---

name: video-stylization description: "Guides Fast Style Transfer transform_video.py and ffwd_video checkpoint-based video stylization, moviepy/ffmpeg checks, device/batch choices, and video troubleshooting." disable-model-invocation: true metadata: disco-role: operating license: CC BY-NC 4.0

Video Stylization

Use this sub-skill when the user has a trained Fast Style Transfer checkpoint and wants to apply it to a video, or when they need to debug moviepy, ffmpeg, video input/output, checkpoint restore, device, batch-size, or performance problems.

Read and run

• Read references/video-stylization-workflow.md for command recipes, prerequisites, checkpoint handoff, frame batching behavior, CPU/GPU caveats, and output validation.
• Read references/cli-reference.md for verified the bundled video stylization runtime flags and evaluate.ffwd_video behavior.
• Read references/troubleshooting.md for checkpoint, moviepy, ffmpeg, codec/audio, output path, memory, and backend failures.
• Run scripts/validate_video_stylization_inputs.py before processing frames. It checks paths, dependency availability, optional video metadata, and option semantics without restoring checkpoints or writing video.

When to use this route

Use this route for requests like:

• "Stylize an MP4 with a Fast Style Transfer checkpoint."
• "Check whether moviepy/ffmpeg are ready before running the bundled video stylization runtime."
• "Run video stylization on CPU because TensorFlow GPU is unavailable."
• "Why did video encoding or audio handling fail?"
• "How should I choose --batch-size for frames?"

Route away when:

• The user needs to create a checkpoint first: ../training/SKILL.md
• The user needs still-image or image-directory stylization: ../image-stylization/SKILL.md

Command pattern

python sub-skills/video-stylization/scripts/run_video_stylization.py \
  --checkpoint checkpoints/udnie \
  --in-path content/input.mp4 \
  --out-path outputs/input_udnie.mp4 \
  --device /gpu:0 \
  --batch-size 4

CPU debug pattern:

python sub-skills/video-stylization/scripts/run_video_stylization.py \
  --checkpoint checkpoints/udnie \
  --in-path content/input.mp4 \
  --out-path outputs/input_udnie.mp4 \
  --device /cpu:0 \
  --batch-size 1

Preflight:

python sub-skills/video-stylization/scripts/validate_video_stylization_inputs.py \
  --checkpoint checkpoints/udnie \
  --in-path content/input.mp4 \
  --out-path outputs/input_udnie.mp4 \
  --device /cpu:0 \
  --batch-size 1 \
  --check-dependencies \
  --probe-video

Behavior facts

• the bundled video stylization runtime is a thin wrapper around evaluate.ffwd_video.
• evaluate.ffwd_video opens the input through moviepy, creates an ffmpeg writer, batches frames, runs the transform network, clips predictions to uint8, and writes output frames.
• The repository implementation opens the input video with audio=False while the ffmpeg writer passes audiofile=path_in; audio/container behavior can therefore depend on moviepy/ffmpeg compatibility.
• Default CLI device is /gpu:0; CPU works for small debugging but is usually slow for real videos.
• The parsed --tmp-dir and --no-disk options are documented parser surfaces, but the inspected main() calls evaluate.ffwd_video directly and does not use them for a disk-frame workflow.

Validation limits

The bundled validator can check path existence, dependency imports, optional video metadata, output parent directory, device string, and batch-size sanity. It cannot prove checkpoint compatibility, frame-by-frame TensorFlow inference, codec support for every output container, or acceptable runtime performance.