Initial commit: video effects processing system

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>

effects/ascii_art.py

@@ -0,0 +1,205 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy", "opencv-python"]
+# ///
+"""
+@effect ascii_art
+@version 1.0.0
+@author artdag
+
+@description
+ASCII art effect - converts video to ASCII character representation.
+Renders the video using ASCII characters based on brightness,
+creating a retro terminal aesthetic.
+
+@param char_size int
+  @range 4 32
+  @default 8
+  Size of each character cell in pixels. Sync to bass for reactive sizing.
+
+@param alphabet string
+  @enum standard blocks cyrillic greek japanese braille
+  @default standard
+  Character set to use for rendering. Each has different visual density.
+
+@param color_mode string
+  @enum mono color invert
+  @default color
+  Color rendering mode:
+  - mono: white on black
+  - color: preserve source colors
+  - invert: dark text on colored background
+
+@param contrast_boost float
+  @range 1 3
+  @default 1.5
+  Enhance contrast for better character separation.
+
+@param background list
+  @default [0, 0, 0]
+  Background color RGB.
+
+@example
+  (effect ascii_art :char_size 8 :color_mode "color")
+
+@example
+  ;; Japanese characters, reactive sizing
+  (effect ascii_art :alphabet "japanese" :char_size (bind bass :range [6 16]))
+
+@example
+  ;; Braille pattern for high detail
+  (effect ascii_art :alphabet "braille" :char_size 4)
+"""
+
+import numpy as np
+import cv2
+
+
+# Character sets ordered by visual density (light to dark)
+ALPHABETS = {
+    # Classic ASCII gradient
+    "standard": " .`'^\",:;Il!i><~+_-?][}{1)(|/tfjrxnuvczXYUJCLQ0OZmwqpdbkhao*#MW&8%B@$",
+
+    # Unicode block elements - naturally ordered by fill
+    "blocks": " ░▒▓█",
+
+    # Cyrillic - ordered by visual complexity
+    "cyrillic": " ·гтпрсьоеаилнкчуцбдвжзмъыюяфщшэ",
+
+    # Greek - ordered by visual weight
+    "greek": " ·ιτορεαηυικλνσςπμβγδζθξφψωΣΩΨΦ",
+
+    # Japanese Katakana - ordered by stroke complexity
+    "japanese": " ·ノ一ヘイコニハヒフホメヨワヲンリルレロカキクケサシスセソタチツテト",
+
+    # Braille patterns - high detail
+    "braille": " ⠁⠂⠃⠄⠅⠆⠇⠈⠉⠊⠋⠌⠍⠎⠏⠐⠑⠒⠓⠔⠕⠖⠗⠘⠙⠚⠛⠜⠝⠞⠟⠠⠡⠢⠣⠤⠥⠦⠧⠨⠩⠪⠫⠬⠭⠮⠯⠰⠱⠲⠳⠴⠵⠶⠷⠸⠹⠺⠻⠼⠽⠾⠿",
+}
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply ASCII art effect to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - char_size: character cell size (default 8)
+            - alphabet: character set name (default "standard")
+            - color_mode: mono/color/invert (default "color")
+            - contrast_boost: enhance contrast (default 1.5)
+            - background: RGB tuple (default [0,0,0])
+        state: Persistent state dict (used for caching)
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    char_size = max(4, min(int(params.get("char_size", 8)), 32))
+    alphabet_name = params.get("alphabet", "standard")
+    color_mode = params.get("color_mode", "color")
+    contrast_boost = max(1.0, min(params.get("contrast_boost", 1.5), 3.0))
+    background = params.get("background", [0, 0, 0])
+
+    if state is None:
+        state = {}
+
+    # Get character set
+    char_set = ALPHABETS.get(alphabet_name, ALPHABETS["standard"])
+
+    # Get or create character atlas cache
+    cache_key = f"{char_size}_{alphabet_name}"
+    if "atlas_cache" not in state or state.get("cache_key") != cache_key:
+        state["atlas"] = _create_char_atlas(char_size, char_set)
+        state["cache_key"] = cache_key
+
+    atlas = state["atlas"]
+
+    h, w = frame.shape[:2]
+    cols = w // char_size
+    rows = h // char_size
+
+    if cols < 1 or rows < 1:
+        return frame, state
+
+    # Crop frame to fit grid
+    grid_h, grid_w = rows * char_size, cols * char_size
+    frame_cropped = frame[:grid_h, :grid_w]
+
+    # Downsample to get average color per cell
+    reshaped = frame_cropped.reshape(rows, char_size, cols, char_size, 3)
+    cell_colors = reshaped.mean(axis=(1, 3)).astype(np.uint8)
+
+    # Convert to grayscale for brightness mapping
+    cell_gray = 0.299 * cell_colors[:,:,0] + 0.587 * cell_colors[:,:,1] + 0.114 * cell_colors[:,:,2]
+
+    # Apply contrast boost
+    if contrast_boost > 1:
+        cell_gray = (cell_gray - 128) * contrast_boost + 128
+        cell_gray = np.clip(cell_gray, 0, 255)
+
+    # Map brightness to character indices
+    char_indices = ((cell_gray / 255) * (len(char_set) - 1)).astype(np.int32)
+    char_indices = np.clip(char_indices, 0, len(char_set) - 1)
+
+    # Create output frame
+    if isinstance(background, (list, tuple)) and len(background) >= 3:
+        bg = background[:3]
+    else:
+        bg = [0, 0, 0]
+    result = np.full((grid_h, grid_w, 3), bg, dtype=np.uint8)
+
+    # Render characters
+    for row in range(rows):
+        for col in range(cols):
+            char_idx = char_indices[row, col]
+            char = char_set[char_idx]
+            char_mask = atlas.get(char)
+
+            if char_mask is None:
+                continue
+
+            y1, x1 = row * char_size, col * char_size
+
+            if color_mode == "mono":
+                color = np.array([255, 255, 255], dtype=np.uint8)
+            elif color_mode == "invert":
+                # Colored background, dark text
+                result[y1:y1+char_size, x1:x1+char_size] = cell_colors[row, col]
+                color = np.array([0, 0, 0], dtype=np.uint8)
+            else:  # color
+                color = cell_colors[row, col]
+
+            # Apply character mask
+            if char != ' ':
+                mask = char_mask > 0
+                result[y1:y1+char_size, x1:x1+char_size][mask] = color
+
+    # Pad to original size if needed
+    if result.shape[0] < h or result.shape[1] < w:
+        padded = np.full((h, w, 3), bg, dtype=np.uint8)
+        padded[:grid_h, :grid_w] = result
+        result = padded
+
+    return result, state
+
+
+def _create_char_atlas(char_size: int, char_set: str) -> dict:
+    """Pre-render all characters as masks."""
+    font = cv2.FONT_HERSHEY_SIMPLEX
+    font_scale = char_size / 20.0
+    thickness = max(1, int(char_size / 10))
+
+    atlas = {}
+    for char in char_set:
+        char_img = np.zeros((char_size, char_size), dtype=np.uint8)
+        if char != ' ':
+            try:
+                (text_w, text_h), baseline = cv2.getTextSize(char, font, font_scale, thickness)
+                text_x = (char_size - text_w) // 2
+                text_y = (char_size + text_h) // 2
+                cv2.putText(char_img, char, (text_x, text_y), font, font_scale, 255, thickness, cv2.LINE_AA)
+            except:
+                pass
+        atlas[char] = char_img
+
+    return atlas

effects/ascii_art.sexp

@@ -0,0 +1,34 @@
+;; ASCII art effect - render as text characters (music reactive)
+;; Usage: python3 plan.py effects/ascii_art.sexp | python3 execute.py - -d . -o - | mpv --fs -
+;;
+;; Parameters:
+;;   color_mode: coloring mode ("color", "green", "white", default: "color")
+;;   char_size is bound to energy (wobbles with overall loudness)
+
+(recipe "ascii_art"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect ascii_art :path "sexp_effects/effects/ascii_art.sexp")
+  (analyzer energy :path "../artdag-analyzers/energy/analyzer.py")
+
+  ;; Default parameter
+  (def color_mode "color")
+
+  (def video (source :path "monday.webm"))
+  (def audio (source :path "dizzy.mp3"))
+
+  (def clip (-> video (segment :start 0 :duration 10)))
+  ;; Audio from 60s where it's louder
+  (def audio-clip (-> audio (segment :start 60 :duration 10)))
+
+  ;; Analyze just the audio clip - times are 0-10s relative to clip
+  (def energy-data (-> audio-clip (analyze energy)))
+
+  ;; char_size bound to energy - no offset needed since analysis is on clip
+  (def result (-> clip
+    (effect ascii_art
+      :char_size (bind energy-data values :range [2 32])
+      :color_mode color_mode)))
+
+  (mux result audio-clip))

effects/ascii_zones.sexp

@@ -0,0 +1,33 @@
+;; ASCII zones effect - region-based ASCII rendering
+;; Usage: python3 plan.py effects/ascii_zones.sexp -p char_size=10 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   char_size: character cell size in pixels (4 to 20, default: 10)
+
+(recipe "ascii_zones"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect ascii_zones :path "sexp_effects/effects/ascii_zones.sexp")
+  (analyzer energy :path "../artdag-analyzers/energy/analyzer.py")
+
+
+  ;; Default parameter (overridden by -p char_size=N)
+  (def char_size 10)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def audio (source :path "dizzy.mp3"))
+  (def audio-clip (-> audio (segment :start 60 :duration 10)))
+
+  ;; Analyze just the audio clip - times are 0-10s relative to clip
+  (def energy-data (-> audio-clip (analyze energy)))
+
+
+
+  ;; char_size bound to energy - no offset needed since analysis is on clip
+  (def result (-> clip
+    (effect ascii_zones
+      :char_size (bind energy-data values :range [2 32]))))
+
+  (mux result audio-clip))

effects/beam.py

@@ -0,0 +1,164 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy"]
+# ///
+"""
+@effect beam
+@version 1.0.0
+@author artdag
+
+@description
+Beam effect. Creates animated light beams / lasers from a starting
+point to an ending point with glow effect.
+
+@param start_x float
+  @range 0 1
+  @default 0
+  Beam start X position (0-1).
+
+@param start_y float
+  @range 0 1
+  @default 0.5
+  Beam start Y position (0-1).
+
+@param end_x float
+  @range 0 1
+  @default 1
+  Beam end X position (0-1).
+
+@param end_y float
+  @range 0 1
+  @default 0.5
+  Beam end Y position (0-1).
+
+@param thickness float
+  @range 1 50
+  @default 5
+  Beam core thickness in pixels.
+
+@param glow_radius float
+  @range 0 100
+  @default 20
+  Outer glow size in pixels.
+
+@param color list
+  @default [0, 255, 255]
+  Beam color RGB (default cyan).
+
+@param intensity float
+  @range 0 2
+  @default 1.0
+  Beam brightness.
+
+@param pulse bool
+  @default false
+  Enable pulsing animation.
+
+@param pulse_speed float
+  @range 0.1 10
+  @default 2.0
+  Pulse animation speed.
+
+@example
+  (effect beam :start_x 0 :start_y 0.5 :end_x 1 :end_y 0.5)
+
+@example
+  ;; Reactive laser
+  (effect beam :intensity (bind bass :range [0.5 2]) :color [255 0 0])
+"""
+
+import numpy as np
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply beam effect to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+        state: Persistent state dict
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    start_x = params.get("start_x", 0)
+    start_y = params.get("start_y", 0.5)
+    end_x = params.get("end_x", 1)
+    end_y = params.get("end_y", 0.5)
+    thickness = params.get("thickness", 5)
+    glow_radius = params.get("glow_radius", 20)
+    color = params.get("color", [0, 255, 255])
+    intensity = params.get("intensity", 1.0)
+    pulse = params.get("pulse", False)
+    pulse_speed = params.get("pulse_speed", 2.0)
+    t = params.get("_time", 0)
+
+    if state is None:
+        state = {}
+
+    h, w = frame.shape[:2]
+    result = frame.copy().astype(np.float32)
+
+    # Calculate beam endpoints in pixels
+    x1, y1 = int(start_x * w), int(start_y * h)
+    x2, y2 = int(end_x * w), int(end_y * h)
+
+    # Apply pulse modulation
+    if pulse:
+        pulse_mod = 0.5 + 0.5 * np.sin(t * pulse_speed * 2 * np.pi)
+        intensity = intensity * pulse_mod
+
+    # Create coordinate grids
+    y_coords, x_coords = np.mgrid[0:h, 0:w].astype(np.float32)
+
+    # Calculate distance from each pixel to the line segment
+    line_vec = np.array([x2 - x1, y2 - y1], dtype=np.float32)
+    line_len = np.sqrt(line_vec[0]**2 + line_vec[1]**2)
+
+    if line_len < 1:
+        return frame, state
+
+    line_unit = line_vec / line_len
+
+    # Vector from start to each pixel
+    px = x_coords - x1
+    py = y_coords - y1
+
+    # Project onto line
+    proj_len = px * line_unit[0] + py * line_unit[1]
+    proj_len = np.clip(proj_len, 0, line_len)
+
+    # Closest point on line
+    closest_x = x1 + proj_len * line_unit[0]
+    closest_y = y1 + proj_len * line_unit[1]
+
+    # Distance to closest point
+    dist = np.sqrt((x_coords - closest_x)**2 + (y_coords - closest_y)**2)
+
+    # Get beam color
+    if isinstance(color, (list, tuple)) and len(color) >= 3:
+        beam_color = np.array(color[:3], dtype=np.float32)
+    else:
+        beam_color = np.array([0, 255, 255], dtype=np.float32)
+
+    # Core beam (bright center)
+    core_mask = dist < thickness
+    core_intensity = intensity * (1 - dist[core_mask] / max(1, thickness))
+    for c in range(3):
+        result[core_mask, c] = np.clip(
+            result[core_mask, c] + beam_color[c] * core_intensity,
+            0, 255
+        )
+
+    # Glow (fading outer region)
+    glow_mask = (dist >= thickness) & (dist < thickness + glow_radius)
+    glow_dist = dist[glow_mask] - thickness
+    glow_intensity = intensity * 0.5 * (1 - glow_dist / max(1, glow_radius)) ** 2
+    for c in range(3):
+        result[glow_mask, c] = np.clip(
+            result[glow_mask, c] + beam_color[c] * glow_intensity,
+            0, 255
+        )
+
+    return result.astype(np.uint8), state

effects/bloom.py

@@ -0,0 +1,108 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy", "opencv-python"]
+# ///
+"""
+@effect bloom
+@version 1.0.0
+@author artdag
+
+@description
+Bloom effect. Creates a soft glow around bright areas, simulating
+camera lens bloom. Great for dreamy or ethereal looks.
+
+@param intensity float
+  @range 0 2
+  @default 0.5
+  Bloom brightness.
+
+@param threshold int
+  @range 0 255
+  @default 200
+  Brightness threshold for bloom (pixels above this glow).
+
+@param radius int
+  @range 1 50
+  @default 15
+  Blur radius for the glow.
+
+@param soft_threshold bool
+  @default true
+  Use soft threshold (gradual) vs hard threshold.
+
+@param color_tint list
+  @default [255, 255, 255]
+  Tint color for the bloom.
+
+@example
+  (effect bloom :intensity 0.7 :threshold 180)
+
+@example
+  ;; Warm bloom
+  (effect bloom :intensity 0.6 :color_tint [255 200 150])
+"""
+
+import numpy as np
+import cv2
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply bloom effect to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - intensity: bloom brightness (default 0.5)
+            - threshold: brightness cutoff (default 200)
+            - radius: blur radius (default 15)
+            - soft_threshold: gradual vs hard (default True)
+            - color_tint: RGB tint (default white)
+        state: Persistent state dict
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    intensity = params.get("intensity", 0.5)
+    threshold = int(params.get("threshold", 200))
+    radius = max(1, int(params.get("radius", 15)))
+    soft_threshold = params.get("soft_threshold", True)
+    color_tint = params.get("color_tint", [255, 255, 255])
+
+    if state is None:
+        state = {}
+
+    if intensity <= 0:
+        return frame, state
+
+    # Convert to float
+    result = frame.astype(np.float32)
+
+    # Get brightness (luminance)
+    lum = 0.299 * result[:, :, 0] + 0.587 * result[:, :, 1] + 0.114 * result[:, :, 2]
+
+    # Create bloom mask
+    if soft_threshold:
+        # Soft threshold - gradual falloff
+        bloom_mask = np.clip((lum - threshold) / (255 - threshold + 1e-6), 0, 1)
+    else:
+        # Hard threshold
+        bloom_mask = (lum > threshold).astype(np.float32)
+
+    # Extract bright areas
+    bloom = result * bloom_mask[:, :, np.newaxis]
+
+    # Apply blur to create glow
+    ksize = radius * 2 + 1
+    bloom = cv2.GaussianBlur(bloom, (ksize, ksize), 0)
+
+    # Apply color tint
+    if isinstance(color_tint, (list, tuple)) and len(color_tint) >= 3:
+        tint = np.array(color_tint[:3], dtype=np.float32) / 255.0
+        for c in range(3):
+            bloom[:, :, c] *= tint[c]
+
+    # Add bloom to original (screen blend)
+    result = result + bloom * intensity
+
+    return np.clip(result, 0, 255).astype(np.uint8), state

effects/bloom.sexp

@@ -0,0 +1,21 @@
+;; Bloom effect - glow around bright areas
+;; Usage: python3 plan.py effects/bloom.sexp -p intensity=0.6 -p radius=20 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   intensity: bloom strength (0.0 to 2.0, default: 0.6)
+;;   radius: bloom spread in pixels (5 to 50, default: 20)
+
+(recipe "bloom"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect bloom :path "sexp_effects/effects/bloom.sexp")
+
+  ;; Default parameters (overridden by -p intensity=N -p radius=N)
+  (def intensity 0.6)
+  (def radius 20)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect bloom :intensity intensity :radius radius)))
+  result)

effects/blur.py

@@ -0,0 +1,54 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy", "opencv-python"]
+# ///
+"""
+@effect blur
+@version 1.0.0
+@author artdag
+
+@description
+Gaussian blur effect. Softens the image by averaging neighboring pixels.
+Useful for dreamy effects or reducing detail on quiet parts.
+
+@param radius float
+  @range 0 50
+  @default 5
+  Blur radius in pixels. Higher = more blur. Must be positive.
+
+@example
+  (effect blur :radius 10)
+
+@example
+  ;; Blur on quiet, sharp on loud
+  (effect blur :radius (bind energy :range [20 0]))
+"""
+
+import numpy as np
+import cv2
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply Gaussian blur to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - radius: blur radius in pixels (default 5)
+        state: Persistent state dict (unused)
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    radius = params.get("radius", 5)
+
+    if radius <= 0:
+        return frame, state
+
+    # Kernel size must be odd
+    ksize = int(radius) * 2 + 1
+
+    result = cv2.GaussianBlur(frame, (ksize, ksize), 0)
+
+    return result, state

effects/blur.sexp

@@ -0,0 +1,20 @@
+;; Blur effect - gaussian blur
+;; Usage: python3 plan.py effects/blur.sexp -p radius=10 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   radius: blur radius in pixels (1 to 50, default: 10)
+;;           higher = more blurry
+
+(recipe "blur"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect blur :path "sexp_effects/effects/blur.sexp")
+
+  ;; Default parameter (overridden by -p radius=N)
+  (def radius 10)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect blur :radius radius)))
+  result)

effects/brightness.py

@@ -0,0 +1,52 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy"]
+# ///
+"""
+@effect brightness
+@version 1.0.0
+@author artdag
+
+@description
+Adjusts the brightness of each frame by multiplying pixel values.
+Values > 1.0 brighten, < 1.0 darken. Useful for pulse effects synced to music.
+
+@param factor float
+  @range 0 3
+  @default 1.0
+  Brightness multiplier. 0 = black, 1 = unchanged, 2 = double brightness.
+  Bind to bass/energy for reactive brightness pulses.
+
+@example
+  (effect brightness :factor 1.5)
+
+@example
+  ;; Pulse brighter on bass hits
+  (effect brightness :factor (bind bass :range [1.0 2.0] :transform sqrt))
+"""
+
+import numpy as np
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Adjust brightness of a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - factor: brightness multiplier (default 1.0)
+        state: Persistent state dict (unused)
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    factor = params.get("factor", 1.0)
+
+    if factor == 1.0:
+        return frame, state
+
+    # Apply brightness multiplier with clipping
+    result = np.clip(frame.astype(np.float32) * factor, 0, 255).astype(np.uint8)
+
+    return result, state

effects/brightness.sexp

@@ -0,0 +1,20 @@
+;; Brightness effect - adjust image brightness
+;; Usage: python3 plan.py effects/brightness.sexp [-p amount=30] | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   amount: brightness adjustment (-255 to 255, default: 30)
+;;           negative = darker, positive = brighter
+
+(recipe "brightness"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect brightness :path "sexp_effects/effects/brightness.sexp")
+
+  ;; Default parameter (overridden by -p amount=N)
+  (def amount 30)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect brightness :amount amount)))
+  result)

