---

name: inference description: "Restore single images from DeblurGAN checkpoints and export HTML results." metadata: disco-role: operating disable-model-invocation: true license: NOASSERTION

inference

Use this sub-skill when the task is to restore or inspect images with a trained DeblurGAN checkpoint.

What this route covers

• Single-image inference with model=test and dataset_mode=single.
• Checkpoint lookup and result-directory layout.
• HTML output generation for restored images.
• CPU fallback for inference with --gpu_ids -1.
• A wrapper that avoids the source script's brittle external ssim import path.

Read this when the user asks for

• A command to deblur one image folder with a trained checkpoint.
• Help finding latest_net_G.pth or choosing the right epoch label.
• A safe CPU inference command.
• A way to inspect or save the generated HTML results.

Primary files

• scripts/run_inference.py — portable wrapper around the repository's test-time pipeline.
• references/workflows.md — command patterns, result paths, and CPU fallback notes.
• references/troubleshooting.md — checkpoint, import, and folder-layout failures.

Workflow summary

1. Point the run at a folder of standalone images.
2. Choose the checkpoint directory and epoch label.
3. Use model=test with dataset_mode=single and, for headless runs, --gpu_ids -1.
4. Save the generated HTML and PNGs under the results directory.
5. If you want a smoke-style run, keep how_many small and use a tiny image folder.

Decision points

• If the task is about building the dataset rather than restoring images, route back to data-preparation.
• If the task is about optimizing weights or resuming training, route to training.
• If the user wants the exact source test.py behavior, remember that the shipped script imports ssim directly; the wrapper avoids that brittle path.

Important reminders

• The inference wrapper creates the checkpoint directory before the visualizer is constructed.
• The wrapper defaults to a headless-friendly display setting so the run does not depend on visdom.
• The repository's TestModel expects single dataset mode and a generator checkpoint with the requested epoch label.

Cross-links

• Read the root installation reference if torch, torchvision, or the optional compatibility packages are missing.
• Read the root troubleshooting reference for checkpoint naming and source-script mismatches.
• Read the data-preparation sub-skill first if you still need to build the input image folder.