# /// script
# requires-python = ">=3.10"
# dependencies = ["numpy", "opencv-python"]
# ///
"""
@effect blur
@version 1.0.0
@author artdag

@description
Gaussian blur effect. Softens the image by averaging neighboring pixels.
Useful for dreamy effects or reducing detail on quiet parts.

@param radius float
  @range 0 50
  @default 5
  Blur radius in pixels. Higher = more blur. Must be positive.

@example
  (effect blur :radius 10)

@example
  ;; Blur on quiet, sharp on loud
  (effect blur :radius (bind energy :range [20 0]))
"""

import numpy as np
import cv2


def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
    """
    Apply Gaussian blur to a video frame.

    Args:
        frame: Input frame as numpy array (H, W, 3) RGB uint8
        params: Effect parameters
            - radius: blur radius in pixels (default 5)
        state: Persistent state dict (unused)

    Returns:
        Tuple of (processed_frame, new_state)
    """
    radius = params.get("radius", 5)

    if radius <= 0:
        return frame, state

    # Kernel size must be odd
    ksize = int(radius) * 2 + 1

    result = cv2.GaussianBlur(frame, (ksize, ksize), 0)

    return result, state