ASCII Video Production Pipeline

Creative Standard

This is visual art. ASCII characters are the medium; cinema is the standard.

Before writing a single line of code, articulate the creative concept. What is the mood? What visual story does this tell? What makes THIS project different from every other ASCII video? The user's prompt is a starting point — interpret it with creative ambition, not literal transcription.

First-render excellence is non-negotiable. The output must be visually striking without requiring revision rounds. If something looks generic, flat, or like "AI-generated ASCII art," it is wrong — rethink the creative concept before shipping.

Go beyond the reference vocabulary. The effect catalogs, shader presets, and palette libraries in the references are a starting vocabulary. For every project, combine, modify, and invent new patterns. The catalog is a palette of paints — you write the painting.

Be proactively creative. Extend the skill's vocabulary when the project calls for it. If the references don't have what the vision demands, build it. Include at least one visual moment the user didn't ask for but will appreciate — a transition, an effect, a color choice that elevates the whole piece.

Cohesive aesthetic over technical correctness. All scenes in a video must feel connected by a unifying visual language — shared color temperature, related character palettes, consistent motion vocabulary. A technically correct video where every scene uses a random different effect is an aesthetic failure.

Dense, layered, considered. Every frame should reward viewing. Never flat black backgrounds. Always multi-grid composition. Always per-scene variation. Always intentional color.

Modes

references/inputs.md

references/inputs.md

references/effects.md

references/inputs.md

references/inputs.md

Stack

Single self-contained Python script per project. No GPU required.

Pipeline Architecture

Every mode follows the same 6-stage pipeline:

INPUT → ANALYZE → SCENE_FN → TONEMAP → SHADE → ENCODE

1. INPUT — Load/decode source material (video frames, audio samples, images, or nothing)
2. ANALYZE — Extract per-frame features (audio bands, video luminance/edges, motion vectors)
3. SCENE_FN — Scene function renders to pixel canvas (

   uint8 H,W,3

   ). Composes multiple character grids via

   _render_vf()

   + pixel blend modes. See

   references/composition.md

4. TONEMAP — Percentile-based adaptive brightness normalization. See

   references/composition.md

   § Adaptive Tonemap
5. SHADE — Post-processing via

   ShaderChain

   +

   FeedbackBuffer

   . See

   references/shaders.md

6. ENCODE — Pipe raw RGB frames to ffmpeg for H.264/GIF encoding

Creative Direction

Aesthetic Dimensions

architecture.md

architecture.md

effects.md

effects.md

effects.md

shaders.md

architecture.md

effects.md

composition.md

composition.md

shaders.md

Per-Section Variation

Never use the same config for the entire video. For each section/scene:

• Different background effect (or compose 2-3)
• Different character palette (match the mood)
• Different color strategy (or at minimum a different hue)
• Vary shader intensity (more bloom during peaks, more grain during quiet)
• Different particle types if particles are active

Project-Specific Invention

For every project, invent at least one of:

• A custom character palette matching the theme
• A custom background effect (combine/modify existing building blocks)
• A custom color palette (discrete RGB set matching the brand/mood)
• A custom particle character set
• A novel scene transition or visual moment

Don't just pick from the catalog. The catalog is vocabulary — you write the poem.

Workflow

Step 1: Creative Vision

Before any code, articulate the creative concept:

• Mood/atmosphere: What should the viewer feel? Energetic, meditative, chaotic, elegant, ominous?
• Visual story: What happens over the duration? Build tension? Transform? Dissolve?
• Color world: Warm/cool? Monochrome? Neon? Earth tones? What's the dominant hue?
• Character texture: Dense data? Sparse stars? Organic dots? Geometric blocks?
• What makes THIS different: What's the one thing that makes this project unique?
• Emotional arc: How do scenes progress? Open with energy, build to climax, resolve?

Map the user's prompt to aesthetic choices. A "chill lo-fi visualizer" demands different everything from a "glitch cyberpunk data stream."