effects/cartoon.py

@@ -0,0 +1,117 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy", "scipy"]
+# ///
+"""
+@effect cartoon
+@version 1.0.0
+@author artdag
+
+@description
+Cartoon / Cel-shaded effect. Simplifies colors into flat regions
+and adds dark edge outlines for a hand-drawn cartoon appearance.
+
+@param detail float
+  @range 0.1 1.0
+  @default 0.5
+  Edge detection sensitivity. Higher = more edges detected.
+
+@param edge_thickness int
+  @range 1 5
+  @default 1
+  Outline thickness in pixels.
+
+@param color_levels int
+  @range 2 32
+  @default 6
+  Number of color levels per channel.
+
+@param edge_color list
+  @default [0, 0, 0]
+  RGB color for edges (default black).
+
+@param blur_size int
+  @range 0 10
+  @default 2
+  Pre-blur for smoother color regions.
+
+@example
+  (effect cartoon :detail 0.6 :color_levels 4)
+
+@example
+  ;; Thick outlines, fewer colors
+  (effect cartoon :edge_thickness 3 :color_levels 3 :blur_size 4)
+"""
+
+import numpy as np
+from scipy import ndimage
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply cartoon effect to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - detail: edge sensitivity 0.1-1.0 (default 0.5)
+            - edge_thickness: outline thickness (default 1)
+            - color_levels: posterization levels (default 6)
+            - edge_color: RGB tuple (default [0,0,0])
+            - blur_size: pre-blur amount (default 2)
+        state: Persistent state dict
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    detail = np.clip(params.get("detail", 0.5), 0.1, 1.0)
+    edge_thickness = max(1, min(int(params.get("edge_thickness", 1)), 5))
+    color_levels = max(2, min(int(params.get("color_levels", 6)), 32))
+    edge_color = params.get("edge_color", [0, 0, 0])
+    blur_size = max(0, int(params.get("blur_size", 2)))
+
+    if state is None:
+        state = {}
+
+    h, w = frame.shape[:2]
+    result = frame.copy().astype(np.float32)
+
+    # Step 1: Blur to reduce noise and create smoother regions
+    if blur_size > 0:
+        for c in range(3):
+            result[:, :, c] = ndimage.uniform_filter(result[:, :, c], size=blur_size)
+
+    # Step 2: Posterize colors (reduce to N levels)
+    step = 256 / color_levels
+    result = (np.floor(result / step) * step).astype(np.uint8)
+
+    # Step 3: Detect edges using Sobel
+    gray = np.mean(frame, axis=2).astype(np.float32)
+
+    sobel_x = ndimage.sobel(gray, axis=1)
+    sobel_y = ndimage.sobel(gray, axis=0)
+    edges = np.sqrt(sobel_x**2 + sobel_y**2)
+
+    # Normalize and threshold
+    edge_max = edges.max()
+    if edge_max > 0:
+        edges = edges / edge_max
+
+    edge_threshold = 1.0 - detail
+    edge_mask = edges > edge_threshold
+
+    # Dilate edges for thickness
+    if edge_thickness > 1:
+        struct = ndimage.generate_binary_structure(2, 1)
+        for _ in range(edge_thickness - 1):
+            edge_mask = ndimage.binary_dilation(edge_mask, structure=struct)
+
+    # Step 4: Apply edge color
+    if isinstance(edge_color, (list, tuple)) and len(edge_color) >= 3:
+        color = np.array(edge_color[:3], dtype=np.uint8)
+    else:
+        color = np.array([0, 0, 0], dtype=np.uint8)
+
+    result[edge_mask] = color
+
+    return result, state

effects/chromatic.py

@@ -0,0 +1,115 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy", "opencv-python"]
+# ///
+"""
+@effect chromatic
+@version 1.0.0
+@author artdag
+
+@description
+Chromatic aberration effect. Creates color fringing by offsetting
+RGB channels radially from the center (lens distortion simulation).
+
+@param strength float
+  @range 0 50
+  @default 10
+  Aberration strength. Bind to bass for reactive effect.
+
+@param center_x float
+  @range 0 1
+  @default 0.5
+  Aberration center X.
+
+@param center_y float
+  @range 0 1
+  @default 0.5
+  Aberration center Y.
+
+@param radial bool
+  @default true
+  If true, aberration increases from center to edges.
+
+@example
+  (effect chromatic :strength 20)
+
+@example
+  ;; Beat-reactive chromatic aberration
+  (effect chromatic :strength (bind bass :range [0 30]))
+"""
+
+import numpy as np
+import cv2
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply chromatic aberration effect to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - strength: aberration amount (default 10)
+            - center_x: center X 0-1 (default 0.5)
+            - center_y: center Y 0-1 (default 0.5)
+            - radial: increase from center (default True)
+        state: Persistent state dict
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    strength = params.get("strength", 10)
+    center_x = params.get("center_x", 0.5)
+    center_y = params.get("center_y", 0.5)
+    radial = params.get("radial", True)
+
+    if state is None:
+        state = {}
+
+    if strength == 0:
+        return frame, state
+
+    h, w = frame.shape[:2]
+    r, g, b = frame[:, :, 0], frame[:, :, 1], frame[:, :, 2]
+
+    if radial:
+        # Create distance-from-center map
+        y_coords, x_coords = np.ogrid[:h, :w]
+        cx, cy = w * center_x, h * center_y
+        dist = np.sqrt((x_coords - cx)**2 + (y_coords - cy)**2)
+        max_dist = np.sqrt(cx**2 + cy**2)
+        dist_normalized = (dist / max_dist).astype(np.float32)
+
+        # Create coordinate maps for remapping
+        map_x = np.tile(np.arange(w, dtype=np.float32), (h, 1))
+        map_y = np.tile(np.arange(h, dtype=np.float32).reshape(-1, 1), (1, w))
+
+        # Direction from center
+        dx = (map_x - cx) / (dist + 1e-6)
+        dy = (map_y - cy) / (dist + 1e-6)
+
+        # Apply radial offset to red channel (outward)
+        r_offset = strength * dist_normalized
+        r_map_x = (map_x + dx * r_offset).astype(np.float32)
+        r_map_y = (map_y + dy * r_offset).astype(np.float32)
+        r_shifted = cv2.remap(r, r_map_x, r_map_y,
+                              cv2.INTER_LINEAR, borderMode=cv2.BORDER_REPLICATE)
+
+        # Apply radial offset to blue channel (inward)
+        b_offset = -strength * dist_normalized
+        b_map_x = (map_x + dx * b_offset).astype(np.float32)
+        b_map_y = (map_y + dy * b_offset).astype(np.float32)
+        b_shifted = cv2.remap(b, b_map_x, b_map_y,
+                              cv2.INTER_LINEAR, borderMode=cv2.BORDER_REPLICATE)
+
+        return np.stack([r_shifted, g, b_shifted], axis=-1).astype(np.uint8), state
+    else:
+        # Simple uniform offset
+        offset = int(strength)
+        M_r = np.float32([[1, 0, offset], [0, 1, 0]])
+        M_b = np.float32([[1, 0, -offset], [0, 1, 0]])
+
+        r_shifted = cv2.warpAffine(r, M_r, (w, h), borderMode=cv2.BORDER_REPLICATE)
+        b_shifted = cv2.warpAffine(b, M_b, (w, h), borderMode=cv2.BORDER_REPLICATE)
+
+        return np.stack([r_shifted, g, b_shifted], axis=-1).astype(np.uint8), state

effects/color-adjust.sexp

@@ -0,0 +1,21 @@
+;; Color adjust effect - combined brightness and contrast
+;; Usage: python3 plan.py effects/color-adjust.sexp -p brightness=20 -p contrast=1.2 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   brightness: brightness adjustment (-255 to 255, default: 20)
+;;   contrast: contrast multiplier (0.0 to 3.0, default: 1.2)
+
+(recipe "color-adjust"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect color-adjust :path "sexp_effects/effects/color-adjust.sexp")
+
+  ;; Default parameters (overridden by -p brightness=N -p contrast=N)
+  (def brightness 20)
+  (def contrast 1.2)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect color-adjust :brightness brightness :contrast contrast)))
+  result)

effects/color_cycle.py

@@ -0,0 +1,104 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy", "opencv-python"]
+# ///
+"""
+@effect color_cycle
+@version 1.0.0
+@author artdag
+
+@description
+Color cycle effect. Shifts all hues over time creating psychedelic
+rainbow cycling. Great for trippy visuals.
+
+@param speed float
+  @range 0 10
+  @default 1
+  Cycle speed (rotations per second).
+
+@param offset float
+  @range 0 360
+  @default 0
+  Initial hue offset in degrees.
+
+@param saturation_boost float
+  @range 0 2
+  @default 1
+  Saturation multiplier.
+
+@param mode string
+  @enum all highlights shadows midtones
+  @default all
+  Which tones to affect.
+
+@example
+  (effect color_cycle :speed 0.5)
+
+@example
+  ;; Beat-synced color shift
+  (effect color_cycle :offset (bind beat_position :range [0 360]))
+"""
+
+import numpy as np
+import cv2
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply color cycle effect to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - speed: rotations per second (default 1)
+            - offset: initial hue offset (default 0)
+            - saturation_boost: saturation multiplier (default 1)
+            - mode: which tones to affect (default all)
+        state: Persistent state dict
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    speed = params.get("speed", 1)
+    offset = params.get("offset", 0)
+    saturation_boost = max(0, min(params.get("saturation_boost", 1), 2))
+    mode = params.get("mode", "all")
+    t = params.get("_time", 0)
+
+    if state is None:
+        state = {}
+
+    # Calculate hue shift
+    hue_shift = int((offset + speed * t * 360) % 360)
+
+    # Convert to HSV (OpenCV uses BGR, our frame is RGB)
+    frame_bgr = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
+    hsv = cv2.cvtColor(frame_bgr, cv2.COLOR_BGR2HSV).astype(np.float32)
+
+    if mode == "all":
+        # Shift all hues
+        hsv[:, :, 0] = (hsv[:, :, 0] + hue_shift / 2) % 180
+        hsv[:, :, 1] = np.clip(hsv[:, :, 1] * saturation_boost, 0, 255)
+    else:
+        # Calculate luminance mask
+        lum = hsv[:, :, 2] / 255.0
+
+        if mode == "highlights":
+            mask = np.clip((lum - 0.67) * 3, 0, 1)
+        elif mode == "shadows":
+            mask = np.clip(1 - lum * 3, 0, 1)
+        else:  # midtones
+            shadow_mask = np.clip(1 - lum * 3, 0, 1)
+            highlight_mask = np.clip((lum - 0.67) * 3, 0, 1)
+            mask = 1 - shadow_mask - highlight_mask
+
+        # Apply selective hue shift
+        shifted_hue = (hsv[:, :, 0] + hue_shift / 2) % 180
+        hsv[:, :, 0] = hsv[:, :, 0] * (1 - mask) + shifted_hue * mask
+
+    # Convert back
+    hsv = np.clip(hsv, 0, 255).astype(np.uint8)
+    result_bgr = cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)
+    result = cv2.cvtColor(result_bgr, cv2.COLOR_BGR2RGB)
+
+    return result, state

effects/color_cycle.sexp

@@ -0,0 +1,20 @@
+;; Color cycle effect - animated hue rotation over time
+;; Usage: python3 plan.py effects/color_cycle.sexp -p speed=2 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   speed: rotation speed multiplier (0.1 to 10, default: 2)
+;;          higher = faster color cycling
+
+(recipe "color_cycle"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect color_cycle :path "sexp_effects/effects/color_cycle.sexp")
+
+  ;; Default parameter (overridden by -p speed=N)
+  (def speed 2)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect color_cycle :speed speed)))
+  result)

effects/color_grade.py

@@ -0,0 +1,139 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy", "opencv-python"]
+# ///
+"""
+@effect color_grade
+@version 1.0.0
+@author artdag
+
+@description
+Color grading effect. Applies cinematic color adjustments including
+shadows/midtones/highlights tinting, lift/gamma/gain, and temperature.
+
+@param shadows list
+  @default [0, 0, 0]
+  RGB tint for dark areas.
+
+@param midtones list
+  @default [0, 0, 0]
+  RGB tint for middle tones.
+
+@param highlights list
+  @default [0, 0, 0]
+  RGB tint for bright areas.
+
+@param lift float
+  @range -0.5 0.5
+  @default 0
+  Raise/lower shadow levels.
+
+@param gamma float
+  @range 0.5 2
+  @default 1
+  Midtone brightness curve.
+
+@param gain float
+  @range 0.5 2
+  @default 1
+  Highlight intensity.
+
+@param temperature float
+  @range -100 100
+  @default 0
+  Color temperature (-100 = cool/blue, +100 = warm/orange).
+
+@param tint float
+  @range -100 100
+  @default 0
+  Green/magenta tint (-100 = green, +100 = magenta).
+
+@example
+  (effect color_grade :temperature 30 :shadows [0 0 20])
+
+@example
+  ;; Cinematic teal-orange look
+  (effect color_grade :shadows [0 10 20] :highlights [20 10 0])
+"""
+
+import numpy as np
+import cv2
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply color grading to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+        state: Persistent state dict
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    shadows = params.get("shadows", [0, 0, 0])
+    midtones = params.get("midtones", [0, 0, 0])
+    highlights = params.get("highlights", [0, 0, 0])
+    lift = params.get("lift", 0)
+    gamma = max(0.5, min(params.get("gamma", 1), 2))
+    gain = max(0.5, min(params.get("gain", 1), 2))
+    temperature = params.get("temperature", 0)
+    tint = params.get("tint", 0)
+
+    if state is None:
+        state = {}
+
+    result = frame.astype(np.float32) / 255.0
+
+    # Apply lift (shadows)
+    result = result + lift
+
+    # Apply gamma (midtones)
+    result = np.power(np.clip(result, 0.001, 1), 1 / gamma)
+
+    # Apply gain (highlights)
+    result = result * gain
+
+    # Convert tints to float
+    if isinstance(shadows, (list, tuple)) and len(shadows) >= 3:
+        shadows = np.array(shadows[:3], dtype=np.float32) / 255.0
+    else:
+        shadows = np.zeros(3, dtype=np.float32)
+
+    if isinstance(midtones, (list, tuple)) and len(midtones) >= 3:
+        midtones = np.array(midtones[:3], dtype=np.float32) / 255.0
+    else:
+        midtones = np.zeros(3, dtype=np.float32)
+
+    if isinstance(highlights, (list, tuple)) and len(highlights) >= 3:
+        highlights = np.array(highlights[:3], dtype=np.float32) / 255.0
+    else:
+        highlights = np.zeros(3, dtype=np.float32)
+
+    # Calculate luminance for zone-based grading
+    lum = 0.299 * result[:, :, 0] + 0.587 * result[:, :, 1] + 0.114 * result[:, :, 2]
+
+    # Create zone masks
+    shadow_mask = np.clip(1 - lum * 3, 0, 1)[:, :, np.newaxis]
+    highlight_mask = np.clip((lum - 0.67) * 3, 0, 1)[:, :, np.newaxis]
+    midtone_mask = 1 - shadow_mask - highlight_mask
+
+    # Apply zone tints
+    for c in range(3):
+        result[:, :, c] += shadows[c] * shadow_mask[:, :, 0]
+        result[:, :, c] += midtones[c] * midtone_mask[:, :, 0]
+        result[:, :, c] += highlights[c] * highlight_mask[:, :, 0]
+
+    # Apply temperature (blue <-> orange)
+    if temperature != 0:
+        temp_shift = temperature / 100.0
+        result[:, :, 0] += temp_shift * 0.3  # Red
+        result[:, :, 2] -= temp_shift * 0.3  # Blue
+
+    # Apply tint (green <-> magenta)
+    if tint != 0:
+        tint_shift = tint / 100.0
+        result[:, :, 1] -= tint_shift * 0.2  # Green
+
+    return (np.clip(result, 0, 1) * 255).astype(np.uint8), state

effects/contrast.py

@@ -0,0 +1,52 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy"]
+# ///
+"""
+@effect contrast
+@version 1.0.0
+@author artdag
+
+@description
+Adjusts contrast by scaling pixel values around the midpoint (128).
+Higher values increase contrast, lower values flatten the image.
+
+@param factor float
+  @range 0 3
+  @default 1.0
+  Contrast multiplier. 0.5 = low contrast, 1 = unchanged, 2 = high contrast.
+
+@example
+  (effect contrast :factor 1.5)
+
+@example
+  ;; Dramatic contrast on energy peaks
+  (effect contrast :factor (bind energy :range [1.0 2.0]))
+"""
+
+import numpy as np
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Adjust contrast of a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - factor: contrast multiplier (default 1.0)
+        state: Persistent state dict (unused)
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    factor = params.get("factor", 1.0)
+
+    if factor == 1.0:
+        return frame, state
+
+    # Adjust contrast around midpoint (128)
+    img_float = frame.astype(np.float32)
+    result = 128 + factor * (img_float - 128)
+
+    return np.clip(result, 0, 255).astype(np.uint8), state

effects/contrast.sexp

@@ -0,0 +1,20 @@
+;; Contrast effect - adjust image contrast
+;; Usage: python3 plan.py effects/contrast.sexp -p amount=1.5 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   amount: contrast multiplier (0.0 to 3.0, default: 1.5)
+;;           <1 = less contrast, >1 = more contrast
+
+(recipe "contrast"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect contrast :path "sexp_effects/effects/contrast.sexp")
+
+  ;; Default parameter (overridden by -p amount=N)
+  (def amount 1.5)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect contrast :amount amount)))
+  result)

effects/crt.py

@@ -0,0 +1,193 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy", "opencv-python"]
+# ///
+"""
+@effect crt
+@version 1.0.0
+@author artdag
+
+@description
+CRT / Scanlines effect. Simulates CRT monitor aesthetics with visible
+scan lines, optional RGB subpixels, barrel distortion, and vignette.
+
+@param line_spacing int
+  @range 1 10
+  @default 2
+  Pixels between scanlines.
+
+@param line_opacity float
+  @range 0 1
+  @default 0.3
+  Darkness of scanlines.
+
+@param rgb_subpixels bool
+  @default false
+  Show RGB subpixel pattern.
+
+@param curvature float
+  @range 0 0.5
+  @default 0
+  Barrel distortion amount for curved screen look.
+
+@param vignette float
+  @range 0 1
+  @default 0
+  Dark corners effect.
+
+@param bloom float
+  @range 0 1
+  @default 0
+  Glow/blur on bright areas.
+
+@param flicker float
+  @range 0 0.3
+  @default 0
+  Brightness variation.
+
+@param seed int
+  @default 42
+  Random seed for flicker.
+
+@state rng DeterministicRNG
+  Random number generator for flicker.
+
+@example
+  (effect crt :line_spacing 2 :line_opacity 0.4)
+
+@example
+  ;; Full retro CRT look
+  (effect crt :curvature 0.2 :vignette 0.3 :rgb_subpixels true :bloom 0.2)
+"""
+
+import numpy as np
+import cv2
+from pathlib import Path
+import sys
+
+# Import DeterministicRNG from same directory
+_effects_dir = Path(__file__).parent
+if str(_effects_dir) not in sys.path:
+    sys.path.insert(0, str(_effects_dir))
+from random import DeterministicRNG
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply CRT effect to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+        state: Persistent state dict
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    line_spacing = max(1, int(params.get("line_spacing", 2)))
+    line_opacity = params.get("line_opacity", 0.3)
+    rgb_subpixels = params.get("rgb_subpixels", False)
+    curvature = params.get("curvature", 0)
+    vignette = params.get("vignette", 0)
+    bloom = params.get("bloom", 0)
+    flicker = params.get("flicker", 0)
+    seed = int(params.get("seed", 42))
+
+    if state is None:
+        state = {}
+
+    # Initialize RNG
+    if "rng" not in state:
+        state["rng"] = DeterministicRNG(seed)
+    rng = state["rng"]
+
+    h, w = frame.shape[:2]
+    result = frame.astype(np.float32).copy()
+
+    # Apply barrel distortion (curvature)
+    if curvature > 0:
+        result = _apply_curvature(result, curvature)
+
+    # Apply bloom (glow on bright areas)
+    if bloom > 0:
+        result = _apply_bloom(result, bloom)
+
+    # Apply scanlines
+    if line_opacity > 0:
+        for y in range(0, h, line_spacing):
+            result[y, :] = result[y, :] * (1 - line_opacity)
+
+    # Apply RGB subpixel pattern
+    if rgb_subpixels:
+        for x in range(w):
+            col_type = x % 3
+            if col_type == 0:
+                result[:, x, 0] *= 1.2
+                result[:, x, 1] *= 0.8
+                result[:, x, 2] *= 0.8
+            elif col_type == 1:
+                result[:, x, 0] *= 0.8
+                result[:, x, 1] *= 1.2
+                result[:, x, 2] *= 0.8
+            else:
+                result[:, x, 0] *= 0.8
+                result[:, x, 1] *= 0.8
+                result[:, x, 2] *= 1.2
+
+    # Apply vignette
+    if vignette > 0:
+        y_coords, x_coords = np.ogrid[:h, :w]
+        center_x, center_y = w / 2, h / 2
+        dist = np.sqrt((x_coords - center_x)**2 + (y_coords - center_y)**2)
+        max_dist = np.sqrt(center_x**2 + center_y**2)
+        vignette_mask = 1 - (dist / max_dist) * vignette
+        vignette_mask = np.clip(vignette_mask, 0, 1)
+        result = result * vignette_mask[:, :, np.newaxis]
+
+    # Apply flicker
+    if flicker > 0:
+        flicker_amount = 1.0 + rng.uniform(-flicker, flicker)
+        result = result * flicker_amount
+
+    return np.clip(result, 0, 255).astype(np.uint8), state
+
+
+def _apply_curvature(frame: np.ndarray, strength: float) -> np.ndarray:
+    """Apply barrel distortion."""
+    h, w = frame.shape[:2]
+
+    y_coords, x_coords = np.mgrid[0:h, 0:w].astype(np.float32)
+
+    # Normalize to -1 to 1
+    x_norm = (x_coords - w / 2) / (w / 2)
+    y_norm = (y_coords - h / 2) / (h / 2)
+
+    # Calculate radius
+    r = np.sqrt(x_norm**2 + y_norm**2)
+
+    # Apply barrel distortion
+    r_distorted = r * (1 + strength * r**2)
+
+    # Scale factor
+    scale = np.where(r > 0, r_distorted / r, 1)
+
+    # New coordinates
+    new_x = (x_norm * scale * (w / 2) + w / 2).astype(np.float32)
+    new_y = (y_norm * scale * (h / 2) + h / 2).astype(np.float32)
+
+    result = cv2.remap(frame.astype(np.uint8), new_x, new_y,
+                      cv2.INTER_LINEAR, borderMode=cv2.BORDER_CONSTANT,
+                      borderValue=(0, 0, 0))
+    return result.astype(np.float32)
+
+
+def _apply_bloom(frame: np.ndarray, strength: float) -> np.ndarray:
+    """Apply bloom (glow on bright areas)."""
+    gray = cv2.cvtColor(frame.astype(np.uint8), cv2.COLOR_RGB2GRAY)
+    _, bright = cv2.threshold(gray, 200, 255, cv2.THRESH_BINARY)
+
+    bloom = cv2.GaussianBlur(bright, (21, 21), 0)
+    bloom = cv2.cvtColor(bloom, cv2.COLOR_GRAY2RGB)
+
+    result = frame + bloom.astype(np.float32) * strength * 0.5
+    return result

