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

@description
Pixelate effect. Reduces resolution to create blocky, retro pixel art
look. Great for 8-bit aesthetics.

@param block_size int
  @range 2 64
  @default 8
  Size of pixel blocks. Larger = more pixelated.

@param maintain_edges bool
  @default false
  Try to preserve edges while pixelating.

@example
  (effect pixelate :block_size 16)

@example
  ;; Beat-reactive pixelation
  (effect pixelate :block_size (bind bass :range [4 32]))
"""

import numpy as np
import cv2


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

    Args:
        frame: Input frame as numpy array (H, W, 3) RGB uint8
        params: Effect parameters
            - block_size: pixel block size (default 8)
            - maintain_edges: preserve edges (default False)
        state: Persistent state dict

    Returns:
        Tuple of (processed_frame, new_state)
    """
    block_size = max(2, min(int(params.get("block_size", 8)), 64))
    maintain_edges = params.get("maintain_edges", False)

    if state is None:
        state = {}

    h, w = frame.shape[:2]

    # Scale down then up to create pixelation
    small_h = max(1, h // block_size)
    small_w = max(1, w // block_size)

    small = cv2.resize(frame, (small_w, small_h), interpolation=cv2.INTER_AREA)
    result = cv2.resize(small, (w, h), interpolation=cv2.INTER_NEAREST)

    if maintain_edges:
        # Detect edges in original and overlay
        gray = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY)
        edges = cv2.Canny(gray, 50, 150)
        edges_dilated = cv2.dilate(edges, np.ones((2, 2), np.uint8))
        edge_mask = edges_dilated > 0
        result[edge_mask] = frame[edge_mask]

    return result, state