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>
64 lines
1.5 KiB
Python
64 lines
1.5 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 sharpen
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@version 1.0.0
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@author artdag
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@description
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Sharpening effect using unsharp mask technique. Enhances edges and detail.
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Great for making footage pop on beats.
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@param amount float
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@range 0 5
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@default 1.0
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Sharpening intensity. 0 = no change, 1 = normal, 2+ = aggressive.
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@param radius float
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@range 0 10
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@default 1
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Radius of sharpening (affects edge thickness).
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@example
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(effect sharpen :amount 1.5)
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@example
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;; Sharpen on beats
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(effect sharpen :amount (bind bass :range [0.5 2.0]))
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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 sharpening 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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- amount: sharpening intensity (default 1.0)
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- radius: edge radius (default 1)
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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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amount = params.get("amount", 1.0)
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radius = params.get("radius", 1)
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if amount <= 0:
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return frame, state
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# Create blurred version
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ksize = max(1, int(radius)) * 2 + 1
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blurred = cv2.GaussianBlur(frame, (ksize, ksize), 0)
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# Unsharp mask: original + amount * (original - blurred)
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result = frame.astype(np.float32) + amount * (frame.astype(np.float32) - blurred.astype(np.float32))
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return np.clip(result, 0, 255).astype(np.uint8), state
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