effects/crt.sexp

@@ -0,0 +1,21 @@
+;; CRT effect - old TV/monitor look with scanlines and vignette
+;; Usage: python3 plan.py effects/crt.sexp -p line_spacing=3 -p vignette_amount=0.3 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   line_spacing: pixels between scanlines (1 to 8, default: 3)
+;;   vignette_amount: edge darkening strength (0 to 1, default: 0.3)
+
+(recipe "crt"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect crt :path "sexp_effects/effects/crt.sexp")
+
+  ;; Default parameters (overridden by -p line_spacing=N -p vignette_amount=N)
+  (def line_spacing 3)
+  (def vignette_amount 0.3)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect crt :line_spacing line_spacing :vignette_amount vignette_amount)))
+  result)

effects/datamosh.py

@@ -0,0 +1,141 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy"]
+# ///
+"""
+@effect datamosh
+@version 1.0.0
+@author artdag
+
+@description
+Digital corruption / glitch block effect. Randomly corrupts rectangular
+blocks by shifting, swapping, or duplicating from previous frames.
+Simulates video compression artifacts.
+
+@param block_size int
+  @range 8 128
+  @default 32
+  Size of corruption blocks in pixels.
+
+@param corruption float
+  @range 0 1
+  @default 0.3
+  Probability of corrupting each block. Bind to energy for reactive glitch.
+
+@param max_offset int
+  @range 0 200
+  @default 50
+  Maximum pixel offset when shifting blocks.
+
+@param color_corrupt bool
+  @default true
+  Also apply color channel shifts to blocks.
+
+@param seed int
+  @default 42
+  Random seed for deterministic glitch patterns.
+
+@state previous_frame ndarray
+  Stores previous frame for frame-blending corruption.
+
+@state rng DeterministicRNG
+  Random number generator for reproducible results.
+
+@example
+  (effect datamosh :corruption 0.4)
+
+@example
+  ;; Heavy glitch on energy peaks
+  (effect datamosh :corruption (bind energy :range [0 0.8]) :block_size 16)
+
+@example
+  ;; Reproducible glitch with seed
+  (effect datamosh :corruption 0.5 :seed 12345)
+"""
+
+import numpy as np
+from pathlib import Path
+import sys
+
+# Import DeterministicRNG from same directory
+_effects_dir = Path(__file__).parent
+if str(_effects_dir) not in sys.path:
+    sys.path.insert(0, str(_effects_dir))
+from random import DeterministicRNG
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply datamosh/glitch block effect to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - block_size: corruption block size (default 32)
+            - corruption: probability 0-1 (default 0.3)
+            - max_offset: max shift in pixels (default 50)
+            - color_corrupt: apply color shifts (default True)
+        state: Persistent state dict
+            - previous_frame: last frame for duplication effect
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    block_size = max(8, min(int(params.get("block_size", 32)), 128))
+    corruption = max(0, min(params.get("corruption", 0.3), 1))
+    max_offset = int(params.get("max_offset", 50))
+    color_corrupt = params.get("color_corrupt", True)
+    seed = int(params.get("seed", 42))
+
+    if state is None:
+        state = {}
+
+    # Initialize RNG
+    if "rng" not in state:
+        state["rng"] = DeterministicRNG(seed)
+    rng = state["rng"]
+
+    if corruption == 0:
+        state["previous_frame"] = frame.copy()
+        return frame, state
+
+    h, w = frame.shape[:2]
+    result = frame.copy()
+    prev_frame = state.get("previous_frame")
+
+    # Process blocks
+    for by in range(0, h, block_size):
+        for bx in range(0, w, block_size):
+            bh = min(block_size, h - by)
+            bw = min(block_size, w - bx)
+
+            if rng.uniform() < corruption:
+                corruption_type = rng.choice(["shift", "duplicate", "color", "swap"])
+
+                if corruption_type == "shift" and max_offset > 0:
+                    ox = rng.randint(-max_offset, max_offset)
+                    oy = rng.randint(-max_offset, max_offset)
+                    src_x = max(0, min(bx + ox, w - bw))
+                    src_y = max(0, min(by + oy, h - bh))
+                    result[by:by+bh, bx:bx+bw] = frame[src_y:src_y+bh, src_x:src_x+bw]
+
+                elif corruption_type == "duplicate" and prev_frame is not None:
+                    if prev_frame.shape == frame.shape:
+                        result[by:by+bh, bx:bx+bw] = prev_frame[by:by+bh, bx:bx+bw]
+
+                elif corruption_type == "color" and color_corrupt:
+                    block = result[by:by+bh, bx:bx+bw].copy()
+                    shift = rng.randint(1, 3)
+                    channel = rng.randint(0, 2)
+                    block[:, :, channel] = np.roll(block[:, :, channel], shift, axis=0)
+                    result[by:by+bh, bx:bx+bw] = block
+
+                elif corruption_type == "swap":
+                    other_bx = rng.randint(0, max(0, w - bw - 1))
+                    other_by = rng.randint(0, max(0, h - bh - 1))
+                    temp = result[by:by+bh, bx:bx+bw].copy()
+                    result[by:by+bh, bx:bx+bw] = frame[other_by:other_by+bh, other_bx:other_bx+bw]
+                    result[other_by:other_by+bh, other_bx:other_bx+bw] = temp
+
+    state["previous_frame"] = frame.copy()
+    return result, state

effects/datamosh.sexp

@@ -0,0 +1,21 @@
+;; Datamosh effect - glitch art block corruption
+;; Usage: python3 plan.py effects/datamosh.sexp -p corruption=0.5 -p block_size=24 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   corruption: corruption intensity (0.1 to 1.0, default: 0.5)
+;;   block_size: size of corrupted blocks (8 to 64, default: 24)
+
+(recipe "datamosh"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect datamosh :path "sexp_effects/effects/datamosh.sexp")
+
+  ;; Default parameters (overridden by -p corruption=N -p block_size=N)
+  (def corruption 0.5)
+  (def block_size 24)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect datamosh :corruption corruption :block_size block_size)))
+  result)

effects/displacement.py

@@ -0,0 +1,170 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy", "opencv-python"]
+# ///
+"""
+@effect displacement
+@version 1.0.0
+@author artdag
+
+@description
+Displacement effect. Warps the image based on a pattern (sine waves,
+noise, or radial). Creates flowing, liquid-like distortions.
+
+@param amount float
+  @range 0 100
+  @default 20
+  Displacement strength in pixels.
+
+@param pattern string
+  @enum sine noise radial turbulence
+  @default sine
+  Displacement pattern type:
+  - sine: smooth sine wave
+  - noise: random displacement
+  - radial: swirl from center
+  - turbulence: multi-scale noise
+
+@param frequency float
+  @range 1 50
+  @default 10
+  Pattern frequency (waves per frame width).
+
+@param speed float
+  @range 0 10
+  @default 1
+  Animation speed.
+
+@param direction string
+  @enum horizontal vertical both
+  @default both
+  Displacement direction.
+
+@param seed int
+  @default 42
+  Random seed for noise patterns.
+
+@state rng DeterministicRNG
+  Random number generator.
+
+@example
+  (effect displacement :amount 30 :pattern "sine" :frequency 5)
+
+@example
+  ;; Reactive turbulence
+  (effect displacement :amount (bind energy :range [10 50]) :pattern "turbulence")
+"""
+
+import numpy as np
+import cv2
+from pathlib import Path
+import sys
+
+# Import DeterministicRNG from same directory
+_effects_dir = Path(__file__).parent
+if str(_effects_dir) not in sys.path:
+    sys.path.insert(0, str(_effects_dir))
+from random import DeterministicRNG
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply displacement effect to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+        state: Persistent state dict
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    amount = params.get("amount", 20)
+    pattern = params.get("pattern", "sine")
+    frequency = max(1, params.get("frequency", 10))
+    speed = params.get("speed", 1)
+    direction = params.get("direction", "both")
+    seed = int(params.get("seed", 42))
+    t = params.get("_time", 0)
+
+    if state is None:
+        state = {}
+
+    if amount == 0:
+        return frame, state
+
+    # Initialize RNG
+    if "rng" not in state:
+        state["rng"] = DeterministicRNG(seed)
+
+    h, w = frame.shape[:2]
+
+    # Create base coordinate maps
+    map_x = np.tile(np.arange(w, dtype=np.float32), (h, 1))
+    map_y = np.tile(np.arange(h, dtype=np.float32).reshape(-1, 1), (1, w))
+
+    # Generate displacement based on pattern
+    if pattern == "sine":
+        # Sine wave displacement
+        phase = t * speed * 2 * np.pi
+        if direction in ["horizontal", "both"]:
+            map_x = map_x + amount * np.sin(2 * np.pi * map_y / h * frequency + phase)
+        if direction in ["vertical", "both"]:
+            map_y = map_y + amount * np.sin(2 * np.pi * map_x / w * frequency + phase)
+
+    elif pattern == "noise":
+        # Generate noise displacement
+        rng = state["rng"]
+        if "noise_x" not in state or state.get("noise_size") != (h, w):
+            state["noise_x"] = np.array([[rng.uniform(-1, 1) for _ in range(w)] for _ in range(h)], dtype=np.float32)
+            state["noise_y"] = np.array([[rng.uniform(-1, 1) for _ in range(w)] for _ in range(h)], dtype=np.float32)
+            state["noise_size"] = (h, w)
+
+        if direction in ["horizontal", "both"]:
+            map_x = map_x + amount * state["noise_x"]
+        if direction in ["vertical", "both"]:
+            map_y = map_y + amount * state["noise_y"]
+
+    elif pattern == "radial":
+        # Radial/swirl displacement
+        cx, cy = w / 2, h / 2
+        y_coords, x_coords = np.mgrid[0:h, 0:w].astype(np.float32)
+        dx = x_coords - cx
+        dy = y_coords - cy
+        dist = np.sqrt(dx**2 + dy**2) + 1e-6
+        angle = np.arctan2(dy, dx)
+
+        # Swirl amount varies with distance and time
+        swirl = amount * 0.01 * np.sin(dist / (w / frequency) + t * speed * 2 * np.pi)
+
+        new_angle = angle + swirl
+        if direction in ["horizontal", "both"]:
+            map_x = cx + dist * np.cos(new_angle)
+        if direction in ["vertical", "both"]:
+            map_y = cy + dist * np.sin(new_angle)
+
+    elif pattern == "turbulence":
+        # Multi-scale noise
+        rng = state["rng"]
+        disp_x = np.zeros((h, w), dtype=np.float32)
+        disp_y = np.zeros((h, w), dtype=np.float32)
+
+        for scale in [1, 2, 4]:
+            sh, sw = h // scale, w // scale
+            noise_x = np.array([[rng.uniform(-1, 1) for _ in range(sw)] for _ in range(sh)], dtype=np.float32)
+            noise_y = np.array([[rng.uniform(-1, 1) for _ in range(sw)] for _ in range(sh)], dtype=np.float32)
+            if scale > 1:
+                noise_x = cv2.resize(noise_x, (w, h))
+                noise_y = cv2.resize(noise_y, (w, h))
+            disp_x += noise_x / scale
+            disp_y += noise_y / scale
+
+        if direction in ["horizontal", "both"]:
+            map_x = map_x + amount * disp_x
+        if direction in ["vertical", "both"]:
+            map_y = map_y + amount * disp_y
+
+    # Apply remapping
+    result = cv2.remap(frame, map_x, map_y, cv2.INTER_LINEAR, borderMode=cv2.BORDER_REFLECT)
+
+    return result, state

effects/echo.py

@@ -0,0 +1,139 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy"]
+# ///
+"""
+@effect echo
+@version 1.0.0
+@author artdag
+
+@description
+Motion trail / echo effect. Blends current frame with previous frames
+to create ghosting/trailing effects. Great for fast movement scenes.
+
+Uses a frame buffer in state to store recent frames for blending.
+
+@param num_echoes int
+  @range 1 20
+  @default 4
+  Number of trailing frames to blend.
+
+@param decay float
+  @range 0 1
+  @default 0.5
+  Opacity ratio between successive echoes. 0.5 = each echo half as bright.
+
+@param blend_mode string
+  @enum blend add screen maximum
+  @default blend
+  How to combine echoes:
+  - blend: weighted average
+  - add: sum (can overexpose)
+  - screen: like add but resists overexposure
+  - maximum: brightest pixel wins
+
+@state frame_buffer list
+  Circular buffer of recent frames.
+
+@example
+  (effect echo :num_echoes 6 :decay 0.6)
+
+@example
+  ;; More echoes on energy
+  (effect echo :num_echoes (bind energy :range [2 10]))
+"""
+
+import numpy as np
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply echo/motion trail effect to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - num_echoes: number of trailing frames (default 4)
+            - decay: opacity decay ratio (default 0.5)
+            - blend_mode: blend/add/screen/maximum (default blend)
+        state: Persistent state dict
+            - frame_buffer: list of recent frames
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    num_echoes = max(1, min(int(params.get("num_echoes", 4)), 20))
+    decay = max(0, min(params.get("decay", 0.5), 1))
+    blend_mode = params.get("blend_mode", "blend")
+
+    if state is None:
+        state = {}
+
+    # Initialize frame buffer
+    if "frame_buffer" not in state:
+        state["frame_buffer"] = []
+
+    buffer = state["frame_buffer"]
+
+    # Add current frame to buffer
+    buffer.append(frame.copy())
+
+    # Limit buffer size
+    max_buffer = num_echoes + 5
+    while len(buffer) > max_buffer:
+        buffer.pop(0)
+
+    # Collect frames and intensities for blending
+    frames = []
+    intensities = []
+    intensity = 1.0
+
+    # Current frame first, then older frames
+    for i in range(min(num_echoes + 1, len(buffer))):
+        idx = len(buffer) - 1 - i
+        if idx >= 0:
+            frames.append(buffer[idx].astype(np.float32))
+            intensities.append(intensity)
+            intensity *= decay
+
+    if not frames:
+        return frame, state
+
+    # Blend frames according to mode
+    result = _blend_frames(frames, intensities, blend_mode)
+
+    return np.clip(result, 0, 255).astype(np.uint8), state
+
+
+def _blend_frames(frames, intensities, blend_mode):
+    """Blend multiple frames according to blend mode."""
+    if not frames:
+        return frames[0]
+
+    if blend_mode == "add":
+        result = np.zeros_like(frames[0])
+        for frame, intensity in zip(frames, intensities):
+            result += frame * intensity
+        return result
+
+    elif blend_mode == "screen":
+        result = np.zeros_like(frames[0])
+        for frame, intensity in zip(frames, intensities):
+            weighted = (frame / 255.0) * intensity
+            result = 255 * (1 - (1 - result / 255.0) * (1 - weighted))
+        return result
+
+    elif blend_mode == "maximum":
+        result = frames[0] * intensities[0]
+        for frame, intensity in zip(frames[1:], intensities[1:]):
+            result = np.maximum(result, frame * intensity)
+        return result
+
+    else:  # blend - weighted average
+        total = sum(intensities)
+        if total == 0:
+            return frames[0]
+        result = np.zeros_like(frames[0])
+        for frame, intensity in zip(frames, intensities):
+            result += frame * (intensity / total)
+        return result

effects/echo.sexp

@@ -0,0 +1,21 @@
+;; Echo effect - temporal ghosting/trails
+;; Usage: python3 plan.py effects/echo.sexp -p num_echoes=4 -p decay=0.5 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   num_echoes: number of ghost frames (1 to 10, default: 4)
+;;   decay: fade rate per echo (0.2 to 0.9, default: 0.5)
+
+(recipe "echo"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect echo :path "sexp_effects/effects/echo.sexp")
+
+  ;; Default parameters (overridden by -p num_echoes=N -p decay=N)
+  (def num_echoes 4)
+  (def decay 0.5)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect echo :num_echoes num_echoes :decay decay)))
+  result)

effects/edge_detect.sexp

@@ -0,0 +1,22 @@
+;; Edge detect effect - Canny edge detection
+;; Usage: python3 plan.py effects/edge_detect.sexp -p low=50 -p high=150 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   low: lower threshold (10 to 100, default: 50)
+;;   high: upper threshold (100 to 300, default: 150)
+;;         edges between low-high are kept if connected to strong edges
+
+(recipe "edge_detect"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect edge_detect :path "sexp_effects/effects/edge_detect.sexp")
+
+  ;; Default parameters (overridden by -p low=N -p high=N)
+  (def low 50)
+  (def high 150)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect edge_detect :low low :high high)))
+  result)

effects/emboss.py

@@ -0,0 +1,88 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy", "opencv-python"]
+# ///
+"""
+@effect emboss
+@version 1.0.0
+@author artdag
+
+@description
+Emboss / relief effect. Creates a 3D raised appearance by highlighting
+edges from a simulated light direction. Great for sculptural looks.
+
+@param strength float
+  @range 0.5 3
+  @default 1.0
+  Emboss intensity.
+
+@param direction float
+  @range 0 360
+  @default 135
+  Light direction in degrees. Bind to beat for rotating light.
+
+@param blend float
+  @range 0 1
+  @default 0.3
+  Blend with original (0 = full emboss, 1 = original).
+
+@example
+  (effect emboss :strength 1.5)
+
+@example
+  ;; Rotating light direction
+  (effect emboss :direction (bind beat_position :range [0 360]))
+"""
+
+import numpy as np
+import cv2
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply emboss effect to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - strength: emboss intensity (default 1.0)
+            - direction: light angle in degrees (default 135)
+            - blend: mix with original (default 0.3)
+        state: Persistent state dict (unused)
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    strength = params.get("strength", 1.0)
+    direction = params.get("direction", 135)
+    blend = params.get("blend", 0.3)
+
+    # Calculate kernel based on direction
+    angle_rad = np.deg2rad(direction)
+    dx = np.cos(angle_rad)
+    dy = np.sin(angle_rad)
+
+    # Create emboss kernel
+    kernel = np.array([
+        [-strength * dy - strength * dx, -strength * dy, -strength * dy + strength * dx],
+        [-strength * dx, 1, strength * dx],
+        [strength * dy - strength * dx, strength * dy, strength * dy + strength * dx]
+    ], dtype=np.float32)
+
+    # Apply to grayscale
+    gray = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY).astype(np.float32)
+    embossed = cv2.filter2D(gray, -1, kernel)
+
+    # Normalize
+    embossed = embossed + 128
+    embossed = np.clip(embossed, 0, 255)
+
+    # Convert to RGB
+    embossed_rgb = cv2.cvtColor(embossed.astype(np.uint8), cv2.COLOR_GRAY2RGB)
+
+    # Blend with original
+    if blend > 0:
+        result = frame.astype(np.float32) * blend + embossed_rgb.astype(np.float32) * (1 - blend)
+        return np.clip(result, 0, 255).astype(np.uint8), state
+
+    return embossed_rgb, state

effects/emboss.sexp

@@ -0,0 +1,19 @@
+;; Emboss effect - 3D raised surface look
+;; Usage: python3 plan.py effects/emboss.sexp -p strength=1.5 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   strength: emboss intensity (0.5 to 3.0, default: 1.5)
+
+(recipe "emboss"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect emboss :path "sexp_effects/effects/emboss.sexp")
+
+  ;; Default parameter (overridden by -p strength=N)
+  (def strength 1.5)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect emboss :strength strength)))
+  result)

effects/film_grain.py

@@ -0,0 +1,148 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy", "opencv-python"]
+# ///
+"""
+@effect film_grain
+@version 1.0.0
+@author artdag
+
+@description
+Film grain / Noise effect. Adds realistic film grain texture.
+Great for vintage aesthetics and subtle texture.
+
+@param intensity float
+  @range 0 1
+  @default 0.2
+  Noise intensity. Bind to energy for reactive grain.
+
+@param grain_size float
+  @range 0.5 5
+  @default 1.0
+  Size of grain particles. Larger = coarser grain.
+
+@param colored bool
+  @default false
+  Use colored noise instead of monochrome.
+
+@param temporal_variation float
+  @range 0 1
+  @default 1.0
+  How much grain changes frame-to-frame. 0 = static, 1 = full animation.
+
+@param seed int
+  @default 42
+  Random seed for reproducible grain.
+
+@state rng DeterministicRNG
+  Random number generator for consistent grain.
+
+@example
+  (effect film_grain :intensity 0.3)
+
+@example
+  ;; Colored grain, reactive to energy
+  (effect film_grain :intensity (bind energy :range [0.1 0.5]) :colored true)
+"""
+
+import numpy as np
+import cv2
+from pathlib import Path
+import sys
+
+# Import DeterministicRNG from same directory
+_effects_dir = Path(__file__).parent
+if str(_effects_dir) not in sys.path:
+    sys.path.insert(0, str(_effects_dir))
+from random import DeterministicRNG
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply film grain effect to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - intensity: noise intensity 0-1 (default 0.2)
+            - grain_size: grain particle size (default 1.0)
+            - colored: use colored noise (default False)
+            - temporal_variation: grain animation 0-1 (default 1.0)
+            - seed: random seed (default 42)
+        state: Persistent state dict
+            - rng: DeterministicRNG instance
+            - frame_count: frame counter
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    intensity = params.get("intensity", 0.2)
+    grain_size = max(0.5, params.get("grain_size", 1.0))
+    colored = params.get("colored", False)
+    temporal_var = params.get("temporal_variation", 1.0)
+    seed = int(params.get("seed", 42))
+
+    if state is None:
+        state = {}
+
+    if intensity <= 0:
+        return frame, state
+
+    # Initialize RNG
+    if "rng" not in state:
+        state["rng"] = DeterministicRNG(seed)
+        state["frame_count"] = 0
+        state["static_noise"] = None
+
+    rng = state["rng"]
+    frame_count = state["frame_count"]
+
+    h, w = frame.shape[:2]
+
+    # Calculate noise dimensions
+    if grain_size > 1:
+        noise_h = max(1, int(h / grain_size))
+        noise_w = max(1, int(w / grain_size))
+    else:
+        noise_h, noise_w = h, w
+
+    # Generate noise based on temporal variation
+    if temporal_var >= 1.0 or state.get("static_noise") is None:
+        # Generate new noise
+        if colored:
+            noise = np.array([[[rng.gaussian(0, 1) for _ in range(3)]
+                              for _ in range(noise_w)]
+                             for _ in range(noise_h)]) * intensity * 50
+        else:
+            noise_2d = np.array([[rng.gaussian(0, 1)
+                                 for _ in range(noise_w)]
+                                for _ in range(noise_h)]) * intensity * 50
+            noise = np.stack([noise_2d, noise_2d, noise_2d], axis=-1)
+
+        if temporal_var < 1.0:
+            state["static_noise"] = noise
+    else:
+        # Blend static and new noise
+        static = state["static_noise"]
+        if colored:
+            new_noise = np.array([[[rng.gaussian(0, 1) for _ in range(3)]
+                                  for _ in range(noise_w)]
+                                 for _ in range(noise_h)]) * intensity * 50
+        else:
+            noise_2d = np.array([[rng.gaussian(0, 1)
+                                 for _ in range(noise_w)]
+                                for _ in range(noise_h)]) * intensity * 50
+            new_noise = np.stack([noise_2d, noise_2d, noise_2d], axis=-1)
+
+        noise = static * (1 - temporal_var) + new_noise * temporal_var
+
+    # Scale noise up if using larger grain
+    if grain_size > 1:
+        noise = cv2.resize(noise.astype(np.float32), (w, h), interpolation=cv2.INTER_LINEAR)
+
+    # Add noise to frame
+    result = frame.astype(np.float32) + noise
+
+    state["frame_count"] = frame_count + 1
+
+    return np.clip(result, 0, 255).astype(np.uint8), state

