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skills/creative/manim-video/references/rendering.md
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skills/creative/manim-video/references/rendering.md
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# Rendering Reference
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## Prerequisites
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```bash
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manim --version # Manim CE
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pdflatex --version # LaTeX
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ffmpeg -version # ffmpeg
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```
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## CLI Reference
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```bash
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manim -ql script.py Scene1 Scene2 # draft (480p 15fps)
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manim -qm script.py Scene1 # medium (720p 30fps)
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manim -qh script.py Scene1 # production (1080p 60fps)
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manim -ql --format=png -s script.py Scene1 # preview still (last frame)
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manim -ql --format=gif script.py Scene1 # GIF output
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```
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## Quality Presets
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| Flag | Resolution | FPS | Use case |
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|------|-----------|-----|----------|
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| `-ql` | 854x480 | 15 | Draft iteration (layout, timing) |
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| `-qm` | 1280x720 | 30 | Preview (use for text-heavy scenes) |
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| `-qh` | 1920x1080 | 60 | Production |
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**Text rendering quality:** `-ql` (480p15) produces noticeably poor text kerning and readability. For scenes with significant text, preview stills at `-qm` to catch issues invisible at 480p. Use `-ql` only for testing layout and animation timing.
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## Output Structure
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```
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media/videos/script/480p15/Scene1_Intro.mp4
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media/images/script/Scene1_Intro.png (from -s flag)
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```
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## Stitching with ffmpeg
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```bash
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cat > concat.txt << 'EOF'
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file 'media/videos/script/480p15/Scene1_Intro.mp4'
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file 'media/videos/script/480p15/Scene2_Core.mp4'
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EOF
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ffmpeg -y -f concat -safe 0 -i concat.txt -c copy final.mp4
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```
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## Add Voiceover
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```bash
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# Mux narration
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ffmpeg -y -i final.mp4 -i narration.mp3 -c:v copy -c:a aac -b:a 192k -shortest final_narrated.mp4
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# Concat per-scene audio first
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cat > audio_concat.txt << 'EOF'
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file 'audio/scene1.mp3'
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file 'audio/scene2.mp3'
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EOF
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ffmpeg -y -f concat -safe 0 -i audio_concat.txt -c copy full_narration.mp3
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```
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## Add Background Music
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```bash
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ffmpeg -y -i final.mp4 -i music.mp3 \
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-filter_complex "[1:a]volume=0.15[bg];[0:a][bg]amix=inputs=2:duration=shortest" \
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-c:v copy final_with_music.mp4
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```
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## GIF Export
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```bash
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ffmpeg -y -i scene.mp4 \
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-vf "fps=15,scale=640:-1:flags=lanczos,split[s0][s1];[s0]palettegen[p];[s1][p]paletteuse" \
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output.gif
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```
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## Aspect Ratios
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```bash
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manim -ql --resolution 1080,1920 script.py Scene # 9:16 vertical
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manim -ql --resolution 1080,1080 script.py Scene # 1:1 square
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```
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## Render Workflow
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1. Draft render all scenes at `-ql`
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2. Preview stills at key moments (`-s`)
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3. Fix and re-render only broken scenes
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4. Stitch with ffmpeg
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5. Review stitched output
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6. Production render at `-qh`
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7. Re-stitch + add audio
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## manim.cfg — Project Configuration
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Create `manim.cfg` in the project directory for per-project defaults:
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```ini
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[CLI]
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quality = low_quality
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preview = True
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media_dir = ./media
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[renderer]
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background_color = #0D1117
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[tex]
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tex_template_file = custom_template.tex
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```
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This eliminates repetitive CLI flags and `self.camera.background_color` in every scene.
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## Sections — Chapter Markers
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Mark sections within a scene for organized output:
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```python
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class LongVideo(Scene):
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def construct(self):
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self.next_section("Introduction")
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# ... intro content ...
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self.next_section("Main Concept")
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# ... main content ...
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self.next_section("Conclusion")
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# ... closing ...
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```
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Render individual sections: `manim --save_sections script.py LongVideo`
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This outputs separate video files per section — useful for long videos where you want to re-render only one part.
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## manim-voiceover Plugin (Recommended for Narrated Videos)
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The official `manim-voiceover` plugin integrates TTS directly into scene code, auto-syncing animation duration to voiceover length. This is significantly cleaner than the manual ffmpeg muxing approach above.
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### Installation
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```bash
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pip install "manim-voiceover[elevenlabs]"
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# Or for free/local TTS:
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pip install "manim-voiceover[gtts]" # Google TTS (free, lower quality)
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pip install "manim-voiceover[azure]" # Azure Cognitive Services
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```
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### Usage
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```python
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from manim import *
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from manim_voiceover import VoiceoverScene
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from manim_voiceover.services.elevenlabs import ElevenLabsService
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class NarratedScene(VoiceoverScene):
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def construct(self):
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self.set_speech_service(ElevenLabsService(
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voice_name="Alice",
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model_id="eleven_multilingual_v2"
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))
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# Voiceover auto-controls scene duration
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with self.voiceover(text="Here is a circle being drawn.") as tracker:
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self.play(Create(Circle()), run_time=tracker.duration)
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with self.voiceover(text="Now let's transform it into a square.") as tracker:
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self.play(Transform(circle, Square()), run_time=tracker.duration)
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```
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### Key Features
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- `tracker.duration` — total voiceover duration in seconds
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- `tracker.time_until_bookmark("mark1")` — sync specific animations to specific words
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- Auto-generates subtitle `.srt` files
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- Caches audio locally — re-renders don't re-generate TTS
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- Works with: ElevenLabs, Azure, Google TTS, pyttsx3 (offline), and custom services
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### Bookmarks for Precise Sync
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```python
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with self.voiceover(text='This is a <bookmark mark="circle"/>circle.') as tracker:
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self.wait_until_bookmark("circle")
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self.play(Create(Circle()), run_time=tracker.time_until_bookmark("circle", limit=1))
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```
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This is the recommended approach for any video with narration. The manual ffmpeg muxing workflow above is still useful for adding background music or post-production audio mixing.
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