw.textsize(text, font=font)
    
    x = (width - text_width) // 2
    # Place it at the bottom with some padding (5% of height)
    y = height - text_height - int(height * 0.05)
    
    # Draw drop shadow (slightly offset, black with low opacity)
    shadow_offset = max(2, int(font_size * 0.05))
    draw.text((x + shadow_offset, y + shadow_offset), text, font=font, fill=(0, 0, 0, 150))
    
    # Draw the main white text
    draw.text((x, y), text, font=font, fill=(255, 255, 255, 230))
    
    # Composite the overlay onto the original image
    watermarked_pil = Image.alpha_composite(img_pil.convert('RGBA'), overlay)
    
    # Convert back to OpenCV BGR
    watermarked_cv = cv2.cvtColor(np.array(watermarked_pil), cv2.COLOR_RGBA2BGR)
    
    return watermarked_cv