effects/film_grain.sexp

@@ -0,0 +1,19 @@
+;; Film grain effect - analog film noise
+;; Usage: python3 plan.py effects/film_grain.sexp -p intensity=0.25 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   intensity: grain amount (0.05 to 0.5, default: 0.25)
+
+(recipe "film_grain"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect film_grain :path "sexp_effects/effects/film_grain.sexp")
+
+  ;; Default parameter (overridden by -p intensity=N)
+  (def intensity 0.25)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect film_grain :intensity intensity)))
+  result)

effects/fisheye.py

@@ -0,0 +1,116 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy", "opencv-python"]
+# ///
+"""
+@effect fisheye
+@version 1.0.0
+@author artdag
+
+@description
+Barrel/fisheye lens distortion. Positive values bulge outward (fisheye),
+negative values pinch inward (pincushion). Great for emphasis effects.
+
+@param strength float
+  @range -1 1
+  @default 0.3
+  Distortion strength. Positive = fisheye bulge, negative = pincushion pinch.
+
+@param center_x float
+  @range 0 1
+  @default 0.5
+  Horizontal center of distortion (0 = left, 1 = right).
+
+@param center_y float
+  @range 0 1
+  @default 0.5
+  Vertical center of distortion (0 = top, 1 = bottom).
+
+@param zoom_correction bool
+  @default true
+  Automatically zoom to hide black edges on fisheye.
+
+@example
+  (effect fisheye :strength 0.5)
+
+@example
+  ;; Pulse fisheye on bass
+  (effect fisheye :strength (bind bass :range [0 0.8] :transform sqrt))
+
+@example
+  ;; Pincushion effect
+  (effect fisheye :strength -0.3)
+"""
+
+import numpy as np
+import cv2
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply fisheye/barrel distortion to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - strength: distortion strength -1 to 1 (default 0.3)
+            - center_x: horizontal center 0-1 (default 0.5)
+            - center_y: vertical center 0-1 (default 0.5)
+            - zoom_correction: auto-zoom for fisheye (default True)
+        state: Persistent state dict (unused)
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    strength = params.get("strength", 0.3)
+    center_x = params.get("center_x", 0.5)
+    center_y = params.get("center_y", 0.5)
+    zoom_correction = params.get("zoom_correction", True)
+
+    if strength == 0:
+        return frame, state
+
+    h, w = frame.shape[:2]
+
+    # Calculate center in pixels
+    cx = w * center_x
+    cy = h * center_y
+
+    # Create coordinate grids
+    y_coords, x_coords = np.mgrid[0:h, 0:w].astype(np.float32)
+
+    # Normalize coordinates relative to center
+    x_norm = (x_coords - cx) / (w / 2)
+    y_norm = (y_coords - cy) / (h / 2)
+
+    # Calculate radius from center
+    r = np.sqrt(x_norm**2 + y_norm**2)
+
+    # Apply barrel/pincushion distortion
+    if strength > 0:
+        # Barrel distortion (fisheye)
+        r_distorted = r * (1 + strength * r**2)
+    else:
+        # Pincushion distortion
+        r_distorted = r / (1 - strength * r**2 + 0.001)
+
+    # Calculate scale factor
+    scale = np.where(r > 0, r_distorted / r, 1)
+
+    # Apply zoom correction to hide black edges
+    if zoom_correction and strength > 0:
+        zoom = 1 + strength * 0.5
+        scale = scale / zoom
+
+    # Calculate new coordinates
+    new_x = (x_norm * scale * (w / 2) + cx).astype(np.float32)
+    new_y = (y_norm * scale * (h / 2) + cy).astype(np.float32)
+
+    # Remap
+    result = cv2.remap(
+        frame, new_x, new_y,
+        cv2.INTER_LINEAR,
+        borderMode=cv2.BORDER_REFLECT
+    )
+
+    return result, state

effects/fisheye.sexp

@@ -0,0 +1,20 @@
+;; Fisheye effect - barrel/pincushion distortion
+;; Usage: python3 plan.py effects/fisheye.sexp -p strength=0.5 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   strength: distortion amount (-1.0 to 1.0, default: 0.5)
+;;             positive = barrel (bulge), negative = pincushion
+
+(recipe "fisheye"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect fisheye :path "sexp_effects/effects/fisheye.sexp")
+
+  ;; Default parameter (overridden by -p strength=N)
+  (def strength 0.5)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect fisheye :strength strength)))
+  result)

effects/flip.py

@@ -0,0 +1,64 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy"]
+# ///
+"""
+@effect flip
+@version 1.0.0
+@author artdag
+
+@description
+Flips the frame horizontally and/or vertically.
+Can be used for mirror effects or beat-triggered flips.
+
+@param horizontal bool
+  @default false
+  Flip horizontally (left-right mirror).
+
+@param vertical bool
+  @default false
+  Flip vertically (top-bottom mirror).
+
+@example
+  (effect flip :horizontal true)
+
+@example
+  (effect flip :vertical true)
+
+@example
+  (effect flip :horizontal true :vertical true)  ; 180 degree rotation
+"""
+
+import numpy as np
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Flip a video frame horizontally and/or vertically.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - horizontal: flip left-right (default False)
+            - vertical: flip top-bottom (default False)
+        state: Persistent state dict (unused)
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    horizontal = params.get("horizontal", False)
+    vertical = params.get("vertical", False)
+
+    result = frame
+
+    if horizontal:
+        result = np.flip(result, axis=1)
+
+    if vertical:
+        result = np.flip(result, axis=0)
+
+    # Ensure contiguous array after flips
+    if horizontal or vertical:
+        result = np.ascontiguousarray(result)
+
+    return result, state

effects/flip.sexp

@@ -0,0 +1,19 @@
+;; Flip effect - flip image horizontally or vertically
+;; Usage: python3 plan.py effects/flip.sexp -p direction=horizontal | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   direction: flip axis ("horizontal" or "vertical", default: "horizontal")
+
+(recipe "flip"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect flip :path "sexp_effects/effects/flip.sexp")
+
+  ;; Default parameter (overridden by -p direction=horizontal|vertical)
+  (def direction "horizontal")
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect flip :direction direction)))
+  result)

effects/grayscale.sexp

@@ -0,0 +1,14 @@
+;; Grayscale effect - converts to black and white
+;; Usage: python3 plan.py effects/grayscale.sexp | python3 execute.py - -d . -o output.mp4
+;; No parameters
+
+(recipe "grayscale"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect grayscale :path "sexp_effects/effects/grayscale.sexp")
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect grayscale)))
+  result)

effects/hue_shift.py

@@ -0,0 +1,59 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy", "opencv-python"]
+# ///
+"""
+@effect hue_shift
+@version 1.0.0
+@author artdag
+
+@description
+Rotates the hue of all colors by a specified amount (0-360 degrees).
+Creates rainbow cycling effects when animated over time.
+
+@param shift float
+  @range 0 360
+  @default 0
+  Hue rotation in degrees. 0/360 = unchanged, 180 = complementary colors.
+
+@example
+  (effect hue_shift :shift 180)  ; complementary colors
+
+@example
+  ;; Rainbow cycling based on time (use with frame counter in state)
+  (effect hue_shift :shift (bind beat_position :range [0 360]))
+"""
+
+import numpy as np
+import cv2
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Shift hue of a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - shift: hue rotation in degrees (default 0)
+        state: Persistent state dict (unused)
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    shift = params.get("shift", 0)
+
+    if shift == 0:
+        return frame, state
+
+    # Convert RGB to HSV (OpenCV uses H: 0-179, S: 0-255, V: 0-255)
+    hsv = cv2.cvtColor(frame, cv2.COLOR_RGB2HSV)
+
+    # Shift hue (OpenCV hue is 0-179, so divide by 2)
+    hue_shift = int((shift % 360) / 2)
+    hsv[:, :, 0] = (hsv[:, :, 0].astype(np.int16) + hue_shift) % 180
+
+    # Convert back to RGB
+    result = cv2.cvtColor(hsv, cv2.COLOR_HSV2RGB)
+
+    return result, state

effects/hue_shift.sexp

@@ -0,0 +1,20 @@
+;; Hue shift effect - rotate colors around color wheel
+;; Usage: python3 plan.py effects/hue_shift.sexp -p degrees=90 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   degrees: hue rotation in degrees (0 to 360, default: 90)
+;;            90 = quarter rotation, 180 = complementary colors
+
+(recipe "hue_shift"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect hue_shift :path "sexp_effects/effects/hue_shift.sexp")
+
+  ;; Default parameter (overridden by -p degrees=N)
+  (def degrees 90)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect hue_shift :degrees degrees)))
+  result)

effects/invert.py

@@ -0,0 +1,62 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy"]
+# ///
+"""
+@effect invert
+@version 1.0.0
+@author artdag
+
+@description
+Inverts the colors of each frame. Can be partial (blended with original)
+based on intensity parameter. Useful for beat-reactive flashing effects.
+
+@param intensity float
+  @range 0 100
+  @default 100
+  Intensity of the inversion effect (0 = original, 100 = fully inverted).
+  Bind to audio analysis for reactive effects.
+
+@example
+  (effect invert)
+
+@example
+  (effect invert :intensity 50)
+
+@example
+  ;; Beat-reactive inversion
+  (effect invert :intensity (bind bass :range [0 100] :transform sqrt))
+"""
+
+import numpy as np
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Invert colors of a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - intensity: 0-100, how much to invert (default 100)
+        state: Persistent state dict (unused for this effect)
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    intensity = params.get("intensity", 100)
+
+    # Normalize intensity to 0-1
+    t = intensity / 100.0
+
+    if t <= 0:
+        return frame, state
+
+    if t >= 1:
+        return (255 - frame), state
+
+    # Partial inversion: blend between original and inverted
+    inverted = 255 - frame
+    result = (frame * (1 - t) + inverted * t).astype(np.uint8)
+
+    return result, state

effects/invert.sexp

@@ -0,0 +1,14 @@
+;; Invert effect - inverts all colors
+;; Usage: python3 plan.py effects/invert.sexp | python3 execute.py - -d . -o output.mp4
+;; No parameters
+
+(recipe "invert"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect invert :path "sexp_effects/effects/invert.sexp")
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect invert)))
+  result)

effects/kaleidoscope.py

@@ -0,0 +1,137 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy", "opencv-python"]
+# ///
+"""
+@effect kaleidoscope
+@version 1.0.0
+@author artdag
+
+@description
+Kaleidoscope effect. Creates mesmerizing mandala-like patterns by
+dividing the frame into pie-slice segments and reflecting them.
+Great for psychedelic visuals.
+
+@param segments int
+  @range 3 16
+  @default 6
+  Number of symmetry segments.
+
+@param rotation float
+  @range 0 360
+  @default 0
+  Base rotation angle in degrees.
+
+@param rotation_speed float
+  @range -180 180
+  @default 0
+  Continuous rotation speed in degrees/second.
+
+@param center_x float
+  @range 0 1
+  @default 0.5
+  Center X position (0-1).
+
+@param center_y float
+  @range 0 1
+  @default 0.5
+  Center Y position (0-1).
+
+@param zoom float
+  @range 0.5 3.0
+  @default 1.0
+  Zoom factor for the source region.
+
+@state cumulative_rotation float
+  Tracks rotation over time.
+
+@example
+  (effect kaleidoscope :segments 8 :rotation_speed 30)
+
+@example
+  ;; Beat-reactive segments
+  (effect kaleidoscope :segments (bind bass :range [4 12]) :zoom 1.5)
+"""
+
+import numpy as np
+import cv2
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply kaleidoscope effect to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - segments: number of segments 3-16 (default 6)
+            - rotation: base rotation degrees (default 0)
+            - rotation_speed: degrees per second (default 0)
+            - center_x: center X 0-1 (default 0.5)
+            - center_y: center Y 0-1 (default 0.5)
+            - zoom: zoom factor 0.5-3 (default 1.0)
+        state: Persistent state dict
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    segments = max(3, min(int(params.get("segments", 6)), 16))
+    rotation = params.get("rotation", 0)
+    rotation_speed = params.get("rotation_speed", 0)
+    center_x = params.get("center_x", 0.5)
+    center_y = params.get("center_y", 0.5)
+    zoom = max(0.5, min(params.get("zoom", 1.0), 3.0))
+
+    # Get time for animation
+    t = params.get("_time", 0)
+
+    if state is None:
+        state = {}
+
+    h, w = frame.shape[:2]
+
+    # Calculate center in pixels
+    cx = int(w * center_x)
+    cy = int(h * center_y)
+
+    # Total rotation including time-based animation
+    total_rotation = rotation + rotation_speed * t
+
+    # Calculate the angle per segment
+    segment_angle = 2 * np.pi / segments
+
+    # Create coordinate maps
+    y_coords, x_coords = np.mgrid[0:h, 0:w].astype(np.float32)
+
+    # Translate to center
+    x_centered = x_coords - cx
+    y_centered = y_coords - cy
+
+    # Convert to polar coordinates
+    r = np.sqrt(x_centered**2 + y_centered**2)
+    theta = np.arctan2(y_centered, x_centered)
+
+    # Apply rotation
+    theta = theta - np.deg2rad(total_rotation)
+
+    # Fold angle into first segment and mirror
+    theta_normalized = theta % (2 * np.pi)
+    segment_idx = (theta_normalized / segment_angle).astype(int)
+    theta_in_segment = theta_normalized - segment_idx * segment_angle
+
+    # Mirror alternating segments
+    mirror_mask = (segment_idx % 2) == 1
+    theta_in_segment = np.where(mirror_mask, segment_angle - theta_in_segment, theta_in_segment)
+
+    # Apply zoom
+    r = r / zoom
+
+    # Convert back to Cartesian (source coordinates)
+    src_x = (r * np.cos(theta_in_segment) + cx).astype(np.float32)
+    src_y = (r * np.sin(theta_in_segment) + cy).astype(np.float32)
+
+    # Remap
+    result = cv2.remap(frame, src_x, src_y,
+                      cv2.INTER_LINEAR, borderMode=cv2.BORDER_REFLECT)
+
+    return result, state

effects/kaleidoscope.sexp

@@ -0,0 +1,21 @@
+;; Kaleidoscope effect - radial mirror segments
+;; Usage: python3 plan.py effects/kaleidoscope.sexp -p segments=6 -p rotation_speed=30 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   segments: number of mirror segments (2 to 16, default: 6)
+;;   rotation_speed: rotation in degrees per second (0 to 180, default: 30)
+
+(recipe "kaleidoscope"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect kaleidoscope :path "sexp_effects/effects/kaleidoscope.sexp")
+
+  ;; Default parameters (overridden by -p segments=N -p rotation_speed=N)
+  (def segments 6)
+  (def rotation_speed 30)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect kaleidoscope :segments segments :rotation_speed rotation_speed)))
+  result)

effects/mirror.py

@@ -0,0 +1,86 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy"]
+# ///
+"""
+@effect mirror
+@version 1.0.0
+@author artdag
+
+@description
+Creates mirror/reflection effects by duplicating and flipping portions
+of the frame. Can create kaleidoscope-like symmetry effects.
+
+@param mode string
+  @enum left right top bottom quad
+  @default left
+  Mirror mode:
+  - left: Left half mirrored to right
+  - right: Right half mirrored to left
+  - top: Top half mirrored to bottom
+  - bottom: Bottom half mirrored to top
+  - quad: Four-way symmetry (kaleidoscope)
+
+@example
+  (effect mirror :mode "left")
+
+@example
+  (effect mirror :mode "quad")  ; kaleidoscope effect
+"""
+
+import numpy as np
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Create mirror/reflection effects.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - mode: mirror mode (default "left")
+        state: Persistent state dict (unused)
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    mode = params.get("mode", "left")
+
+    h, w = frame.shape[:2]
+    result = frame.copy()
+
+    if mode == "left":
+        # Mirror left half to right
+        half = w // 2
+        result[:, half:] = np.flip(result[:, :half], axis=1)[:, :w - half]
+
+    elif mode == "right":
+        # Mirror right half to left
+        half = w // 2
+        result[:, :half] = np.flip(result[:, half:], axis=1)[:, :half]
+
+    elif mode == "top":
+        # Mirror top half to bottom
+        half = h // 2
+        result[half:, :] = np.flip(result[:half, :], axis=0)[:h - half, :]
+
+    elif mode == "bottom":
+        # Mirror bottom half to top
+        half = h // 2
+        result[:half, :] = np.flip(result[half:, :], axis=0)[:half, :]
+
+    elif mode == "quad":
+        # Four-way symmetry: use top-left quadrant
+        half_h = h // 2
+        half_w = w // 2
+
+        # Get top-left quadrant
+        tl = result[:half_h, :half_w]
+
+        # Mirror to top-right
+        result[:half_h, half_w:] = np.flip(tl, axis=1)[:, :w - half_w]
+
+        # Mirror top half to bottom
+        result[half_h:, :] = np.flip(result[:half_h, :], axis=0)[:h - half_h, :]
+
+    return np.ascontiguousarray(result), state

effects/mirror.sexp

@@ -0,0 +1,19 @@
+;; Mirror effect - reflect image
+;; Usage: python3 plan.py effects/mirror.sexp -p direction=horizontal | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   direction: mirror axis ("horizontal" or "vertical", default: "horizontal")
+
+(recipe "mirror"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect mirror :path "sexp_effects/effects/mirror.sexp")
+
+  ;; Default parameter (overridden by -p direction=horizontal|vertical)
+  (def direction "horizontal")
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect mirror :direction direction)))
+  result)

effects/motion_blur.py

@@ -0,0 +1,122 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy", "opencv-python"]
+# ///
+"""
+@effect motion_blur
+@version 1.0.0
+@author artdag
+
+@description
+Motion blur effect. Creates directional blur simulating camera or
+subject motion. Great for speed effects.
+
+@param amount int
+  @range 1 100
+  @default 20
+  Blur length in pixels.
+
+@param angle float
+  @range 0 360
+  @default 0
+  Blur direction in degrees (0 = horizontal right).
+
+@param zoom bool
+  @default false
+  Radial zoom blur instead of directional.
+
+@param zoom_center_x float
+  @range 0 1
+  @default 0.5
+  Zoom blur center X.
+
+@param zoom_center_y float
+  @range 0 1
+  @default 0.5
+  Zoom blur center Y.
+
+@example
+  (effect motion_blur :amount 30 :angle 45)
+
+@example
+  ;; Zoom blur
+  (effect motion_blur :amount 20 :zoom true)
+"""
+
+import numpy as np
+import cv2
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply motion blur effect to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - amount: blur length (default 20)
+            - angle: blur direction (default 0)
+            - zoom: radial zoom blur (default False)
+            - zoom_center_x/y: zoom center (default 0.5)
+        state: Persistent state dict
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    amount = max(1, int(params.get("amount", 20)))
+    angle = params.get("angle", 0)
+    zoom = params.get("zoom", False)
+    zoom_center_x = params.get("zoom_center_x", 0.5)
+    zoom_center_y = params.get("zoom_center_y", 0.5)
+
+    if state is None:
+        state = {}
+
+    if amount <= 1:
+        return frame, state
+
+    h, w = frame.shape[:2]
+
+    if zoom:
+        # Radial zoom blur
+        cx, cy = int(w * zoom_center_x), int(h * zoom_center_y)
+
+        # Accumulate multiple scaled versions
+        result = np.zeros_like(frame, dtype=np.float32)
+        num_samples = min(amount, 20)
+
+        for i in range(num_samples):
+            scale = 1.0 + (i / num_samples) * (amount / 100.0)
+            M = cv2.getRotationMatrix2D((cx, cy), 0, scale)
+            scaled = cv2.warpAffine(frame, M, (w, h), borderMode=cv2.BORDER_REFLECT)
+            result += scaled.astype(np.float32) / num_samples
+
+        return result.astype(np.uint8), state
+    else:
+        # Directional motion blur using a line kernel
+        angle_rad = np.deg2rad(angle)
+        dx = np.cos(angle_rad)
+        dy = np.sin(angle_rad)
+
+        # Create motion blur kernel
+        kernel_size = amount
+        kernel = np.zeros((kernel_size, kernel_size), dtype=np.float32)
+
+        # Draw a line in the kernel
+        cx, cy = kernel_size // 2, kernel_size // 2
+        for i in range(kernel_size):
+            t = (i - cx) / max(1, cx)
+            x = int(cx + t * cx * dx)
+            y = int(cy + t * cy * dy)
+            if 0 <= x < kernel_size and 0 <= y < kernel_size:
+                kernel[y, x] = 1
+
+        # Normalize kernel
+        kernel_sum = kernel.sum()
+        if kernel_sum > 0:
+            kernel /= kernel_sum
+
+        # Apply kernel
+        result = cv2.filter2D(frame, -1, kernel)
+
+        return result, state

