Initial commit: video effects processing system

Add S-expression based video effects pipeline with modular effect
definitions, constructs, and recipe files.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

effects/fisheye.py

@@ -0,0 +1,116 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy", "opencv-python"]
+# ///
+"""
+@effect fisheye
+@version 1.0.0
+@author artdag
+
+@description
+Barrel/fisheye lens distortion. Positive values bulge outward (fisheye),
+negative values pinch inward (pincushion). Great for emphasis effects.
+
+@param strength float
+  @range -1 1
+  @default 0.3
+  Distortion strength. Positive = fisheye bulge, negative = pincushion pinch.
+
+@param center_x float
+  @range 0 1
+  @default 0.5
+  Horizontal center of distortion (0 = left, 1 = right).
+
+@param center_y float
+  @range 0 1
+  @default 0.5
+  Vertical center of distortion (0 = top, 1 = bottom).
+
+@param zoom_correction bool
+  @default true
+  Automatically zoom to hide black edges on fisheye.
+
+@example
+  (effect fisheye :strength 0.5)
+
+@example
+  ;; Pulse fisheye on bass
+  (effect fisheye :strength (bind bass :range [0 0.8] :transform sqrt))
+
+@example
+  ;; Pincushion effect
+  (effect fisheye :strength -0.3)
+"""
+
+import numpy as np
+import cv2
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply fisheye/barrel distortion to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - strength: distortion strength -1 to 1 (default 0.3)
+            - center_x: horizontal center 0-1 (default 0.5)
+            - center_y: vertical center 0-1 (default 0.5)
+            - zoom_correction: auto-zoom for fisheye (default True)
+        state: Persistent state dict (unused)
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    strength = params.get("strength", 0.3)
+    center_x = params.get("center_x", 0.5)
+    center_y = params.get("center_y", 0.5)
+    zoom_correction = params.get("zoom_correction", True)
+
+    if strength == 0:
+        return frame, state
+
+    h, w = frame.shape[:2]
+
+    # Calculate center in pixels
+    cx = w * center_x
+    cy = h * center_y
+
+    # Create coordinate grids
+    y_coords, x_coords = np.mgrid[0:h, 0:w].astype(np.float32)
+
+    # Normalize coordinates relative to center
+    x_norm = (x_coords - cx) / (w / 2)
+    y_norm = (y_coords - cy) / (h / 2)
+
+    # Calculate radius from center
+    r = np.sqrt(x_norm**2 + y_norm**2)
+
+    # Apply barrel/pincushion distortion
+    if strength > 0:
+        # Barrel distortion (fisheye)
+        r_distorted = r * (1 + strength * r**2)
+    else:
+        # Pincushion distortion
+        r_distorted = r / (1 - strength * r**2 + 0.001)
+
+    # Calculate scale factor
+    scale = np.where(r > 0, r_distorted / r, 1)
+
+    # Apply zoom correction to hide black edges
+    if zoom_correction and strength > 0:
+        zoom = 1 + strength * 0.5
+        scale = scale / zoom
+
+    # Calculate new coordinates
+    new_x = (x_norm * scale * (w / 2) + cx).astype(np.float32)
+    new_y = (y_norm * scale * (h / 2) + cy).astype(np.float32)
+
+    # Remap
+    result = cv2.remap(
+        frame, new_x, new_y,
+        cv2.INTER_LINEAR,
+        borderMode=cv2.BORDER_REFLECT
+    )
+
+    return result, state