conditional control inputs

**Conditional control inputs** is the **external signals that guide generation toward specified structure, geometry, or appearance constraints** - they extend text prompting with explicit visual controls for more deterministic outcomes. **What Is Conditional control inputs?** - **Definition**: Includes edge maps, depth maps, poses, masks, normals, and reference features. - **Injection Paths**: Condition inputs are fused through control branches, attention layers, or adapter modules. - **Precision Role**: Provide spatial and geometric information that text alone cannot express reliably. - **Workflow Scope**: Used in text-to-image, img2img, inpainting, and video generation systems. **Why Conditional control inputs Matters** - **Determinism**: Improves repeatability for enterprise and design use cases. - **Quality Control**: Reduces semantic drift and off-layout failures in complex scenes. - **Task Fit**: Different control inputs support different constraints, such as pose versus depth. - **Efficiency**: Cuts prompt trial cycles by constraining generation early. - **Integration Risk**: Mismatched control resolution or scale can degrade outputs. **How It Is Used in Practice** - **Input Validation**: Check alignment, normalization, and resolution before inference. - **Control Selection**: Choose the minimal control set needed for the target constraint. - **Policy Testing**: Monitor failure rates when combining multiple control modalities. Conditional control inputs is **a core mechanism for predictable controllable generation** - conditional control inputs should be treated as first-class model inputs with dedicated QA.