effects/neon_glow.py

@@ -0,0 +1,130 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy", "opencv-python"]
+# ///
+"""
+@effect neon_glow
+@version 1.0.0
+@author artdag
+
+@description
+Neon edge glow effect. Detects edges and applies a glowing colored outline.
+Great for cyberpunk/synthwave aesthetics synced to music.
+
+@param glow_radius float
+  @range 0 50
+  @default 15
+  Blur radius for the glow. Bind to bass for pulsing glow.
+
+@param glow_intensity float
+  @range 0.5 5
+  @default 2.0
+  Brightness multiplier for the glow.
+
+@param edge_low float
+  @range 10 200
+  @default 50
+  Lower threshold for edge detection.
+
+@param edge_high float
+  @range 50 300
+  @default 150
+  Upper threshold for edge detection.
+
+@param color_r int
+  @range 0 255
+  @default 0
+  Red component of glow color.
+
+@param color_g int
+  @range 0 255
+  @default 255
+  Green component of glow color.
+
+@param color_b int
+  @range 0 255
+  @default 255
+  Blue component of glow color.
+
+@param background float
+  @range 0 1
+  @default 0.3
+  How much of the original image shows through (0 = glow only).
+
+@example
+  (effect neon_glow :glow_radius 20 :color_r 255 :color_g 0 :color_b 255)
+
+@example
+  ;; Pulsing cyan glow on bass
+  (effect neon_glow :glow_radius (bind bass :range [5 30] :transform sqrt))
+"""
+
+import numpy as np
+import cv2
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply neon glow effect to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - glow_radius: blur radius (default 15)
+            - glow_intensity: brightness (default 2.0)
+            - edge_low: canny low threshold (default 50)
+            - edge_high: canny high threshold (default 150)
+            - color_r/g/b: glow color (default cyan 0,255,255)
+            - background: original visibility (default 0.3)
+        state: Persistent state dict (unused)
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    glow_radius = int(params.get("glow_radius", 15))
+    glow_intensity = params.get("glow_intensity", 2.0)
+    edge_low = int(params.get("edge_low", 50))
+    edge_high = int(params.get("edge_high", 150))
+    color_r = int(params.get("color_r", 0))
+    color_g = int(params.get("color_g", 255))
+    color_b = int(params.get("color_b", 255))
+    background = params.get("background", 0.3)
+
+    h, w = frame.shape[:2]
+    color = np.array([color_r, color_g, color_b], dtype=np.float32)
+
+    # Edge detection
+    gray = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY)
+    blurred = cv2.GaussianBlur(gray, (5, 5), 0)
+    edges = cv2.Canny(blurred, edge_low, edge_high)
+
+    # Create colored edge image
+    glow_base = np.zeros((h, w, 3), dtype=np.float32)
+    for c in range(3):
+        glow_base[:, :, c] = edges.astype(np.float32) * (color[c] / 255.0)
+
+    # Apply blur for glow
+    if glow_radius > 0:
+        ksize = glow_radius * 2 + 1
+        glow = cv2.GaussianBlur(glow_base, (ksize, ksize), 0)
+    else:
+        glow = glow_base
+
+    # Intensify
+    glow = glow * glow_intensity
+
+    # Add sharp edges on top
+    edge_layer = np.zeros((h, w, 3), dtype=np.float32)
+    for c in range(3):
+        edge_layer[:, :, c] = edges.astype(np.float32) * (color[c] / 255.0) * 255
+    glow = np.maximum(glow, edge_layer)
+
+    # Blend with original
+    if background > 0:
+        a = frame.astype(np.float32) / 255.0 * background
+        b = glow / 255.0
+        result = (1 - (1 - a) * (1 - b)) * 255  # Screen blend
+    else:
+        result = glow
+
+    return np.clip(result, 0, 255).astype(np.uint8), state

effects/neon_glow.sexp

@@ -0,0 +1,21 @@
+;; Neon glow effect - glowing edges on dark background
+;; Usage: python3 plan.py effects/neon_glow.sexp -p glow_radius=20 -p glow_intensity=2 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   glow_radius: glow spread in pixels (5 to 50, default: 20)
+;;   glow_intensity: glow brightness (0.5 to 5, default: 2)
+
+(recipe "neon_glow"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect neon_glow :path "sexp_effects/effects/neon_glow.sexp")
+
+  ;; Default parameters (overridden by -p glow_radius=N -p glow_intensity=N)
+  (def glow_radius 20)
+  (def glow_intensity 2)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect neon_glow :glow_radius glow_radius :glow_intensity glow_intensity)))
+  result)

effects/noise.py

@@ -0,0 +1,137 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy"]
+# ///
+"""
+@effect noise
+@version 1.0.0
+@author artdag
+
+@description
+Noise effect. Adds various types of noise to the image including
+static, gaussian, salt & pepper, and more.
+
+@param intensity float
+  @range 0 1
+  @default 0.2
+  Noise intensity.
+
+@param mode string
+  @enum gaussian uniform salt_pepper scanline
+  @default gaussian
+  Type of noise:
+  - gaussian: smooth normal distribution
+  - uniform: flat random noise
+  - salt_pepper: random black/white pixels
+  - scanline: horizontal line noise
+
+@param colored bool
+  @default false
+  Use colored noise instead of monochrome.
+
+@param animate bool
+  @default true
+  Different noise each frame.
+
+@param seed int
+  @default 42
+  Random seed for reproducible noise.
+
+@state rng DeterministicRNG
+  Random number generator.
+
+@example
+  (effect noise :intensity 0.3 :mode "gaussian")
+
+@example
+  ;; Static TV noise
+  (effect noise :intensity 0.5 :mode "uniform" :animate true)
+"""
+
+import numpy as np
+from pathlib import Path
+import sys
+
+# Import DeterministicRNG from same directory
+_effects_dir = Path(__file__).parent
+if str(_effects_dir) not in sys.path:
+    sys.path.insert(0, str(_effects_dir))
+from random import DeterministicRNG
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply noise effect to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+        state: Persistent state dict
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    intensity = params.get("intensity", 0.2)
+    mode = params.get("mode", "gaussian")
+    colored = params.get("colored", False)
+    animate = params.get("animate", True)
+    seed = int(params.get("seed", 42))
+
+    if state is None:
+        state = {}
+
+    if intensity <= 0:
+        return frame, state
+
+    # Initialize RNG
+    if "rng" not in state:
+        state["rng"] = DeterministicRNG(seed)
+    rng = state["rng"]
+
+    h, w = frame.shape[:2]
+    result = frame.astype(np.float32)
+
+    if mode == "gaussian":
+        # Gaussian noise
+        if colored:
+            noise = np.array([[[rng.gaussian(0, intensity * 50) for _ in range(3)]
+                              for _ in range(w)]
+                             for _ in range(h)])
+        else:
+            noise_2d = np.array([[rng.gaussian(0, intensity * 50)
+                                 for _ in range(w)]
+                                for _ in range(h)])
+            noise = np.stack([noise_2d, noise_2d, noise_2d], axis=-1)
+        result = result + noise
+
+    elif mode == "uniform":
+        # Uniform random noise
+        if colored:
+            noise = np.array([[[rng.uniform(-intensity * 100, intensity * 100) for _ in range(3)]
+                              for _ in range(w)]
+                             for _ in range(h)])
+        else:
+            noise_2d = np.array([[rng.uniform(-intensity * 100, intensity * 100)
+                                 for _ in range(w)]
+                                for _ in range(h)])
+            noise = np.stack([noise_2d, noise_2d, noise_2d], axis=-1)
+        result = result + noise
+
+    elif mode == "salt_pepper":
+        # Salt and pepper noise
+        for y in range(h):
+            for x in range(w):
+                if rng.uniform() < intensity * 0.1:
+                    if rng.uniform() < 0.5:
+                        result[y, x] = [0, 0, 0]
+                    else:
+                        result[y, x] = [255, 255, 255]
+
+    elif mode == "scanline":
+        # Horizontal scanline noise
+        for y in range(h):
+            if rng.uniform() < intensity * 0.2:
+                noise_val = rng.uniform(-intensity * 100, intensity * 100)
+                result[y] = result[y] + noise_val
+
+    return np.clip(result, 0, 255).astype(np.uint8), state

effects/noise.sexp

@@ -0,0 +1,19 @@
+;; Noise effect - random pixel noise
+;; Usage: python3 plan.py effects/noise.sexp -p amount=40 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   amount: noise intensity (5 to 100, default: 40)
+
+(recipe "noise"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect noise :path "sexp_effects/effects/noise.sexp")
+
+  ;; Default parameter (overridden by -p amount=N)
+  (def amount 40)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect noise :amount amount)))
+  result)

effects/outline.py

@@ -0,0 +1,111 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy", "opencv-python"]
+# ///
+"""
+@effect outline
+@version 1.0.0
+@author artdag
+
+@description
+Outline / Toon Edges effect. Extracts and displays edges as outlines,
+optionally with fill. Great for cartoon/comic book aesthetics.
+
+@param edge_thickness int
+  @range 1 10
+  @default 2
+  Thickness of outlines in pixels.
+
+@param threshold float
+  @range 20 300
+  @default 100
+  Edge detection sensitivity.
+
+@param outline_color list
+  @default [0, 0, 0]
+  RGB color for outlines (default black).
+
+@param fill_mode string
+  @enum original solid transparent
+  @default original
+  What to show in non-edge areas:
+  - original: keep source image
+  - solid: fill with solid color
+  - transparent: black background
+
+@param fill_color list
+  @default [255, 255, 255]
+  RGB color for solid fill mode.
+
+@example
+  (effect outline :edge_thickness 3 :threshold 80)
+
+@example
+  ;; White outlines on black
+  (effect outline :outline_color [255 255 255] :fill_mode "transparent")
+"""
+
+import numpy as np
+import cv2
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply outline effect to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - edge_thickness: outline width (default 2)
+            - threshold: edge sensitivity (default 100)
+            - outline_color: RGB tuple (default [0,0,0])
+            - fill_mode: original/solid/transparent (default original)
+            - fill_color: RGB tuple for solid fill (default [255,255,255])
+        state: Persistent state dict
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    thickness = max(1, min(int(params.get("edge_thickness", 2)), 10))
+    threshold = params.get("threshold", 100)
+    outline_color = params.get("outline_color", [0, 0, 0])
+    fill_mode = params.get("fill_mode", "original")
+    fill_color = params.get("fill_color", [255, 255, 255])
+
+    if state is None:
+        state = {}
+
+    h, w = frame.shape[:2]
+
+    # Convert to grayscale
+    gray = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY)
+
+    # Apply edge detection
+    edges = cv2.Canny(gray, int(threshold * 0.5), int(threshold))
+
+    # Dilate edges for thickness
+    if thickness > 1:
+        kernel = np.ones((thickness, thickness), np.uint8)
+        edges = cv2.dilate(edges, kernel, iterations=1)
+
+    # Create result based on fill mode
+    if fill_mode == "original":
+        result = frame.copy()
+    elif fill_mode == "solid":
+        if isinstance(fill_color, (list, tuple)) and len(fill_color) >= 3:
+            result = np.full((h, w, 3), fill_color[:3], dtype=np.uint8)
+        else:
+            result = np.full((h, w, 3), 255, dtype=np.uint8)
+    else:  # transparent/none
+        result = np.zeros((h, w, 3), dtype=np.uint8)
+
+    # Apply outline color where edges exist
+    if isinstance(outline_color, (list, tuple)) and len(outline_color) >= 3:
+        color = np.array(outline_color[:3], dtype=np.uint8)
+    else:
+        color = np.array([0, 0, 0], dtype=np.uint8)
+
+    edge_mask = edges > 0
+    result[edge_mask] = color
+
+    return result, state

effects/outline.sexp

@@ -0,0 +1,19 @@
+;; Outline effect - draw edges as lines
+;; Usage: python3 plan.py effects/outline.sexp -p thickness=2 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   thickness: outline width in pixels (1 to 5, default: 2)
+
+(recipe "outline"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect outline :path "sexp_effects/effects/outline.sexp")
+
+  ;; Default parameter (overridden by -p thickness=N)
+  (def thickness 2)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect outline :thickness thickness)))
+  result)

effects/pixelate.py

@@ -0,0 +1,72 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy", "opencv-python"]
+# ///
+"""
+@effect pixelate
+@version 1.0.0
+@author artdag
+
+@description
+Pixelate effect. Reduces resolution to create blocky, retro pixel art
+look. Great for 8-bit aesthetics.
+
+@param block_size int
+  @range 2 64
+  @default 8
+  Size of pixel blocks. Larger = more pixelated.
+
+@param maintain_edges bool
+  @default false
+  Try to preserve edges while pixelating.
+
+@example
+  (effect pixelate :block_size 16)
+
+@example
+  ;; Beat-reactive pixelation
+  (effect pixelate :block_size (bind bass :range [4 32]))
+"""
+
+import numpy as np
+import cv2
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply pixelate effect to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - block_size: pixel block size (default 8)
+            - maintain_edges: preserve edges (default False)
+        state: Persistent state dict
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    block_size = max(2, min(int(params.get("block_size", 8)), 64))
+    maintain_edges = params.get("maintain_edges", False)
+
+    if state is None:
+        state = {}
+
+    h, w = frame.shape[:2]
+
+    # Scale down then up to create pixelation
+    small_h = max(1, h // block_size)
+    small_w = max(1, w // block_size)
+
+    small = cv2.resize(frame, (small_w, small_h), interpolation=cv2.INTER_AREA)
+    result = cv2.resize(small, (w, h), interpolation=cv2.INTER_NEAREST)
+
+    if maintain_edges:
+        # Detect edges in original and overlay
+        gray = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY)
+        edges = cv2.Canny(gray, 50, 150)
+        edges_dilated = cv2.dilate(edges, np.ones((2, 2), np.uint8))
+        edge_mask = edges_dilated > 0
+        result[edge_mask] = frame[edge_mask]
+
+    return result, state

effects/pixelate.sexp

@@ -0,0 +1,20 @@
+;; Pixelate effect - reduce resolution with blocky pixels
+;; Usage: python3 plan.py effects/pixelate.sexp -p block_size=16 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   block_size: pixel block size (2 to 64, default: 16)
+;;               higher = more pixelated
+
+(recipe "pixelate"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect pixelate :path "sexp_effects/effects/pixelate.sexp")
+
+  ;; Default parameter (overridden by -p block_size=N)
+  (def block_size 16)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect pixelate :block_size block_size)))
+  result)

effects/pixelsort.py

@@ -0,0 +1,152 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy", "opencv-python"]
+# ///
+"""
+@effect pixelsort
+@version 1.0.0
+@author artdag
+
+@description
+Pixel sorting glitch art effect. Sorts pixels within rows by brightness,
+hue, or other properties. Creates distinctive streaked/melted aesthetics.
+
+@param sort_by string
+  @enum lightness hue saturation red green blue
+  @default lightness
+  Property to sort pixels by.
+
+@param threshold_low float
+  @range 0 255
+  @default 50
+  Pixels darker than this are not sorted.
+
+@param threshold_high float
+  @range 0 255
+  @default 200
+  Pixels brighter than this are not sorted.
+
+@param angle float
+  @range 0 180
+  @default 0
+  Sort direction: 0 = horizontal, 90 = vertical.
+
+@param reverse bool
+  @default false
+  Reverse the sort order.
+
+@example
+  (effect pixelsort)
+
+@example
+  ;; Vertical pixel sort
+  (effect pixelsort :angle 90)
+
+@example
+  ;; Sort by hue for rainbow streaks
+  (effect pixelsort :sort_by "hue" :threshold_low 20 :threshold_high 240)
+"""
+
+import numpy as np
+import cv2
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply pixel sorting to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - sort_by: property to sort by (default "lightness")
+            - threshold_low: min brightness to sort (default 50)
+            - threshold_high: max brightness to sort (default 200)
+            - angle: 0 = horizontal, 90 = vertical (default 0)
+            - reverse: reverse sort order (default False)
+        state: Persistent state dict (unused)
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    sort_by = params.get("sort_by", "lightness")
+    threshold_low = params.get("threshold_low", 50)
+    threshold_high = params.get("threshold_high", 200)
+    angle = params.get("angle", 0)
+    reverse = params.get("reverse", False)
+
+    h, w = frame.shape[:2]
+
+    # Rotate for non-horizontal sorting
+    if 45 <= (angle % 180) <= 135:
+        frame = np.transpose(frame, (1, 0, 2))
+        h, w = frame.shape[:2]
+        rotated = True
+    else:
+        rotated = False
+
+    result = frame.copy()
+
+    # Get sort values
+    sort_values = _get_sort_values(frame, sort_by)
+
+    # Create mask of pixels to sort
+    mask = (sort_values >= threshold_low) & (sort_values <= threshold_high)
+
+    # Sort each row
+    for y in range(h):
+        row = result[y].copy()
+        row_mask = mask[y]
+        row_values = sort_values[y]
+
+        # Find contiguous segments to sort
+        segments = _find_segments(row_mask)
+
+        for start, end in segments:
+            if end - start > 1:
+                segment_values = row_values[start:end]
+                sort_indices = np.argsort(segment_values)
+                if reverse:
+                    sort_indices = sort_indices[::-1]
+                row[start:end] = row[start:end][sort_indices]
+
+        result[y] = row
+
+    # Rotate back if needed
+    if rotated:
+        result = np.transpose(result, (1, 0, 2))
+
+    return np.ascontiguousarray(result), state
+
+
+def _get_sort_values(frame, sort_by):
+    """Get values to sort pixels by."""
+    if sort_by == "lightness":
+        return cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY).astype(np.float32)
+    elif sort_by == "hue":
+        hsv = cv2.cvtColor(frame, cv2.COLOR_RGB2HSV)
+        return hsv[:, :, 0].astype(np.float32)
+    elif sort_by == "saturation":
+        hsv = cv2.cvtColor(frame, cv2.COLOR_RGB2HSV)
+        return hsv[:, :, 1].astype(np.float32)
+    elif sort_by == "red":
+        return frame[:, :, 0].astype(np.float32)
+    elif sort_by == "green":
+        return frame[:, :, 1].astype(np.float32)
+    elif sort_by == "blue":
+        return frame[:, :, 2].astype(np.float32)
+    return cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY).astype(np.float32)
+
+
+def _find_segments(mask):
+    """Find contiguous True segments in mask."""
+    segments = []
+    start = None
+    for i, val in enumerate(mask):
+        if val and start is None:
+            start = i
+        elif not val and start is not None:
+            segments.append((start, i))
+            start = None
+    if start is not None:
+        segments.append((start, len(mask)))
+    return segments

effects/pixelsort.sexp

@@ -0,0 +1,22 @@
+;; Pixelsort effect - glitch art pixel sorting
+;; Usage: python3 plan.py effects/pixelsort.sexp -p threshold_low=30 -p threshold_high=220 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   threshold_low: lower brightness threshold (0 to 128, default: 30)
+;;   threshold_high: upper brightness threshold (128 to 255, default: 220)
+;;                   pixels between thresholds get sorted
+
+(recipe "pixelsort"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect pixelsort :path "sexp_effects/effects/pixelsort.sexp")
+
+  ;; Default parameters (overridden by -p threshold_low=N -p threshold_high=N)
+  (def threshold_low 30)
+  (def threshold_high 220)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect pixelsort :threshold_low threshold_low :threshold_high threshold_high)))
+  result)

effects/posterize.py

@@ -0,0 +1,79 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy"]
+# ///
+"""
+@effect posterize
+@version 1.0.0
+@author artdag
+
+@description
+Posterize / Color Quantization effect. Reduces the number of colors
+to create a poster/cartoon look. Great for stylized visuals.
+
+@param levels int
+  @range 2 32
+  @default 8
+  Number of color levels per channel. Lower = more stylized.
+
+@param dither bool
+  @default false
+  Apply dithering to reduce color banding.
+
+@example
+  (effect posterize :levels 4)
+
+@example
+  ;; Beat-reactive posterization
+  (effect posterize :levels (bind bass :range [2 16]))
+"""
+
+import numpy as np
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply posterize effect to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - levels: color levels per channel (default 8)
+            - dither: apply dithering (default False)
+        state: Persistent state dict
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    levels = max(2, min(int(params.get("levels", 8)), 256))
+    dither = params.get("dither", False)
+
+    if state is None:
+        state = {}
+
+    step = 256 // levels
+
+    if dither:
+        # Floyd-Steinberg dithering
+        result = frame.astype(np.float32).copy()
+        h, w = result.shape[:2]
+
+        for y in range(h - 1):
+            for x in range(1, w - 1):
+                for c in range(3):
+                    old_val = result[y, x, c]
+                    new_val = np.round(old_val / step) * step
+                    result[y, x, c] = new_val
+                    error = old_val - new_val
+
+                    # Distribute error to neighbors
+                    result[y, x + 1, c] += error * 7 / 16
+                    result[y + 1, x - 1, c] += error * 3 / 16
+                    result[y + 1, x, c] += error * 5 / 16
+                    result[y + 1, x + 1, c] += error * 1 / 16
+
+        return np.clip(result, 0, 255).astype(np.uint8), state
+    else:
+        # Simple quantization
+        quantized = (frame // step) * step
+        return quantized.astype(np.uint8), state

