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name: image-stylization description: "Build and run single-image neural-style-tf stylization commands from content/style paths, VGG weights, device, optimizer, image-size, and output controls." disable-model-invocation: true metadata: disco-role: operating license: GPL 3.0

image-stylization

Use this sub-skill when the user needs a single-image neural_style.py run: choose content/style image paths, pass VGG-19 weights, select CPU/GPU, tune image size or optimizer iterations, choose initialization, and locate the output bundle.

Do not use this sub-skill for:

• masks, original-colors, layer weights, or multi-style weighting/interpolation; use advanced-controls.
• video frames, optical flow, or stylize_video.sh; use video-stylization.
• install/import/runtime setup or VGG download policy; use the root runtime notes and root troubleshooting, then return here for image commands.

Operating route

1. Work from the repository checkout root. This repository is script-style, not an installable package; run python neural_style.py ... rather than importing a package.
2. Prefer the bundled non-interactive command builder over stylize_image.sh when the user gives content/style file paths:
   • scripts/build_image_command.py validates content/style/script paths, derives --content_img_dir, --content_img, --style_imgs_dir, and --style_imgs, prints an argv-safe command, and only executes when --run is explicitly supplied.
3. For concrete recipes and output layout, open references/workflows.md.
4. For verified parser defaults and important single-image flags, open references/output-and-parameters.md.
5. For failures involving TensorFlow v1, protobuf, VGG .mat, image reads, CPU/GPU, memory, shell prompts, ~ paths, or missing outputs, open references/troubleshooting.md.

Required inputs for a normal image run

• neural_style.py reachable as a file, usually from the checkout root.
• One readable content image path.
• At least one readable style image path; one style is the normal path here.
• VGG-19 MatConvNet weights (imagenet-vgg-verydeep-19.mat) in the working directory or passed via --model_weights/builder --model-weights.
• A TensorFlow 1.x-compatible runtime with tf.Session and tf.contrib.opt.ScipyOptimizerInterface for L-BFGS runs.

Full stylized renders require the external VGG weights and are not assumed available by this sub-skill. The verified local evidence for this generated skill covered CLI help/import-level behavior, source inspection, and command construction rather than a full render.