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>
87 lines
2.2 KiB
Python
87 lines
2.2 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 mirror
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@version 1.0.0
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@author artdag
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@description
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Creates mirror/reflection effects by duplicating and flipping portions
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of the frame. Can create kaleidoscope-like symmetry effects.
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@param mode string
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@enum left right top bottom quad
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@default left
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Mirror mode:
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- left: Left half mirrored to right
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- right: Right half mirrored to left
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- top: Top half mirrored to bottom
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- bottom: Bottom half mirrored to top
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- quad: Four-way symmetry (kaleidoscope)
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@example
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(effect mirror :mode "left")
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@example
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(effect mirror :mode "quad") ; kaleidoscope effect
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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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Create mirror/reflection effects.
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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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- mode: mirror mode (default "left")
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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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mode = params.get("mode", "left")
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h, w = frame.shape[:2]
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result = frame.copy()
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if mode == "left":
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# Mirror left half to right
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half = w // 2
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result[:, half:] = np.flip(result[:, :half], axis=1)[:, :w - half]
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elif mode == "right":
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# Mirror right half to left
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half = w // 2
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result[:, :half] = np.flip(result[:, half:], axis=1)[:, :half]
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elif mode == "top":
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# Mirror top half to bottom
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half = h // 2
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result[half:, :] = np.flip(result[:half, :], axis=0)[:h - half, :]
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elif mode == "bottom":
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# Mirror bottom half to top
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half = h // 2
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result[:half, :] = np.flip(result[half:, :], axis=0)[:half, :]
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elif mode == "quad":
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# Four-way symmetry: use top-left quadrant
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half_h = h // 2
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half_w = w // 2
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# Get top-left quadrant
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tl = result[:half_h, :half_w]
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# Mirror to top-right
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result[:half_h, half_w:] = np.flip(tl, axis=1)[:, :w - half_w]
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# Mirror top half to bottom
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result[half_h:, :] = np.flip(result[:half_h, :], axis=0)[:h - half_h, :]
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return np.ascontiguousarray(result), state
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