effects/posterize.sexp

@@ -0,0 +1,20 @@
+;; Posterize effect - reduce color levels for poster-like look
+;; Usage: python3 plan.py effects/posterize.sexp -p levels=6 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   levels: number of color levels per channel (2 to 32, default: 6)
+;;           lower = more posterized, higher = more gradual
+
+(recipe "posterize"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect posterize :path "sexp_effects/effects/posterize.sexp")
+
+  ;; Default parameter (overridden by -p levels=N)
+  (def levels 6)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect posterize :levels levels)))
+  result)

effects/random.py

@@ -0,0 +1,217 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy"]
+# ///
+"""
+@effect random
+@version 1.0.0
+@author artdag
+
+@description
+Deterministic random number generator for use in recipes and effects.
+Given the same seed, produces the same sequence of values every time.
+
+This effect doesn't modify the frame - it provides random values that
+can be bound to other effect parameters. The random state persists
+across frames for consistent sequences.
+
+@param seed int
+  @default 42
+  Random seed for reproducibility. Same seed = same sequence.
+
+@param min float
+  @default 0
+  Minimum output value.
+
+@param max float
+  @default 1
+  Maximum output value.
+
+@param mode string
+  @enum uniform gaussian integer choice
+  @default uniform
+  Distribution type:
+  - uniform: even distribution between min and max
+  - gaussian: normal distribution (min=mean, max=stddev)
+  - integer: random integers between min and max (inclusive)
+  - choice: randomly pick from a list (use choices param)
+
+@param choices list
+  @default []
+  List of values to choose from (for mode=choice).
+
+@param step_every int
+  @default 1
+  Only generate new value every N frames (1 = every frame).
+
+@state rng RandomState
+  Numpy random state for deterministic sequence.
+
+@state frame_count int
+  Tracks frames for step_every.
+
+@state current_value float
+  Current random value (persists between steps).
+
+@example
+  ;; Random value 0-1 each frame
+  (bind (random :seed 123))
+
+@example
+  ;; Random integer 1-10, changes every 5 frames
+  (random :seed 42 :mode "integer" :min 1 :max 10 :step_every 5)
+
+@example
+  ;; Gaussian noise around 0.5
+  (random :mode "gaussian" :min 0.5 :max 0.1)
+"""
+
+import numpy as np
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Generate deterministic random values.
+
+    This effect passes through the frame unchanged but updates state
+    with random values that can be used by the recipe/executor.
+
+    Args:
+        frame: Input frame (passed through unchanged)
+        params: Effect parameters
+            - seed: random seed (default 42)
+            - min: minimum value (default 0)
+            - max: maximum value (default 1)
+            - mode: uniform/gaussian/integer/choice (default uniform)
+            - choices: list for choice mode
+            - step_every: frames between new values (default 1)
+        state: Persistent state dict
+            - rng: numpy RandomState
+            - frame_count: frame counter
+            - current_value: last generated value
+
+    Returns:
+        Tuple of (frame, state_with_random_value)
+    """
+    seed = int(params.get("seed", 42))
+    min_val = params.get("min", 0)
+    max_val = params.get("max", 1)
+    mode = params.get("mode", "uniform")
+    choices = params.get("choices", [])
+    step_every = max(1, int(params.get("step_every", 1)))
+
+    if state is None:
+        state = {}
+
+    # Initialize RNG on first call
+    if "rng" not in state:
+        state["rng"] = np.random.RandomState(seed)
+        state["frame_count"] = 0
+        state["current_value"] = None
+
+    rng = state["rng"]
+    frame_count = state["frame_count"]
+
+    # Generate new value if needed
+    if frame_count % step_every == 0 or state["current_value"] is None:
+        if mode == "uniform":
+            value = rng.uniform(min_val, max_val)
+        elif mode == "gaussian":
+            # min = mean, max = stddev
+            value = rng.normal(min_val, max_val)
+        elif mode == "integer":
+            value = rng.randint(int(min_val), int(max_val) + 1)
+        elif mode == "choice" and choices:
+            value = choices[rng.randint(0, len(choices))]
+        else:
+            value = rng.uniform(min_val, max_val)
+
+        state["current_value"] = value
+
+    state["frame_count"] = frame_count + 1
+
+    # Store value in state for recipe access
+    state["value"] = state["current_value"]
+
+    return frame, state
+
+
+# Standalone RNG class for use in other effects
+class DeterministicRNG:
+    """
+    Deterministic random number generator for use in effects.
+
+    Usage in effects:
+        from effects.random import DeterministicRNG
+
+        def process_frame(frame, params, state):
+            if "rng" not in state:
+                state["rng"] = DeterministicRNG(params.get("seed", 42))
+            rng = state["rng"]
+
+            value = rng.uniform(0, 1)
+            integer = rng.randint(0, 10)
+            choice = rng.choice(["a", "b", "c"])
+    """
+
+    def __init__(self, seed: int = 42):
+        """Initialize with seed for reproducibility."""
+        self._rng = np.random.RandomState(seed)
+        self._seed = seed
+
+    def seed(self, seed: int):
+        """Reset with new seed."""
+        self._rng = np.random.RandomState(seed)
+        self._seed = seed
+
+    def uniform(self, low: float = 0, high: float = 1) -> float:
+        """Random float in [low, high)."""
+        return self._rng.uniform(low, high)
+
+    def randint(self, low: int, high: int) -> int:
+        """Random integer in [low, high]."""
+        return self._rng.randint(low, high + 1)
+
+    def gaussian(self, mean: float = 0, stddev: float = 1) -> float:
+        """Random float from normal distribution."""
+        return self._rng.normal(mean, stddev)
+
+    def choice(self, items: list):
+        """Random choice from list."""
+        if not items:
+            return None
+        return items[self._rng.randint(0, len(items))]
+
+    def shuffle(self, items: list) -> list:
+        """Return shuffled copy of list."""
+        result = list(items)
+        self._rng.shuffle(result)
+        return result
+
+    def sample(self, items: list, n: int) -> list:
+        """Random sample of n items without replacement."""
+        if n >= len(items):
+            return self.shuffle(items)
+        indices = self._rng.choice(len(items), n, replace=False)
+        return [items[i] for i in indices]
+
+    def weighted_choice(self, items: list, weights: list):
+        """Random choice with weights."""
+        if not items or not weights:
+            return None
+        weights = np.array(weights, dtype=float)
+        weights /= weights.sum()
+        idx = self._rng.choice(len(items), p=weights)
+        return items[idx]
+
+    @property
+    def state(self) -> dict:
+        """Get RNG state for serialization."""
+        return {"seed": self._seed, "state": self._rng.get_state()}
+
+    @classmethod
+    def from_state(cls, state: dict) -> 'DeterministicRNG':
+        """Restore RNG from serialized state."""
+        rng = cls(state["seed"])
+        rng._rng.set_state(state["state"])
+        return rng

effects/rgb_split.py

@@ -0,0 +1,106 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy", "opencv-python"]
+# ///
+"""
+@effect rgb_split
+@version 1.0.0
+@author artdag
+
+@description
+Chromatic aberration / RGB channel separation. Offsets red and blue channels
+in different directions, creating color fringing. Classic glitch aesthetic.
+
+@param amount float
+  @range 0 50
+  @default 10
+  Offset amount in pixels. Bind to bass for punchy glitch effect.
+
+@param angle float
+  @range 0 360
+  @default 0
+  Direction of split in degrees. 0 = horizontal, 90 = vertical.
+
+@param red_offset float
+  @range -50 50
+  @default 0
+  Override: specific red channel X offset (ignores amount/angle if set).
+
+@param blue_offset float
+  @range -50 50
+  @default 0
+  Override: specific blue channel X offset (ignores amount/angle if set).
+
+@example
+  (effect rgb_split :amount 15)
+
+@example
+  ;; Bass-reactive chromatic aberration
+  (effect rgb_split :amount (bind bass :range [0 30] :transform sqrt))
+
+@example
+  ;; Vertical split
+  (effect rgb_split :amount 20 :angle 90)
+"""
+
+import numpy as np
+import cv2
+import math
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply RGB channel split to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - amount: offset in pixels (default 10)
+            - angle: split direction in degrees (default 0)
+            - red_offset: override red X offset
+            - blue_offset: override blue X offset
+        state: Persistent state dict (unused)
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    amount = params.get("amount", 10)
+    angle = params.get("angle", 0)
+    red_override = params.get("red_offset")
+    blue_override = params.get("blue_offset")
+
+    # Calculate offsets
+    if red_override is not None or blue_override is not None:
+        # Use explicit offsets
+        r_x = int(red_override or 0)
+        r_y = 0
+        b_x = int(blue_override or 0)
+        b_y = 0
+    else:
+        # Calculate from amount and angle
+        angle_rad = math.radians(angle)
+        r_x = int(amount * math.cos(angle_rad))
+        r_y = int(amount * math.sin(angle_rad))
+        b_x = -r_x  # Blue goes opposite direction
+        b_y = -r_y
+
+    if r_x == 0 and r_y == 0 and b_x == 0 and b_y == 0:
+        return frame, state
+
+    h, w = frame.shape[:2]
+
+    # Split channels
+    r, g, b = frame[:, :, 0], frame[:, :, 1], frame[:, :, 2]
+
+    # Create translation matrices
+    M_r = np.float32([[1, 0, r_x], [0, 1, r_y]])
+    M_b = np.float32([[1, 0, b_x], [0, 1, b_y]])
+
+    # Translate red and blue channels
+    r_shifted = cv2.warpAffine(r, M_r, (w, h), borderMode=cv2.BORDER_REPLICATE)
+    b_shifted = cv2.warpAffine(b, M_b, (w, h), borderMode=cv2.BORDER_REPLICATE)
+
+    # Merge channels
+    result = np.stack([r_shifted, g, b_shifted], axis=-1)
+
+    return result, state

effects/rgb_split.sexp

@@ -0,0 +1,19 @@
+;; RGB split effect - chromatic aberration
+;; Usage: python3 plan.py effects/rgb_split.sexp -p offset_x=20 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   offset_x: horizontal color channel offset in pixels (2 to 50, default: 20)
+
+(recipe "rgb_split"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect rgb_split :path "sexp_effects/effects/rgb_split.sexp")
+
+  ;; Default parameter (overridden by -p offset_x=N)
+  (def offset_x 20)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect rgb_split :offset_x offset_x)))
+  result)

effects/ripple.sexp

@@ -0,0 +1,21 @@
+;; Ripple effect - concentric wave distortion from center
+;; Usage: python3 plan.py effects/ripple.sexp -p amplitude=20 -p frequency=6 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   amplitude: ripple strength in pixels (5 to 50, default: 20)
+;;   frequency: number of ripples (1 to 20, default: 6)
+
+(recipe "ripple"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect ripple :path "sexp_effects/effects/ripple.sexp")
+
+  ;; Default parameters (overridden by -p amplitude=N -p frequency=N)
+  (def amplitude 20)
+  (def frequency 6)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect ripple :amplitude amplitude :frequency frequency)))
+  result)

effects/rotate.py

@@ -0,0 +1,110 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy", "opencv-python"]
+# ///
+"""
+@effect rotate
+@version 1.0.0
+@author artdag
+
+@description
+Rotates the frame by a specified angle. Supports two modes:
+- Static: rotate by fixed angle
+- Continuous: rotate by speed (degrees per frame), accumulating over time
+
+The effect uses state to track cumulative rotation for smooth continuous motion.
+
+@param angle float
+  @range -360 360
+  @default 0
+  Rotation angle in degrees. Positive = counter-clockwise.
+
+@param speed float
+  @range -30 30
+  @default 0
+  Rotation speed in degrees per frame (for continuous rotation).
+  When non-zero, angle is ignored and rotation accumulates.
+
+@param auto_zoom bool
+  @default false
+  If true, automatically zooms to crop out black corners.
+
+@state cumulative_angle float
+  Tracks total rotation for continuous mode. Persists across frames.
+
+@example
+  (effect rotate :angle 45)
+
+@example
+  ;; Continuous spin at 5 degrees per frame
+  (effect rotate :speed 5)
+
+@example
+  ;; Beat-reactive rotation
+  (effect rotate :angle (bind bass :range [0 90]))
+"""
+
+import numpy as np
+import cv2
+import math
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Rotate a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - angle: rotation angle in degrees (default 0)
+            - speed: rotation speed per frame for continuous mode (default 0)
+            - auto_zoom: zoom to hide black corners (default False)
+        state: Persistent state dict
+            - cumulative_angle: total rotation for continuous mode
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    angle = params.get("angle", 0)
+    speed = params.get("speed", 0)
+    auto_zoom = params.get("auto_zoom", False)
+
+    # Initialize state
+    if state is None:
+        state = {}
+
+    # Handle continuous rotation mode
+    if speed != 0:
+        cumulative = state.get("cumulative_angle", 0)
+        cumulative += speed
+        state["cumulative_angle"] = cumulative
+        angle = cumulative
+
+    if angle == 0:
+        return frame, state
+
+    h, w = frame.shape[:2]
+    center = (w / 2, h / 2)
+
+    # Calculate zoom factor to hide black corners
+    scale = 1.0
+    if auto_zoom:
+        angle_rad = math.radians(abs(angle) % 90)
+        if w >= h:
+            scale = math.cos(angle_rad) + (w / h) * math.sin(angle_rad)
+        else:
+            scale = math.cos(angle_rad) + (h / w) * math.sin(angle_rad)
+        scale = max(1.0, scale)
+
+    # Get rotation matrix
+    rotation_matrix = cv2.getRotationMatrix2D(center, angle, scale)
+
+    # Apply rotation
+    result = cv2.warpAffine(
+        frame, rotation_matrix, (w, h),
+        flags=cv2.INTER_LINEAR,
+        borderMode=cv2.BORDER_CONSTANT,
+        borderValue=(0, 0, 0)
+    )
+
+    return result, state

effects/rotate.sexp

@@ -0,0 +1,20 @@
+;; Rotate effect - rotate image around center
+;; Usage: python3 plan.py effects/rotate.sexp -p angle=15 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   angle: rotation in degrees (-180 to 180, default: 15)
+;;          positive = clockwise
+
+(recipe "rotate"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect rotate :path "sexp_effects/effects/rotate.sexp")
+
+  ;; Default parameter (overridden by -p angle=N)
+  (def angle 15)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect rotate :angle angle)))
+  result)

effects/saturation.py

@@ -0,0 +1,61 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy", "opencv-python"]
+# ///
+"""
+@effect saturation
+@version 1.0.0
+@author artdag
+
+@description
+Adjusts color saturation. 0 = grayscale, 1 = original, 2 = oversaturated.
+Uses HSV color space for accurate saturation control.
+
+@param factor float
+  @range 0 3
+  @default 1.0
+  Saturation multiplier. 0 = grayscale, 1 = unchanged, 2 = double saturation.
+
+@example
+  (effect saturation :factor 0)  ; grayscale
+
+@example
+  (effect saturation :factor 1.5)  ; vibrant colors
+
+@example
+  ;; Desaturate on quiet parts, saturate on loud
+  (effect saturation :factor (bind energy :range [0.5 2.0]))
+"""
+
+import numpy as np
+import cv2
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Adjust saturation of a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - factor: saturation multiplier (default 1.0)
+        state: Persistent state dict (unused)
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    factor = params.get("factor", 1.0)
+
+    if factor == 1.0:
+        return frame, state
+
+    # Convert RGB to HSV
+    hsv = cv2.cvtColor(frame, cv2.COLOR_RGB2HSV).astype(np.float32)
+
+    # Scale saturation channel (index 1)
+    hsv[:, :, 1] = np.clip(hsv[:, :, 1] * factor, 0, 255)
+
+    # Convert back to RGB
+    result = cv2.cvtColor(hsv.astype(np.uint8), cv2.COLOR_HSV2RGB)
+
+    return result, state

effects/saturation.sexp

@@ -0,0 +1,20 @@
+;; Saturation effect - adjust color saturation
+;; Usage: python3 plan.py effects/saturation.sexp -p amount=2.0 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   amount: saturation multiplier (0.0 to 3.0, default: 2.0)
+;;           0 = grayscale, 1 = normal, >1 = vivid colors
+
+(recipe "saturation"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect saturation :path "sexp_effects/effects/saturation.sexp")
+
+  ;; Default parameter (overridden by -p amount=N)
+  (def amount 2.0)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect saturation :amount amount)))
+  result)

effects/scanlines.py

@@ -0,0 +1,116 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy"]
+# ///
+"""
+@effect scanlines
+@version 1.0.0
+@author artdag
+
+@description
+VHS/CRT-style scan line shift. Horizontally displaces alternating lines
+to create analog video distortion. Great for retro/glitch aesthetics.
+
+@param amplitude float
+  @range 0 100
+  @default 10
+  Maximum shift amount in pixels. Bind to bass for reactive glitch.
+
+@param frequency float
+  @range 1 100
+  @default 10
+  Lines per cycle (affects pattern density).
+
+@param randomness float
+  @range 0 1
+  @default 0.5
+  0 = regular sine pattern, 1 = fully random shifts.
+
+@param line_gap int
+  @range 1 20
+  @default 1
+  Only shift every Nth line (1 = all lines).
+
+@param seed int
+  @default 42
+  Random seed for deterministic patterns.
+
+@state rng DeterministicRNG
+  Random number generator for reproducible results.
+
+@example
+  (effect scanlines :amplitude 20)
+
+@example
+  ;; Heavy glitch on bass
+  (effect scanlines :amplitude (bind bass :range [0 50]) :randomness 0.8)
+
+@example
+  ;; Reproducible scanlines
+  (effect scanlines :amplitude 30 :randomness 0.7 :seed 999)
+"""
+
+import numpy as np
+from pathlib import Path
+import sys
+
+# Import DeterministicRNG from same directory
+_effects_dir = Path(__file__).parent
+if str(_effects_dir) not in sys.path:
+    sys.path.insert(0, str(_effects_dir))
+from random import DeterministicRNG
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply scan line shift to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - amplitude: max shift in pixels (default 10)
+            - frequency: lines per cycle (default 10)
+            - randomness: 0-1 random vs sine (default 0.5)
+            - line_gap: shift every Nth line (default 1)
+            - seed: random seed (default 42)
+        state: Persistent state dict
+            - rng: DeterministicRNG instance
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    amplitude = params.get("amplitude", 10)
+    frequency = params.get("frequency", 10) or 1
+    randomness = params.get("randomness", 0.5)
+    line_gap = max(1, int(params.get("line_gap", 1)))
+    seed = int(params.get("seed", 42))
+
+    if state is None:
+        state = {}
+
+    # Initialize RNG
+    if "rng" not in state:
+        state["rng"] = DeterministicRNG(seed)
+    rng = state["rng"]
+
+    if amplitude == 0:
+        return frame, state
+
+    h, w = frame.shape[:2]
+    result = frame.copy()
+
+    for y in range(0, h, line_gap):
+        # Calculate shift amount
+        if randomness >= 1.0:
+            shift = int(rng.uniform(-amplitude, amplitude))
+        elif randomness <= 0:
+            shift = int(amplitude * np.sin(2 * np.pi * y / frequency))
+        else:
+            sine_shift = amplitude * np.sin(2 * np.pi * y / frequency)
+            rand_shift = rng.uniform(-amplitude, amplitude)
+            shift = int(sine_shift * (1 - randomness) + rand_shift * randomness)
+
+        if shift != 0:
+            result[y] = np.roll(result[y], shift, axis=0)
+
+    return result, state

effects/scanlines.sexp

@@ -0,0 +1,21 @@
+;; Scanlines effect - horizontal line overlay
+;; Usage: python3 plan.py effects/scanlines.sexp -p spacing=3 -p intensity=0.4 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   spacing: pixels between lines (1 to 8, default: 3)
+;;   intensity: line darkness (0 to 1, default: 0.4)
+
+(recipe "scanlines"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect scanlines :path "sexp_effects/effects/scanlines.sexp")
+
+  ;; Default parameters (overridden by -p spacing=N -p intensity=N)
+  (def spacing 3)
+  (def intensity 0.4)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect scanlines :spacing spacing :intensity intensity)))
+  result)