Step 2: Technical Design

• Mode — which of the 6 modes above
• Resolution — landscape 1920x1080 (default), portrait 1080x1920, square 1080x1080 @ 24fps
• Hardware detection — auto-detect cores/RAM, set quality profile. See

  references/optimization.md

• Sections — map timestamps to scene functions, each with its own effect/palette/color/shader config
• Output format — MP4 (default), GIF (640x360 @ 15fps), PNG sequence

Step 3: Build the Script

Single Python file. Components (with references):

1. Hardware detection + quality profile —

   references/optimization.md

2. Input loader — mode-dependent;

   references/inputs.md

3. Feature analyzer — audio FFT, video luminance, or synthetic
4. Grid + renderer — multi-density grids with bitmap cache;

   references/architecture.md

5. Character palettes — multiple per project;

   references/architecture.md

   § Palettes
6. Color system — HSV + discrete RGB + harmony generation;

   references/architecture.md

   § Color
7. Scene functions — each returns

   canvas (uint8 H,W,3)

   ;

   references/scenes.md

8. Tonemap — adaptive brightness normalization;

   references/composition.md

9. Shader pipeline —

   ShaderChain

   +

   FeedbackBuffer

   ;

   references/shaders.md

10. Scene table + dispatcher — time → scene function + config;

    references/scenes.md

11. Parallel encoder — N-worker clip rendering with ffmpeg pipes
12. Main — orchestrate full pipeline

Step 4: Quality Verification

• Test frames first: render single frames at key timestamps before full render
• Brightness check:

  canvas.mean() > 8

  for all ASCII content. If dark, lower gamma
• Visual coherence: do all scenes feel like they belong to the same video?
• Creative vision check: does the output match the concept from Step 1? If it looks generic, go back

Critical Implementation Notes

Brightness — Use

tonemap()

, Not Linear Multipliers

This is the #1 visual issue. ASCII on black is inherently dark. Never use

canvas * N

def tonemap(canvas, gamma=0.75):
    f = canvas.astype(np.float32)
    lo, hi = np.percentile(f[::4, ::4], [1, 99.5])
    if hi - lo < 10: hi = lo + 10
    f = np.clip((f - lo) / (hi - lo), 0, 1) ** gamma
    return (f * 255).astype(np.uint8)

Pipeline:

scene_fn() → tonemap() → FeedbackBuffer → ShaderChain → ffmpeg

Per-scene gamma: default 0.75, solarize 0.55, posterize 0.50, bright scenes 0.85. Use

screen

overlay

Font Cell Height

macOS Pillow:

textbbox()

font.getmetrics()

cell_height = ascent + descent

references/troubleshooting.md

ffmpeg Pipe Deadlock

Never

stderr=subprocess.PIPE

references/troubleshooting.md

Font Compatibility

Not all Unicode chars render in all fonts. Validate palettes at init — render each char, check for blank output. See

references/troubleshooting.md

Per-Clip Architecture

For segmented videos (quotes, scenes, chapters), render each as a separate clip file for parallel rendering and selective re-rendering. See

references/scenes.md

Performance Targets

References

references/architecture.md

_render_vf()

references/composition.md

blend_canvas()

tonemap()

FeedbackBuffer

PixelBlendStack

references/effects.md

references/shaders.md

ShaderChain

_apply_shader_step()

references/scenes.md

Renderer

SCENES

render_clip()

references/inputs.md

references/optimization.md

references/troubleshooting.md

Creative Divergence (use only when user requests experimental/creative/unique output)

If the user asks for creative, experimental, surprising, or unconventional output, select the strategy that best fits and reason through its steps BEFORE generating code.

• Forced Connections — when the user wants cross-domain inspiration ("make it look organic," "industrial aesthetic")
• Conceptual Blending — when the user names two things to combine ("ocean meets music," "space + calligraphy")
• Oblique Strategies — when the user is maximally open ("surprise me," "something I've never seen")

Forced Connections

1. Pick a domain unrelated to the visual goal (weather systems, microbiology, architecture, fluid dynamics, textile weaving)
2. List its core visual/structural elements (erosion → gradual reveal; mitosis → splitting duplication; weaving → interlocking patterns)
3. Map those elements onto ASCII characters and animation patterns
4. Synthesize — what does "erosion" or "crystallization" look like in a character grid?

Conceptual Blending

1. Name two distinct visual/conceptual spaces (e.g., ocean waves + sheet music)
2. Map correspondences (crests = high notes, troughs = rests, foam = staccato)
3. Blend selectively — keep the most interesting mappings, discard forced ones
4. Develop emergent properties that exist only in the blend

Oblique Strategies

1. Draw one: "Honor thy error as a hidden intention" / "Use an old idea" / "What would your closest friend do?" / "Emphasize the flaws" / "Turn it upside down" / "Only a part, not the whole" / "Reverse"
2. Interpret the directive against the current ASCII animation challenge
3. Apply the lateral insight to the visual design before writing code