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>
140 lines
3.8 KiB
Python
140 lines
3.8 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 echo
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@version 1.0.0
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@author artdag
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@description
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Motion trail / echo effect. Blends current frame with previous frames
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to create ghosting/trailing effects. Great for fast movement scenes.
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Uses a frame buffer in state to store recent frames for blending.
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@param num_echoes int
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@range 1 20
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@default 4
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Number of trailing frames to blend.
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@param decay float
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@range 0 1
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@default 0.5
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Opacity ratio between successive echoes. 0.5 = each echo half as bright.
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@param blend_mode string
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@enum blend add screen maximum
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@default blend
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How to combine echoes:
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- blend: weighted average
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- add: sum (can overexpose)
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- screen: like add but resists overexposure
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- maximum: brightest pixel wins
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@state frame_buffer list
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Circular buffer of recent frames.
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@example
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(effect echo :num_echoes 6 :decay 0.6)
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@example
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;; More echoes on energy
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(effect echo :num_echoes (bind energy :range [2 10]))
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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 echo/motion trail 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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- num_echoes: number of trailing frames (default 4)
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- decay: opacity decay ratio (default 0.5)
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- blend_mode: blend/add/screen/maximum (default blend)
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state: Persistent state dict
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- frame_buffer: list of recent frames
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Returns:
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Tuple of (processed_frame, new_state)
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"""
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num_echoes = max(1, min(int(params.get("num_echoes", 4)), 20))
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decay = max(0, min(params.get("decay", 0.5), 1))
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blend_mode = params.get("blend_mode", "blend")
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if state is None:
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state = {}
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# Initialize frame buffer
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if "frame_buffer" not in state:
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state["frame_buffer"] = []
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buffer = state["frame_buffer"]
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# Add current frame to buffer
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buffer.append(frame.copy())
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# Limit buffer size
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max_buffer = num_echoes + 5
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while len(buffer) > max_buffer:
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buffer.pop(0)
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# Collect frames and intensities for blending
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frames = []
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intensities = []
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intensity = 1.0
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# Current frame first, then older frames
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for i in range(min(num_echoes + 1, len(buffer))):
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idx = len(buffer) - 1 - i
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if idx >= 0:
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frames.append(buffer[idx].astype(np.float32))
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intensities.append(intensity)
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intensity *= decay
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if not frames:
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return frame, state
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# Blend frames according to mode
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result = _blend_frames(frames, intensities, blend_mode)
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return np.clip(result, 0, 255).astype(np.uint8), state
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def _blend_frames(frames, intensities, blend_mode):
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"""Blend multiple frames according to blend mode."""
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if not frames:
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return frames[0]
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if blend_mode == "add":
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result = np.zeros_like(frames[0])
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for frame, intensity in zip(frames, intensities):
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result += frame * intensity
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return result
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elif blend_mode == "screen":
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result = np.zeros_like(frames[0])
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for frame, intensity in zip(frames, intensities):
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weighted = (frame / 255.0) * intensity
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result = 255 * (1 - (1 - result / 255.0) * (1 - weighted))
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return result
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elif blend_mode == "maximum":
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result = frames[0] * intensities[0]
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for frame, intensity in zip(frames[1:], intensities[1:]):
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result = np.maximum(result, frame * intensity)
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return result
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else: # blend - weighted average
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total = sum(intensities)
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if total == 0:
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return frames[0]
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result = np.zeros_like(frames[0])
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for frame, intensity in zip(frames, intensities):
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result += frame * (intensity / total)
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return result
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