effects/scatter.py

@@ -0,0 +1,142 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy", "scipy"]
+# ///
+"""
+@effect scatter
+@version 1.0.0
+@author artdag
+
+@description
+Scatter effect. Randomly redistributes pixels in local area creating
+a dissolving, dispersed look.
+
+@param amount float
+  @range 0 100
+  @default 10
+  Scatter radius in pixels. Bind to energy for reactive dissolve.
+
+@param randomize_per_frame bool
+  @default false
+  Different scatter pattern each frame (vs. static pattern).
+
+@param grain float
+  @range 0 1
+  @default 0
+  Add film grain to scattered result.
+
+@param seed int
+  @default 42
+  Random seed for reproducible patterns.
+
+@state rng DeterministicRNG
+  Random number generator for displacement.
+
+@state displacement_map ndarray
+  Cached displacement map for static mode.
+
+@example
+  (effect scatter :amount 20)
+
+@example
+  ;; Reactive dissolve
+  (effect scatter :amount (bind energy :range [5 50]) :randomize_per_frame true)
+"""
+
+import numpy as np
+from scipy import ndimage
+from pathlib import Path
+import sys
+
+# Import DeterministicRNG from same directory
+_effects_dir = Path(__file__).parent
+if str(_effects_dir) not in sys.path:
+    sys.path.insert(0, str(_effects_dir))
+from random import DeterministicRNG
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply scatter effect to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - amount: scatter radius (default 10)
+            - randomize_per_frame: animate pattern (default False)
+            - grain: add film grain (default 0)
+            - seed: random seed (default 42)
+        state: Persistent state dict
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    amount = int(np.clip(params.get("amount", 10), 0, 100))
+    randomize = params.get("randomize_per_frame", False)
+    grain = params.get("grain", 0)
+    seed = int(params.get("seed", 42))
+
+    if state is None:
+        state = {}
+
+    if amount < 1:
+        return frame, state
+
+    # Initialize RNG
+    if "rng" not in state:
+        state["rng"] = DeterministicRNG(seed)
+    rng = state["rng"]
+
+    h, w = frame.shape[:2]
+
+    # Generate or reuse displacement map
+    last_size = state.get("last_size")
+    if randomize or "displacement_map" not in state or last_size != (h, w):
+        # Generate new displacement map
+        displacement = np.zeros((h, w, 2), dtype=np.float32)
+        for y in range(h):
+            for x in range(w):
+                displacement[y, x, 0] = rng.uniform(-amount, amount)
+                displacement[y, x, 1] = rng.uniform(-amount, amount)
+        state["displacement_map"] = displacement
+        state["last_size"] = (h, w)
+
+    displacement_map = state["displacement_map"]
+
+    # Create coordinate grids
+    y_coords, x_coords = np.mgrid[0:h, 0:w].astype(np.float32)
+
+    # Apply displacement
+    new_y = y_coords + displacement_map[:, :, 0]
+    new_x = x_coords + displacement_map[:, :, 1]
+
+    # Clip to valid range
+    new_y = np.clip(new_y, 0, h - 1)
+    new_x = np.clip(new_x, 0, w - 1)
+
+    # Sample from displaced positions
+    result = np.zeros_like(frame)
+    for c in range(frame.shape[2] if len(frame.shape) > 2 else 1):
+        if len(frame.shape) > 2:
+            result[:, :, c] = ndimage.map_coordinates(
+                frame[:, :, c],
+                [new_y, new_x],
+                order=1,
+                mode='reflect'
+            )
+        else:
+            result = ndimage.map_coordinates(
+                frame,
+                [new_y, new_x],
+                order=1,
+                mode='reflect'
+            )
+
+    # Add grain
+    if grain > 0:
+        noise = np.array([[[rng.uniform(-grain * 20, grain * 20) for _ in range(3)]
+                          for _ in range(w)]
+                         for _ in range(h)])
+        result = np.clip(result.astype(np.float32) + noise, 0, 255).astype(np.uint8)
+
+    return result, state

effects/sepia.sexp

@@ -0,0 +1,14 @@
+;; Sepia effect - vintage brown tone
+;; Usage: python3 plan.py effects/sepia.sexp | python3 execute.py - -d . -o output.mp4
+;; No parameters
+
+(recipe "sepia"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect sepia :path "sexp_effects/effects/sepia.sexp")
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect sepia)))
+  result)

effects/sharpen.py

@@ -0,0 +1,63 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy", "opencv-python"]
+# ///
+"""
+@effect sharpen
+@version 1.0.0
+@author artdag
+
+@description
+Sharpening effect using unsharp mask technique. Enhances edges and detail.
+Great for making footage pop on beats.
+
+@param amount float
+  @range 0 5
+  @default 1.0
+  Sharpening intensity. 0 = no change, 1 = normal, 2+ = aggressive.
+
+@param radius float
+  @range 0 10
+  @default 1
+  Radius of sharpening (affects edge thickness).
+
+@example
+  (effect sharpen :amount 1.5)
+
+@example
+  ;; Sharpen on beats
+  (effect sharpen :amount (bind bass :range [0.5 2.0]))
+"""
+
+import numpy as np
+import cv2
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply sharpening to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - amount: sharpening intensity (default 1.0)
+            - radius: edge radius (default 1)
+        state: Persistent state dict (unused)
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    amount = params.get("amount", 1.0)
+    radius = params.get("radius", 1)
+
+    if amount <= 0:
+        return frame, state
+
+    # Create blurred version
+    ksize = max(1, int(radius)) * 2 + 1
+    blurred = cv2.GaussianBlur(frame, (ksize, ksize), 0)
+
+    # Unsharp mask: original + amount * (original - blurred)
+    result = frame.astype(np.float32) + amount * (frame.astype(np.float32) - blurred.astype(np.float32))
+
+    return np.clip(result, 0, 255).astype(np.uint8), state

effects/sharpen.sexp

@@ -0,0 +1,20 @@
+;; Sharpen effect - enhance edge detail
+;; Usage: python3 plan.py effects/sharpen.sexp -p amount=2 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   amount: sharpening strength (0.5 to 5, default: 2)
+;;           higher = sharper edges
+
+(recipe "sharpen"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect sharpen :path "sexp_effects/effects/sharpen.sexp")
+
+  ;; Default parameter (overridden by -p amount=N)
+  (def amount 2)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect sharpen :amount amount)))
+  result)

effects/shatter.py

@@ -0,0 +1,233 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy", "scipy"]
+# ///
+"""
+@effect shatter
+@version 1.0.0
+@author artdag
+
+@description
+Shatter effect. Explodes the image into flying pieces that move
+outward from a center point. Great for beat drops and transitions.
+
+@param intensity float
+  @range 0 1
+  @default 0.5
+  Explosion force (0 = no effect, 1 = full explosion).
+
+@param num_pieces int
+  @range 10 200
+  @default 50
+  Number of shatter pieces.
+
+@param center_x float
+  @range 0 1
+  @default 0.5
+  Explosion center X position.
+
+@param center_y float
+  @range 0 1
+  @default 0.5
+  Explosion center Y position.
+
+@param rotation_speed float
+  @range 0 5
+  @default 1.0
+  How fast pieces rotate as they fly.
+
+@param gravity float
+  @range 0 2
+  @default 0.3
+  Downward pull on pieces.
+
+@param fade_out bool
+  @default true
+  Fade pieces as they fly away.
+
+@param seed int
+  @default 42
+  Random seed for piece positions.
+
+@state pieces list
+  List of piece positions and velocities.
+
+@example
+  (effect shatter :intensity 0.7 :num_pieces 80)
+
+@example
+  ;; Beat-reactive explosion
+  (effect shatter :intensity (bind onset :range [0 1]) :gravity 0.5)
+"""
+
+import numpy as np
+from scipy import ndimage
+from pathlib import Path
+import sys
+
+# Import DeterministicRNG from same directory
+_effects_dir = Path(__file__).parent
+if str(_effects_dir) not in sys.path:
+    sys.path.insert(0, str(_effects_dir))
+from random import DeterministicRNG
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply shatter effect to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+        state: Persistent state dict
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    intensity = np.clip(params.get("intensity", 0.5), 0, 1)
+    num_pieces = max(10, min(int(params.get("num_pieces", 50)), 200))
+    center_x = params.get("center_x", 0.5)
+    center_y = params.get("center_y", 0.5)
+    rotation_speed = params.get("rotation_speed", 1.0)
+    gravity = params.get("gravity", 0.3)
+    fade_out = params.get("fade_out", True)
+    seed = int(params.get("seed", 42))
+    t = params.get("_time", 0)
+
+    if state is None:
+        state = {}
+
+    if intensity < 0.01:
+        return frame, state
+
+    h, w = frame.shape[:2]
+    cx, cy = int(center_x * w), int(center_y * h)
+
+    # Initialize pieces
+    if "pieces" not in state or len(state["pieces"]) != num_pieces:
+        state["pieces"] = _init_pieces(w, h, num_pieces, cx, cy, seed)
+        state["start_time"] = t
+
+    pieces = state["pieces"]
+    start_time = state.get("start_time", t)
+    effect_t = t - start_time
+
+    # Create output with black background
+    result = np.zeros_like(frame)
+
+    time_factor = effect_t * intensity * 3.0
+
+    # Draw each piece
+    for piece in pieces:
+        px, py, pw, ph, vx, vy, rot = piece
+
+        if pw <= 0 or ph <= 0:
+            continue
+
+        # Calculate current position with physics
+        curr_x = px + vx * time_factor * w * 0.5
+        curr_y = py + vy * time_factor * h * 0.5 + gravity * time_factor ** 2 * h * 0.2
+        curr_rot = rot * rotation_speed * time_factor * 180
+
+        # Calculate alpha (fade out over distance)
+        distance = np.sqrt((curr_x - px)**2 + (curr_y - py)**2)
+        alpha = 1.0 - (distance / max(w, h)) if fade_out else 1.0
+        alpha = max(0, min(1, alpha))
+
+        if alpha < 0.05:
+            continue
+
+        # Extract piece from original frame
+        px1, py1 = max(0, int(px)), max(0, int(py))
+        px2, py2 = min(w, int(px + pw)), min(h, int(py + ph))
+
+        if px2 <= px1 or py2 <= py1:
+            continue
+
+        piece_img = frame[py1:py2, px1:px2].copy()
+
+        # Rotate piece
+        if abs(curr_rot) > 1:
+            piece_img = ndimage.rotate(piece_img, curr_rot, reshape=False, mode='constant', cval=0)
+
+        # Calculate destination
+        dest_x = int(curr_x)
+        dest_y = int(curr_y)
+        piece_h, piece_w = piece_img.shape[:2]
+
+        # Clip to frame bounds
+        src_x1, src_y1 = 0, 0
+        src_x2, src_y2 = piece_w, piece_h
+        dst_x1, dst_y1 = dest_x, dest_y
+        dst_x2, dst_y2 = dest_x + piece_w, dest_y + piece_h
+
+        if dst_x1 < 0:
+            src_x1 = -dst_x1
+            dst_x1 = 0
+        if dst_y1 < 0:
+            src_y1 = -dst_y1
+            dst_y1 = 0
+        if dst_x2 > w:
+            src_x2 -= (dst_x2 - w)
+            dst_x2 = w
+        if dst_y2 > h:
+            src_y2 -= (dst_y2 - h)
+            dst_y2 = h
+
+        if dst_x2 <= dst_x1 or dst_y2 <= dst_y1:
+            continue
+        if src_x2 <= src_x1 or src_y2 <= src_y1:
+            continue
+
+        # Blend piece onto result
+        piece_region = piece_img[src_y1:src_y2, src_x1:src_x2]
+        if piece_region.size == 0:
+            continue
+
+        result_region = result[dst_y1:dst_y2, dst_x1:dst_x2]
+        if result_region.shape != piece_region.shape:
+            continue
+
+        result[dst_y1:dst_y2, dst_x1:dst_x2] = (
+            result_region * (1 - alpha) + piece_region * alpha
+        ).astype(np.uint8)
+
+    # Blend with original based on intensity
+    final = ((1 - intensity) * frame + intensity * result).astype(np.uint8)
+
+    return final, state
+
+
+def _init_pieces(w: int, h: int, num_pieces: int, cx: int, cy: int, seed: int) -> list:
+    """Initialize shatter pieces with random positions and velocities."""
+    rng = DeterministicRNG(seed)
+
+    pieces = []
+
+    # Create grid of pieces
+    cols = max(1, int(np.sqrt(num_pieces * w / h)))
+    rows = max(1, int(num_pieces / cols))
+    piece_w = w // cols
+    piece_h = h // rows
+
+    for row in range(rows):
+        for col in range(cols):
+            px = col * piece_w
+            py = row * piece_h
+            pw = piece_w + (w % cols if col == cols - 1 else 0)
+            ph = piece_h + (h % rows if row == rows - 1 else 0)
+
+            # Velocity away from center
+            piece_cx = px + pw // 2
+            piece_cy = py + ph // 2
+            dx = piece_cx - cx
+            dy = piece_cy - cy
+            dist = max(1, np.sqrt(dx*dx + dy*dy))
+
+            vx = dx / dist + rng.uniform(-0.3, 0.3)
+            vy = dy / dist + rng.uniform(-0.3, 0.3)
+            rot = rng.uniform(-2, 2)
+
+            pieces.append((px, py, pw, ph, vx, vy, rot))
+
+    return pieces

effects/strobe.py

@@ -0,0 +1,90 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy"]
+# ///
+"""
+@effect strobe
+@version 1.0.0
+@author artdag
+
+@description
+Strobe / Posterize Time effect. Locks video to a reduced frame rate,
+creating a choppy, stop-motion look. Also known as frame hold.
+
+@param frame_rate float
+  @range 1 60
+  @default 12
+  Target frame rate in fps. Lower = choppier.
+
+@param sync_to_beat bool
+  @default false
+  If true, hold frames until next beat (overrides frame_rate).
+
+@param beat_divisor int
+  @range 1 8
+  @default 1
+  Hold for 1/N beats when sync_to_beat is true.
+
+@state held_frame ndarray
+  Currently held frame.
+
+@state held_until float
+  Time until which to hold the frame.
+
+@example
+  (effect strobe :frame_rate 8)
+
+@example
+  ;; Very choppy at 4 fps
+  (effect strobe :frame_rate 4)
+
+@example
+  ;; Beat-synced frame hold
+  (effect strobe :sync_to_beat true :beat_divisor 2)
+"""
+
+import numpy as np
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply strobe/posterize time effect to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - frame_rate: target fps 1-60 (default 12)
+            - sync_to_beat: use beat timing (default False)
+            - beat_divisor: beat fraction (default 1)
+        state: Persistent state dict
+            - held_frame: currently held frame
+            - held_until: hold expiry time
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    target_fps = max(1, min(params.get("frame_rate", 12), 60))
+    sync_to_beat = params.get("sync_to_beat", False)
+    beat_divisor = max(1, int(params.get("beat_divisor", 1)))
+
+    # Get current time from params (executor should provide this)
+    t = params.get("_time", 0)
+
+    if state is None:
+        state = {}
+
+    # Initialize state
+    if "held_frame" not in state:
+        state["held_frame"] = None
+        state["held_until"] = 0.0
+        state["last_beat"] = -1
+
+    # Frame rate based hold
+    frame_duration = 1.0 / target_fps
+
+    if t >= state["held_until"]:
+        # Time for new frame
+        state["held_frame"] = frame.copy()
+        state["held_until"] = t + frame_duration
+
+    return state["held_frame"] if state["held_frame"] is not None else frame, state

effects/strobe.sexp

@@ -0,0 +1,20 @@
+;; Strobe effect - flashing/blinking
+;; Usage: python3 plan.py effects/strobe.sexp -p frequency=4 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   frequency: flashes per second (1 to 15, default: 4)
+;;              WARNING: high values may cause discomfort
+
+(recipe "strobe"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect strobe :path "sexp_effects/effects/strobe.sexp")
+
+  ;; Default parameter (overridden by -p frequency=N)
+  (def frequency 4)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect strobe :frequency frequency)))
+  result)

effects/swirl.py

@@ -0,0 +1,121 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy", "opencv-python"]
+# ///
+"""
+@effect swirl
+@version 1.0.0
+@author artdag
+
+@description
+Spiral/vortex distortion that twists the image around a center point.
+Creates whirlpool-like effects. Great for psychedelic/hypnotic visuals.
+
+@param strength float
+  @range -10 10
+  @default 1.0
+  Swirl strength in radians. Positive = counter-clockwise, negative = clockwise.
+
+@param radius float
+  @range 0.1 2
+  @default 0.5
+  Effect radius as fraction of image size. Larger = wider swirl.
+
+@param center_x float
+  @range 0 1
+  @default 0.5
+  Horizontal center of swirl (0 = left, 1 = right).
+
+@param center_y float
+  @range 0 1
+  @default 0.5
+  Vertical center of swirl (0 = top, 1 = bottom).
+
+@param falloff string
+  @enum linear quadratic gaussian
+  @default quadratic
+  How swirl strength decreases from center:
+  - linear: constant decrease
+  - quadratic: sharper center, softer edges
+  - gaussian: smooth bell curve
+
+@example
+  (effect swirl :strength 2)
+
+@example
+  ;; Reactive swirl
+  (effect swirl :strength (bind energy :range [0 5]))
+"""
+
+import numpy as np
+import cv2
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply swirl distortion to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - strength: swirl amount in radians (default 1.0)
+            - radius: effect radius as fraction (default 0.5)
+            - center_x: horizontal center 0-1 (default 0.5)
+            - center_y: vertical center 0-1 (default 0.5)
+            - falloff: linear/quadratic/gaussian (default quadratic)
+        state: Persistent state dict (unused)
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    strength = params.get("strength", 1.0)
+    radius_frac = params.get("radius", 0.5)
+    center_x = params.get("center_x", 0.5)
+    center_y = params.get("center_y", 0.5)
+    falloff = params.get("falloff", "quadratic")
+
+    if strength == 0:
+        return frame, state
+
+    h, w = frame.shape[:2]
+
+    # Calculate center and radius in pixels
+    cx = w * center_x
+    cy = h * center_y
+    radius = max(w, h) * radius_frac
+
+    # Create coordinate grids
+    y_coords, x_coords = np.mgrid[0:h, 0:w].astype(np.float64)
+
+    # Calculate distance and angle from center
+    dx = x_coords - cx
+    dy = y_coords - cy
+    dist = np.sqrt(dx**2 + dy**2)
+    angle = np.arctan2(dy, dx)
+
+    # Normalized distance for falloff
+    norm_dist = dist / radius
+
+    # Calculate falloff factor
+    if falloff == "linear":
+        factor = np.maximum(0, 1 - norm_dist)
+    elif falloff == "gaussian":
+        factor = np.exp(-norm_dist**2 * 2)
+    else:  # quadratic
+        factor = np.maximum(0, 1 - norm_dist**2)
+
+    # Apply swirl rotation
+    new_angle = angle + strength * factor
+
+    # Calculate new coordinates
+    new_x = (cx + dist * np.cos(new_angle)).astype(np.float32)
+    new_y = (cy + dist * np.sin(new_angle)).astype(np.float32)
+
+    # Remap
+    result = cv2.remap(
+        frame, new_x, new_y,
+        cv2.INTER_LINEAR,
+        borderMode=cv2.BORDER_REFLECT
+    )
+
+    return result, state

effects/swirl.sexp

@@ -0,0 +1,20 @@
+;; Swirl effect - spiral distortion from center
+;; Usage: python3 plan.py effects/swirl.sexp -p strength=3 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   strength: swirl intensity (-10 to 10, default: 3)
+;;             positive = clockwise, negative = counter-clockwise
+
+(recipe "swirl"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect swirl :path "sexp_effects/effects/swirl.sexp")
+
+  ;; Default parameter (overridden by -p strength=N)
+  (def strength 3)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect swirl :strength strength)))
+  result)

effects/threshold.py

@@ -0,0 +1,85 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy"]
+# ///
+"""
+@effect threshold
+@version 1.0.0
+@author artdag
+
+@description
+Threshold effect. Converts to high-contrast black and white.
+Creates stark, graphic look by converting grayscale to pure
+black/white based on a threshold value.
+
+@param level int
+  @range 0 255
+  @default 128
+  Threshold level. Pixels above = white, below = black.
+
+@param invert bool
+  @default false
+  Swap black and white.
+
+@param color_mode string
+  @enum bw color
+  @default bw
+  Output mode:
+  - bw: pure black and white
+  - color: keep original colors where above threshold
+
+@example
+  (effect threshold :level 100)
+
+@example
+  ;; Beat-reactive threshold
+  (effect threshold :level (bind bass :range [80 180]) :invert true)
+"""
+
+import numpy as np
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply threshold effect to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - level: threshold 0-255 (default 128)
+            - invert: swap black/white (default False)
+            - color_mode: bw or color (default bw)
+        state: Persistent state dict
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    level = int(np.clip(params.get("level", 128), 0, 255))
+    invert = params.get("invert", False)
+    color_mode = params.get("color_mode", "bw")
+
+    if state is None:
+        state = {}
+
+    # Convert to grayscale for threshold comparison
+    if len(frame.shape) == 3:
+        gray = np.mean(frame, axis=2)
+    else:
+        gray = frame
+
+    # Apply threshold
+    mask = gray > level
+
+    if invert:
+        mask = ~mask
+
+    if color_mode == "bw":
+        # Pure black and white
+        result = np.where(mask[:, :, np.newaxis], 255, 0).astype(np.uint8)
+        if len(frame.shape) == 3:
+            result = np.repeat(result, frame.shape[2], axis=2)
+    else:
+        # Keep original colors where above threshold
+        result = np.where(mask[:, :, np.newaxis], frame, 0).astype(np.uint8)
+
+    return result, state

effects/threshold.sexp

@@ -0,0 +1,20 @@
+;; Threshold effect - convert to pure black and white
+;; Usage: python3 plan.py effects/threshold.sexp -p level=128 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   level: threshold cutoff (0 to 255, default: 128)
+;;          pixels below = black, above = white
+
+(recipe "threshold"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect threshold :path "sexp_effects/effects/threshold.sexp")
+
+  ;; Default parameter (overridden by -p level=N)
+  (def level 128)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect threshold :level level)))
+  result)

