Video Production Strategies Using Image Sequences
summary
Shows how Python turns folders of numbered images into finished video using ffmpeg + ImageMagick and libraries like pySVG, cairo, PIL and numpy; demonstrates rasterizing SVG turtle frames, plotting bus GPS updates into per-minute frames, and assembling a year of forum threads into ~10,000 images processed in parallel on 30–40 EC2 instances (cost ≈ $5). Mixdown and frame-rate fixes (60→30 fps, duplicate last frame) are required; outputs work with some encoding glitches handled by simple scripting.
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chapters (19)
- 0:00Intro
- 0:59Video
- 2:02Image Sequences
- 2:36Video Files
- 4:10Video Sources
- 4:36Video Problems
- 6:09Nonlinear Video Editors
- 7:19Image Sequences Integration
- 8:57What is an Image
- 10:51Frame Rates
- 12:32Streams
- 13:48Python
- 14:47Logistic Operations
- 16:38Creative Content
- 19:16Primitive Operations
- 19:55Examples
- 20:50Code
- 25:28Video Example
- 35:54Other Ideas
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