406cc7c0c7
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>
117 lines
2.9 KiB
Python
117 lines
2.9 KiB
Python
# /// script
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# requires-python = ">=3.10"
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# dependencies = ["numpy"]
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# ///
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"""
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@effect vignette
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@version 1.0.0
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@author artdag
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@description
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Vignette effect. Darkens the corners of the frame, drawing focus
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to the center. Classic cinematic look.
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@param strength float
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@range 0 1
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@default 0.5
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How dark the corners get (0 = none, 1 = black corners).
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@param radius float
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@range 0.5 2
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@default 1.0
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Size of the bright center area. Smaller = more vignette.
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@param softness float
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@range 0.1 1
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@default 0.5
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How gradual the falloff is.
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@param center_x float
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@range 0 1
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@default 0.5
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Center X position.
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@param center_y float
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@range 0 1
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@default 0.5
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Center Y position.
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@param color list
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@default [0, 0, 0]
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Vignette color (default black).
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@example
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(effect vignette :strength 0.6)
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@example
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;; Off-center vignette
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(effect vignette :center_x 0.3 :center_y 0.3 :strength 0.7)
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"""
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import numpy as np
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def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
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"""
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Apply vignette effect to a video frame.
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Args:
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frame: Input frame as numpy array (H, W, 3) RGB uint8
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params: Effect parameters
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- strength: darkness 0-1 (default 0.5)
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- radius: center size 0.5-2 (default 1.0)
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- softness: falloff gradient (default 0.5)
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- center_x: center X 0-1 (default 0.5)
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- center_y: center Y 0-1 (default 0.5)
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- color: RGB tuple (default [0,0,0])
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state: Persistent state dict
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Returns:
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Tuple of (processed_frame, new_state)
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"""
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strength = np.clip(params.get("strength", 0.5), 0, 1)
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radius = max(0.5, min(params.get("radius", 1.0), 2))
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softness = max(0.1, min(params.get("softness", 0.5), 1))
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center_x = params.get("center_x", 0.5)
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center_y = params.get("center_y", 0.5)
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color = params.get("color", [0, 0, 0])
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if state is None:
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state = {}
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if strength <= 0:
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return frame, state
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h, w = frame.shape[:2]
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# Calculate center in pixels
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cx = w * center_x
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cy = h * center_y
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# Create distance map from center
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y_coords, x_coords = np.ogrid[:h, :w]
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dist = np.sqrt((x_coords - cx)**2 + (y_coords - cy)**2)
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# Normalize distance
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max_dist = np.sqrt(cx**2 + cy**2) * radius
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# Create vignette mask
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normalized_dist = dist / max_dist
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# Apply softness to the falloff
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vignette_mask = 1 - np.clip((normalized_dist - (1 - softness)) / softness, 0, 1) * strength
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# Apply vignette
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if isinstance(color, (list, tuple)) and len(color) >= 3:
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vignette_color = np.array(color[:3], dtype=np.float32)
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else:
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vignette_color = np.array([0, 0, 0], dtype=np.float32)
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result = frame.astype(np.float32)
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# Blend toward vignette color based on mask
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for c in range(3):
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result[:, :, c] = result[:, :, c] * vignette_mask + vignette_color[c] * (1 - vignette_mask)
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return np.clip(result, 0, 255).astype(np.uint8), state
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