effects/tile_grid.py

@@ -0,0 +1,134 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy", "opencv-python"]
+# ///
+"""
+@effect tile_grid
+@version 1.0.0
+@author artdag
+
+@description
+Tile Grid effect. Repeats the frame in a grid pattern creating
+a mosaic by tiling scaled-down copies. Great for psychedelic visuals.
+
+@param rows int
+  @range 1 10
+  @default 2
+  Number of rows in grid.
+
+@param cols int
+  @range 1 10
+  @default 2
+  Number of columns in grid.
+
+@param gap int
+  @range 0 50
+  @default 0
+  Gap between tiles in pixels.
+
+@param gap_color list
+  @default [0, 0, 0]
+  RGB color for gaps.
+
+@param rotation_per_tile float
+  @range -180 180
+  @default 0
+  Rotation increment per tile in degrees.
+
+@param alternate_flip bool
+  @default false
+  Flip alternating tiles horizontally.
+
+@example
+  (effect tile_grid :rows 3 :cols 3)
+
+@example
+  ;; Rotating tiles
+  (effect tile_grid :rows 2 :cols 2 :rotation_per_tile 90)
+
+@example
+  ;; Beat-reactive grid
+  (effect tile_grid :rows (bind bass :range [2 6]) :cols (bind bass :range [2 6]))
+"""
+
+import numpy as np
+import cv2
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply tile grid effect to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - rows: number of rows (default 2)
+            - cols: number of columns (default 2)
+            - gap: gap between tiles (default 0)
+            - gap_color: RGB tuple (default [0,0,0])
+            - rotation_per_tile: rotation increment (default 0)
+            - alternate_flip: flip alternating tiles (default False)
+        state: Persistent state dict
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    rows = max(1, min(int(params.get("rows", 2)), 10))
+    cols = max(1, min(int(params.get("cols", 2)), 10))
+    gap = max(0, int(params.get("gap", 0)))
+    gap_color = params.get("gap_color", [0, 0, 0])
+    rotation_per_tile = params.get("rotation_per_tile", 0)
+    alternate_flip = params.get("alternate_flip", False)
+
+    if state is None:
+        state = {}
+
+    h, w = frame.shape[:2]
+
+    # Calculate tile size
+    tile_w = (w - gap * (cols - 1)) // cols
+    tile_h = (h - gap * (rows - 1)) // rows
+
+    if tile_w <= 0 or tile_h <= 0:
+        return frame, state
+
+    # Scale down the original frame to tile size
+    tile = cv2.resize(frame, (tile_w, tile_h), interpolation=cv2.INTER_LINEAR)
+
+    # Create result with gap color
+    if isinstance(gap_color, (list, tuple)) and len(gap_color) >= 3:
+        result = np.full((h, w, 3), gap_color[:3], dtype=np.uint8)
+    else:
+        result = np.zeros((h, w, 3), dtype=np.uint8)
+
+    # Place tiles
+    tile_idx = 0
+    for row in range(rows):
+        for col in range(cols):
+            y = row * (tile_h + gap)
+            x = col * (tile_w + gap)
+
+            current_tile = tile.copy()
+
+            # Apply rotation if specified
+            if rotation_per_tile != 0:
+                angle = rotation_per_tile * tile_idx
+                center = (tile_w // 2, tile_h // 2)
+                M = cv2.getRotationMatrix2D(center, angle, 1.0)
+                current_tile = cv2.warpAffine(current_tile, M, (tile_w, tile_h),
+                                              borderMode=cv2.BORDER_REFLECT)
+
+            # Apply flip for alternating tiles
+            if alternate_flip and (row + col) % 2 == 1:
+                current_tile = cv2.flip(current_tile, 1)
+
+            # Place tile
+            y_end = min(y + tile_h, h)
+            x_end = min(x + tile_w, w)
+            tile_crop_h = y_end - y
+            tile_crop_w = x_end - x
+            result[y:y_end, x:x_end] = current_tile[:tile_crop_h, :tile_crop_w]
+
+            tile_idx += 1
+
+    return result, state

effects/tile_grid.sexp

@@ -0,0 +1,21 @@
+;; Tile grid effect - repeat image in grid
+;; Usage: python3 plan.py effects/tile_grid.sexp -p rows=2 -p cols=2 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   rows: number of rows (1 to 8, default: 2)
+;;   cols: number of columns (1 to 8, default: 2)
+
+(recipe "tile_grid"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect tile_grid :path "sexp_effects/effects/tile_grid.sexp")
+
+  ;; Default parameters (overridden by -p rows=N -p cols=N)
+  (def rows 2)
+  (def cols 2)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect tile_grid :rows rows :cols cols)))
+  result)

effects/trails.py

@@ -0,0 +1,95 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy"]
+# ///
+"""
+@effect trails
+@version 1.0.0
+@author artdag
+
+@description
+Trails effect. Creates persistent motion trails by blending current
+frame with previous frames. Like echo but with configurable blend.
+
+@param persistence float
+  @range 0 0.99
+  @default 0.8
+  How much of previous frame remains (0 = none, 0.99 = very long trails).
+
+@param blend_mode string
+  @enum blend add screen lighten darken
+  @default blend
+  How to combine frames.
+
+@param fade_color list
+  @default [0, 0, 0]
+  Color to fade toward.
+
+@state trail_buffer ndarray
+  Accumulated trail buffer.
+
+@example
+  (effect trails :persistence 0.85)
+
+@example
+  ;; Long bright trails
+  (effect trails :persistence 0.9 :blend_mode "add")
+"""
+
+import numpy as np
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply trails effect to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - persistence: trail length 0-0.99 (default 0.8)
+            - blend_mode: how to combine (default blend)
+            - fade_color: color to fade to (default black)
+        state: Persistent state dict
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    persistence = max(0, min(params.get("persistence", 0.8), 0.99))
+    blend_mode = params.get("blend_mode", "blend")
+    fade_color = params.get("fade_color", [0, 0, 0])
+
+    if state is None:
+        state = {}
+
+    # Initialize trail buffer
+    if "trail_buffer" not in state or state["trail_buffer"].shape != frame.shape:
+        state["trail_buffer"] = frame.astype(np.float32)
+
+    buffer = state["trail_buffer"]
+    current = frame.astype(np.float32)
+
+    # Get fade color
+    if isinstance(fade_color, (list, tuple)) and len(fade_color) >= 3:
+        fade = np.array(fade_color[:3], dtype=np.float32)
+    else:
+        fade = np.array([0, 0, 0], dtype=np.float32)
+
+    # Blend buffer toward fade color
+    faded_buffer = buffer * persistence + fade * (1 - persistence)
+
+    # Combine with current frame based on blend mode
+    if blend_mode == "add":
+        result = faded_buffer + current
+    elif blend_mode == "screen":
+        result = 255 - ((255 - faded_buffer) * (255 - current) / 255)
+    elif blend_mode == "lighten":
+        result = np.maximum(faded_buffer, current)
+    elif blend_mode == "darken":
+        result = np.minimum(faded_buffer, current)
+    else:  # blend
+        result = faded_buffer + current * (1 - persistence)
+
+    # Update buffer
+    state["trail_buffer"] = np.clip(result, 0, 255)
+
+    return np.clip(result, 0, 255).astype(np.uint8), state

effects/trails.sexp

@@ -0,0 +1,20 @@
+;; Trails effect - motion blur/persistence
+;; Usage: python3 plan.py effects/trails.sexp -p persistence=0.7 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   persistence: trail strength (0.3 to 0.95, default: 0.7)
+;;                higher = longer trails
+
+(recipe "trails"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect trails :path "sexp_effects/effects/trails.sexp")
+
+  ;; Default parameter (overridden by -p persistence=N)
+  (def persistence 0.7)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect trails :persistence persistence)))
+  result)

effects/vhs.py

@@ -0,0 +1,163 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy", "opencv-python"]
+# ///
+"""
+@effect vhs
+@version 1.0.0
+@author artdag
+
+@description
+VHS / Analog Video effect. Complete VHS tape simulation combining
+tracking errors, color bleeding, noise, and scan line distortion.
+
+@param tracking_error float
+  @range 0 50
+  @default 5
+  Horizontal displacement amount. Sync to onset for glitches.
+
+@param color_bleed int
+  @range 0 20
+  @default 3
+  Horizontal color smearing (typical VHS artifact).
+
+@param noise_intensity float
+  @range 0 1
+  @default 0.2
+  Static noise amount.
+
+@param chroma_shift int
+  @range 0 15
+  @default 2
+  Color channel offset (VHS color alignment issues).
+
+@param head_switching bool
+  @default true
+  Bottom-of-frame distortion.
+
+@param tape_crease_prob float
+  @range 0 0.5
+  @default 0.05
+  Probability of random tape crease distortion per frame.
+
+@param blur_amount float
+  @range 0 5
+  @default 1
+  VHS softness blur.
+
+@param seed int
+  @default 42
+  Random seed for deterministic artifacts.
+
+@state rng DeterministicRNG
+  Random number generator for artifacts.
+
+@example
+  (effect vhs :tracking_error 10 :color_bleed 5)
+
+@example
+  ;; Reactive VHS glitch
+  (effect vhs :tracking_error (bind onset :range [0 30]) :tape_crease_prob 0.1)
+"""
+
+import numpy as np
+import cv2
+from pathlib import Path
+import sys
+
+# Import DeterministicRNG from same directory
+_effects_dir = Path(__file__).parent
+if str(_effects_dir) not in sys.path:
+    sys.path.insert(0, str(_effects_dir))
+from random import DeterministicRNG
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply VHS effect to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+        state: Persistent state dict
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    tracking_error = params.get("tracking_error", 5)
+    color_bleed = int(params.get("color_bleed", 3))
+    noise_intensity = params.get("noise_intensity", 0.2)
+    chroma_shift = int(params.get("chroma_shift", 2))
+    head_switching = params.get("head_switching", True)
+    tape_crease_prob = params.get("tape_crease_prob", 0.05)
+    blur_amount = params.get("blur_amount", 1)
+    seed = int(params.get("seed", 42))
+
+    if state is None:
+        state = {}
+
+    # Initialize RNG
+    if "rng" not in state:
+        state["rng"] = DeterministicRNG(seed)
+    rng = state["rng"]
+
+    h, w = frame.shape[:2]
+    result = frame.astype(np.float32).copy()
+
+    # Apply slight blur (VHS softness)
+    if blur_amount > 0:
+        ksize = int(blur_amount * 2) * 2 + 1
+        result = cv2.GaussianBlur(result, (ksize, 1), 0)
+
+    # Apply color bleed (horizontal color smearing)
+    if color_bleed > 0:
+        ksize = color_bleed * 2 + 1
+        result[:, :, 0] = cv2.blur(result[:, :, 0], (ksize, 1))
+        result[:, :, 2] = cv2.blur(result[:, :, 2], (ksize, 1))
+
+    # Apply chroma shift (color channel misalignment)
+    if chroma_shift > 0:
+        shifted = np.zeros_like(result)
+        M_r = np.float32([[1, 0, chroma_shift], [0, 1, 0]])
+        M_b = np.float32([[1, 0, -chroma_shift], [0, 1, 0]])
+        shifted[:, :, 0] = cv2.warpAffine(result[:, :, 0], M_r, (w, h), borderMode=cv2.BORDER_REPLICATE)
+        shifted[:, :, 1] = result[:, :, 1]
+        shifted[:, :, 2] = cv2.warpAffine(result[:, :, 2], M_b, (w, h), borderMode=cv2.BORDER_REPLICATE)
+        result = shifted
+
+    # Apply tracking error (horizontal line displacement)
+    if tracking_error > 0:
+        for y in range(h):
+            sine_shift = np.sin(y * 0.05)
+            rand_shift = rng.uniform(-0.3, 0.3)
+            displacement = int(tracking_error * (sine_shift + rand_shift))
+            if displacement != 0:
+                result[y] = np.roll(result[y], displacement, axis=0)
+
+    # Apply tape crease (random distortion bands)
+    if tape_crease_prob > 0 and rng.uniform() < tape_crease_prob:
+        band_start = rng.randint(0, max(1, h - 20))
+        band_height = rng.randint(5, 20)
+        for y in range(band_start, min(band_start + band_height, h)):
+            displacement = rng.randint(-50, 50)
+            result[y] = np.roll(result[y], displacement, axis=0)
+            result[y] = result[y] * rng.uniform(0.5, 1.5)
+
+    # Apply head switching noise (bottom of frame distortion)
+    if head_switching:
+        switch_height = rng.randint(5, 15)
+        for y in range(h - switch_height, h):
+            factor = (y - (h - switch_height)) / switch_height
+            displacement = int(factor * 30 * rng.uniform(0.5, 1.5))
+            result[y] = np.roll(result[y], displacement, axis=0)
+            noise = np.array([[rng.gaussian(0, 20 * factor) for _ in range(3)] for _ in range(w)])
+            result[y] = result[y] + noise
+
+    # Apply static noise
+    if noise_intensity > 0:
+        noise = np.array([[[rng.gaussian(0, noise_intensity * 30) for _ in range(3)]
+                          for _ in range(w)]
+                         for _ in range(h)])
+        result = result + noise
+
+    return np.clip(result, 0, 255).astype(np.uint8), state

effects/vignette.py

@@ -0,0 +1,116 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy"]
+# ///
+"""
+@effect vignette
+@version 1.0.0
+@author artdag
+
+@description
+Vignette effect. Darkens the corners of the frame, drawing focus
+to the center. Classic cinematic look.
+
+@param strength float
+  @range 0 1
+  @default 0.5
+  How dark the corners get (0 = none, 1 = black corners).
+
+@param radius float
+  @range 0.5 2
+  @default 1.0
+  Size of the bright center area. Smaller = more vignette.
+
+@param softness float
+  @range 0.1 1
+  @default 0.5
+  How gradual the falloff is.
+
+@param center_x float
+  @range 0 1
+  @default 0.5
+  Center X position.
+
+@param center_y float
+  @range 0 1
+  @default 0.5
+  Center Y position.
+
+@param color list
+  @default [0, 0, 0]
+  Vignette color (default black).
+
+@example
+  (effect vignette :strength 0.6)
+
+@example
+  ;; Off-center vignette
+  (effect vignette :center_x 0.3 :center_y 0.3 :strength 0.7)
+"""
+
+import numpy as np
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply vignette effect to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - strength: darkness 0-1 (default 0.5)
+            - radius: center size 0.5-2 (default 1.0)
+            - softness: falloff gradient (default 0.5)
+            - center_x: center X 0-1 (default 0.5)
+            - center_y: center Y 0-1 (default 0.5)
+            - color: RGB tuple (default [0,0,0])
+        state: Persistent state dict
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    strength = np.clip(params.get("strength", 0.5), 0, 1)
+    radius = max(0.5, min(params.get("radius", 1.0), 2))
+    softness = max(0.1, min(params.get("softness", 0.5), 1))
+    center_x = params.get("center_x", 0.5)
+    center_y = params.get("center_y", 0.5)
+    color = params.get("color", [0, 0, 0])
+
+    if state is None:
+        state = {}
+
+    if strength <= 0:
+        return frame, state
+
+    h, w = frame.shape[:2]
+
+    # Calculate center in pixels
+    cx = w * center_x
+    cy = h * center_y
+
+    # Create distance map from center
+    y_coords, x_coords = np.ogrid[:h, :w]
+    dist = np.sqrt((x_coords - cx)**2 + (y_coords - cy)**2)
+
+    # Normalize distance
+    max_dist = np.sqrt(cx**2 + cy**2) * radius
+
+    # Create vignette mask
+    normalized_dist = dist / max_dist
+
+    # Apply softness to the falloff
+    vignette_mask = 1 - np.clip((normalized_dist - (1 - softness)) / softness, 0, 1) * strength
+
+    # Apply vignette
+    if isinstance(color, (list, tuple)) and len(color) >= 3:
+        vignette_color = np.array(color[:3], dtype=np.float32)
+    else:
+        vignette_color = np.array([0, 0, 0], dtype=np.float32)
+
+    result = frame.astype(np.float32)
+
+    # Blend toward vignette color based on mask
+    for c in range(3):
+        result[:, :, c] = result[:, :, c] * vignette_mask + vignette_color[c] * (1 - vignette_mask)
+
+    return np.clip(result, 0, 255).astype(np.uint8), state

effects/vignette.sexp

@@ -0,0 +1,19 @@
+;; Vignette effect - darken edges
+;; Usage: python3 plan.py effects/vignette.sexp -p strength=0.6 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   strength: edge darkening amount (0.1 to 1.0, default: 0.6)
+
+(recipe "vignette"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect vignette :path "sexp_effects/effects/vignette.sexp")
+
+  ;; Default parameter (overridden by -p strength=N)
+  (def strength 0.6)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect vignette :strength strength)))
+  result)

effects/wave.py

@@ -0,0 +1,108 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy", "opencv-python"]
+# ///
+"""
+@effect wave
+@version 1.0.0
+@author artdag
+
+@description
+Sine wave displacement distortion. Creates wavy, liquid-like warping.
+Great for psychedelic and underwater effects synced to music.
+
+@param amplitude float
+  @range 0 100
+  @default 10
+  Wave height in pixels. Bind to bass for punchy distortion.
+
+@param wavelength float
+  @range 10 500
+  @default 50
+  Distance between wave peaks in pixels.
+
+@param speed float
+  @range 0 10
+  @default 1
+  Wave animation speed. Uses state to track phase over time.
+
+@param direction string
+  @enum horizontal vertical both
+  @default horizontal
+  Wave direction:
+  - horizontal: waves move left-right
+  - vertical: waves move up-down
+  - both: waves in both directions
+
+@state phase float
+  Tracks wave animation phase across frames.
+
+@example
+  (effect wave :amplitude 20 :wavelength 100)
+
+@example
+  ;; Bass-reactive waves
+  (effect wave :amplitude (bind bass :range [0 50] :transform sqrt))
+"""
+
+import numpy as np
+import cv2
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Apply wave distortion to a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - amplitude: wave height in pixels (default 10)
+            - wavelength: distance between peaks (default 50)
+            - speed: animation speed (default 1)
+            - direction: horizontal/vertical/both (default horizontal)
+        state: Persistent state dict
+            - phase: current wave phase
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    amplitude = params.get("amplitude", 10)
+    wavelength = params.get("wavelength", 50)
+    speed = params.get("speed", 1)
+    direction = params.get("direction", "horizontal")
+
+    if state is None:
+        state = {}
+
+    if amplitude == 0:
+        return frame, state
+
+    h, w = frame.shape[:2]
+
+    # Update phase for animation
+    phase = state.get("phase", 0)
+    phase += speed * 0.1
+    state["phase"] = phase
+
+    # Create coordinate maps
+    map_x = np.tile(np.arange(w, dtype=np.float32), (h, 1))
+    map_y = np.tile(np.arange(h, dtype=np.float32).reshape(-1, 1), (1, w))
+
+    if direction in ("horizontal", "both"):
+        # Horizontal waves: displace X based on Y
+        wave = np.sin(2 * np.pi * map_y / wavelength + phase) * amplitude
+        map_x = map_x + wave
+
+    if direction in ("vertical", "both"):
+        # Vertical waves: displace Y based on X
+        wave = np.sin(2 * np.pi * map_x / wavelength + phase) * amplitude
+        map_y = map_y + wave
+
+    # Apply distortion
+    result = cv2.remap(
+        frame, map_x, map_y,
+        cv2.INTER_LINEAR,
+        borderMode=cv2.BORDER_REFLECT
+    )
+
+    return result, state

effects/wave.sexp

@@ -0,0 +1,21 @@
+;; Wave effect - sinusoidal distortion
+;; Usage: python3 plan.py effects/wave.sexp -p amplitude=30 -p wavelength=60 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   amplitude: wave height in pixels (5 to 100, default: 30)
+;;   wavelength: wave period in pixels (20 to 200, default: 60)
+
+(recipe "wave"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect wave :path "sexp_effects/effects/wave.sexp")
+
+  ;; Default parameters (overridden by -p amplitude=N -p wavelength=N)
+  (def amplitude 30)
+  (def wavelength 60)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect wave :amplitude amplitude :wavelength wavelength)))
+  result)

effects/zoom.py

@@ -0,0 +1,91 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["numpy", "opencv-python"]
+# ///
+"""
+@effect zoom
+@version 1.0.0
+@author artdag
+
+@description
+Zooms into the center of the frame. Values > 1 zoom in (magnify),
+values < 1 zoom out (shrink with black borders).
+
+@param factor float
+  @range 0.1 5
+  @default 1.0
+  Zoom factor. 1 = unchanged, 2 = 2x magnification, 0.5 = half size.
+
+@param center_x float
+  @range 0 1
+  @default 0.5
+  Horizontal center of zoom (0 = left, 1 = right).
+
+@param center_y float
+  @range 0 1
+  @default 0.5
+  Vertical center of zoom (0 = top, 1 = bottom).
+
+@example
+  (effect zoom :factor 1.5)
+
+@example
+  ;; Pulse zoom on bass
+  (effect zoom :factor (bind bass :range [1.0 1.5] :transform sqrt))
+
+@example
+  ;; Zoom to corner
+  (effect zoom :factor 2 :center_x 0 :center_y 0)
+"""
+
+import numpy as np
+import cv2
+
+
+def process_frame(frame: np.ndarray, params: dict, state: dict) -> tuple:
+    """
+    Zoom a video frame.
+
+    Args:
+        frame: Input frame as numpy array (H, W, 3) RGB uint8
+        params: Effect parameters
+            - factor: zoom multiplier (default 1.0)
+            - center_x: horizontal center 0-1 (default 0.5)
+            - center_y: vertical center 0-1 (default 0.5)
+        state: Persistent state dict (unused)
+
+    Returns:
+        Tuple of (processed_frame, new_state)
+    """
+    factor = params.get("factor", 1.0)
+    center_x = params.get("center_x", 0.5)
+    center_y = params.get("center_y", 0.5)
+
+    if factor is None or factor <= 0.01:
+        factor = 1.0
+
+    if factor == 1.0:
+        return frame, state
+
+    h, w = frame.shape[:2]
+
+    # Calculate crop region for zoom in
+    new_w = int(w / factor)
+    new_h = int(h / factor)
+
+    if new_w <= 0 or new_h <= 0:
+        return frame, state
+
+    # Calculate crop offset based on center
+    x_start = int((w - new_w) * center_x)
+    y_start = int((h - new_h) * center_y)
+
+    # Clamp to valid range
+    x_start = max(0, min(x_start, w - new_w))
+    y_start = max(0, min(y_start, h - new_h))
+
+    # Crop and resize back to original dimensions
+    cropped = frame[y_start:y_start + new_h, x_start:x_start + new_w]
+    result = cv2.resize(cropped, (w, h), interpolation=cv2.INTER_LINEAR)
+
+    return result, state

effects/zoom.sexp

@@ -0,0 +1,20 @@
+;; Zoom effect - scale from center
+;; Usage: python3 plan.py effects/zoom.sexp -p factor=1.2 | python3 execute.py - -d . -o output.mp4
+;;
+;; Parameters:
+;;   factor: zoom multiplier (0.5 to 3.0, default: 1.2)
+;;           <1 = zoom out, >1 = zoom in
+
+(recipe "zoom"
+  :version "1.0"
+  :encoding (:codec "libx264" :crf 20 :preset "medium" :audio-codec "aac" :fps 30)
+
+  (effect zoom :path "sexp_effects/effects/zoom.sexp")
+
+  ;; Default parameter (overridden by -p factor=N)
+  (def factor 1.2)
+
+  (def video (source :path "monday.webm"))
+  (def clip (-> video (segment :start 0 :duration 10)))
+  (def result (-> clip (effect zoom :factor factor)))
+  result)