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>
55 lines
1.2 KiB
Python
55 lines
1.2 KiB
Python
# /// script
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# requires-python = ">=3.10"
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# dependencies = ["numpy", "opencv-python"]
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# ///
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"""
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@effect blur
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@version 1.0.0
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@author artdag
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@description
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Gaussian blur effect. Softens the image by averaging neighboring pixels.
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Useful for dreamy effects or reducing detail on quiet parts.
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@param radius float
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@range 0 50
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@default 5
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Blur radius in pixels. Higher = more blur. Must be positive.
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@example
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(effect blur :radius 10)
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@example
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;; Blur on quiet, sharp on loud
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(effect blur :radius (bind energy :range [20 0]))
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"""
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import numpy as np
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import cv2
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def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
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"""
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Apply Gaussian blur 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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- radius: blur radius in pixels (default 5)
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state: Persistent state dict (unused)
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Returns:
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Tuple of (processed_frame, new_state)
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"""
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radius = params.get("radius", 5)
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if radius <= 0:
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return frame, state
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# Kernel size must be odd
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ksize = int(radius) * 2 + 1
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result = cv2.GaussianBlur(frame, (ksize, ksize), 0)
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return result, state
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