AI Structure Control - Precise Image Generation with ControlNet

AI Structure Control represents one of the most significant advances in AI image generation - the ability to guide generation using structural information from reference images. Using technologies like ControlNet, you can now create images that follow exact poses, maintain specific compositions, or preserve architectural layouts.

What is Structure Control?

Structure Control refers to techniques that allow you to guide AI image generation using structural information extracted from reference images. Instead of just describing what you want, you can show the AI the exact structure, pose, or composition you need.

The technology extracts:

• Edge contours and outlines
• Depth information and spatial relationships
• Human poses and body positions
• Architectural lines and perspectives
• Segmentation maps and regions

How Structure Control Works

Modern structure control uses conditioning mechanisms:

1. Extraction: Structural information is extracted from your reference image
2. Encoding: This structure is converted into a format the AI understands
3. Conditioning: The generation process is guided by this structural information
4. Generation: New content is created following the extracted structure

The result is an image that matches your creative vision while following the exact structural guidelines you provided.

Types of Structure Control

Canny Edge Detection

Uses edge outlines to guide generation:

• Preserves hard edges and contours
• Great for architectural subjects
• Maintains object boundaries
• Ideal for precise shape control

Best for: Architecture, product design, mechanical objects

Depth Maps

Uses 3D depth information:

• Preserves spatial relationships
• Maintains foreground/background separation
• Creates consistent 3D feel
• Excellent for landscapes and interiors

Best for: Landscapes, interior design, scene composition

Pose Estimation (OpenPose)

Detects human body positions:

• Captures exact poses and gestures
• Tracks multiple people
• Includes hand and face details
• Perfect for character work

Best for: Fashion, character design, action scenes

Normal Maps

Captures surface orientation:

• Preserves surface details
• Maintains 3D surface information
• Great for texture-heavy subjects

Best for: Product photography, detailed surfaces

Segmentation

Divides image into semantic regions:

• Defines areas by meaning (sky, ground, building)
• Allows region-specific generation
• Precise compositional control

Best for: Complex scenes, layout preservation

Line Art

Extracts clean linework:

• Follows artistic line drawings
• Great for illustration styles
• Preserves artistic intent

Best for: Illustration, concept art, anime style

Practical Applications

Product Visualization

• Maintain exact product shapes while changing materials
• Generate lifestyle photos keeping product position
• Create consistent product series with varying backgrounds
• Produce catalog images with uniform composition

Fashion and Character Design

• Generate clothing designs on consistent poses
• Create character variations maintaining body position
• Produce fashion lookbooks with uniform stances
• Design costumes using specific reference poses

Architecture and Interior Design

• Reimagine spaces while keeping layout
• Generate seasonal variations of buildings
• Create mood alternatives for interiors
• Produce design concepts from floor plans

Illustration and Art

• Create variations of artwork maintaining composition
• Generate style alternatives from sketches
• Produce colorizations following line art
• Transform art styles while keeping structure

Best Practices

Choosing the Right Control Type

Adjusting Control Strength

Balance structure adherence with creative freedom:

• High strength (0.8-1.0): Strict structural adherence
• Medium strength (0.5-0.7): Guided but flexible
• Low strength (0.2-0.4): Loose inspiration

Combining with Prompts

Structure control works best with complementary prompts:

• Describe the style and mood you want
• Specify materials, lighting, and atmosphere
• Let the structure handle composition
• Use prompts for aesthetic direction

Multi-Control Techniques

Combine multiple control types for precise results:

• Depth + Canny for architectural precision
• Pose + Depth for character in environment
• Segmentation + Line for illustrated scenes

Structure Control vs Other Tools

Integration with Pixelift Workflow

Pixelift's Structure Control integrates with other tools:

• Pre-processing: Upscale reference images for better extraction
• Combination: Use with Style Transfer for styled structure
• Post-processing: Inpaint to refine specific areas
• Finishing: Upscale final results for production

Technical Tips

Preparing Reference Images

• Use clear, high-contrast images for edge detection
• Ensure good lighting for depth estimation
• Position subjects clearly for pose detection
• Crop to focus on relevant structure

Troubleshooting Common Issues

• Result too rigid: Lower control strength
• Structure not followed: Increase strength or use cleaner reference
• Artifacts at edges: Try different control type
• Pose incorrect: Use clearer reference with visible joints

Getting Started

Ready for precise control? Pixelift's Structure Control offers:

• Multiple control types (edge, depth, pose)
• Adjustable control strength
• Prompt-guided generation
• High-quality output
• Fast processing

Take complete control of your AI-generated images.

Summary

AI Structure Control transforms how you work with generative AI:

• Guide generation with exact structural references
• Maintain compositions while changing content
• Create consistent series with structural guidelines
• Combine multiple control types for precision
• Balance structure with creative freedom

Whether you're designing products, creating characters, or reimagining architecture, Structure Control gives you the precision you need while leveraging AI's creative power.