Computer vision
Control the transformation. Inspect the result. Explore image generation, image-to-image translation, semantic layouts, super resolution, and style transfer. These workflows share visual outputs but differ in what their inputs mean and what an acceptable result must preserve.
Choose a guide based on the operation, not merely the file type. Latent generation creates new samples; translation changes a supplied representation; restoration and stylization add their own fidelity requirements. Compare against a relevant baseline and keep the generated artifact distinguishable from an original observation.
Image Translation and Semantic Layouts: Preserve What Matters
Compare image-to-image and layout-conditioned workflows, with explicit class maps, alignment rules, and preservation tests.
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Super Resolution: Better-Looking Is Not Always More Faithful
Evaluate upscaling with honest baselines, realistic inputs, artifact review, and a clear distinction between inferred and observed detail.
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Style Transfer APIs: Change the Look, Preserve the Brief
Build a domain-based stylization workflow with supported controls, explicit preservation rules, and useful creative review.
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Image Generation APIs: Seeds, Latent Controls, and Reproducibility
Expose controls that match the checkpoint, preserve artifact provenance, and evaluate diversity alongside visual quality.
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