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>
89 lines
2.4 KiB
Python
89 lines
2.4 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 emboss
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@version 1.0.0
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@author artdag
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@description
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Emboss / relief effect. Creates a 3D raised appearance by highlighting
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edges from a simulated light direction. Great for sculptural looks.
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@param strength float
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@range 0.5 3
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@default 1.0
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Emboss intensity.
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@param direction float
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@range 0 360
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@default 135
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Light direction in degrees. Bind to beat for rotating light.
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@param blend float
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@range 0 1
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@default 0.3
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Blend with original (0 = full emboss, 1 = original).
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@example
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(effect emboss :strength 1.5)
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@example
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;; Rotating light direction
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(effect emboss :direction (bind beat_position :range [0 360]))
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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 emboss 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: emboss intensity (default 1.0)
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- direction: light angle in degrees (default 135)
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- blend: mix with original (default 0.3)
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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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strength = params.get("strength", 1.0)
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direction = params.get("direction", 135)
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blend = params.get("blend", 0.3)
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# Calculate kernel based on direction
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angle_rad = np.deg2rad(direction)
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dx = np.cos(angle_rad)
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dy = np.sin(angle_rad)
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# Create emboss kernel
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kernel = np.array([
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[-strength * dy - strength * dx, -strength * dy, -strength * dy + strength * dx],
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[-strength * dx, 1, strength * dx],
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[strength * dy - strength * dx, strength * dy, strength * dy + strength * dx]
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], dtype=np.float32)
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# Apply to grayscale
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gray = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY).astype(np.float32)
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embossed = cv2.filter2D(gray, -1, kernel)
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# Normalize
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embossed = embossed + 128
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embossed = np.clip(embossed, 0, 255)
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# Convert to RGB
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embossed_rgb = cv2.cvtColor(embossed.astype(np.uint8), cv2.COLOR_GRAY2RGB)
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# Blend with original
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if blend > 0:
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result = frame.astype(np.float32) * blend + embossed_rgb.astype(np.float32) * (1 - blend)
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return np.clip(result, 0, 255).astype(np.uint8), state
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return embossed_rgb, state
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