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

@description
Sharpening effect using unsharp mask technique. Enhances edges and detail.
Great for making footage pop on beats.

@param amount float
  @range 0 5
  @default 1.0
  Sharpening intensity. 0 = no change, 1 = normal, 2+ = aggressive.

@param radius float
  @range 0 10
  @default 1
  Radius of sharpening (affects edge thickness).

@example
  (effect sharpen :amount 1.5)

@example
  ;; Sharpen on beats
  (effect sharpen :amount (bind bass :range [0.5 2.0]))
"""

import numpy as np
import cv2


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

    Args:
        frame: Input frame as numpy array (H, W, 3) RGB uint8
        params: Effect parameters
            - amount: sharpening intensity (default 1.0)
            - radius: edge radius (default 1)
        state: Persistent state dict (unused)

    Returns:
        Tuple of (processed_frame, new_state)
    """
    amount = params.get("amount", 1.0)
    radius = params.get("radius", 1)

    if amount <= 0:
        return frame, state

    # Create blurred version
    ksize = max(1, int(radius)) * 2 + 1
    blurred = cv2.GaussianBlur(frame, (ksize, ksize), 0)

    # Unsharp mask: original + amount * (original - blurred)
    result = frame.astype(np.float32) + amount * (frame.astype(np.float32) - blurred.astype(np.float32))

    return np.clip(result, 0, 255).astype(np.uint8), state