Patterned light projection

Start with the right photo.

An interior with a broad wall and visible window for a readable projected light pattern.

What to expect

Project a crisp repeated geometric leaf pattern of sunlight and shade onto the back wall and floor, as if a patterned screen were outside the existing left window.

Keep an eye on

A single view cannot establish measurements or hidden construction. Check furniture count and window alignment.

Make it yours, step by step.

1. Adjust the recipe to describe your subject and preferred background.
2. Copy the complete recipe, then open ChatGPT.
3. Upload your photo in ChatGPT and paste the recipe. The short code alone is not an official command.
4. Inspect identity, text and proportions. Ask for a targeted correction if needed.

Choose the change deliberately.

A projected pattern should bend and soften across surfaces according to their position. Choose one readable pattern so the room remains the subject rather than a wall of decoration.

Review and refine the result

Inspect furniture edges where the projection crosses them. If the pattern looks pasted on, ask for light falloff and surface-aware distortion. Keep windows and existing light sources consistent.

A related direction, and why

/SHADOWPLAY — Shadow-led composition can create graphic structure without a recognizable projected pattern.

These are editing suggestions, not additional test observations. Read the practical guide or use the before/after checklist.

Where this effect helps — and its limits.

Project a crisp repeated geometric leaf pattern of sunlight and shade onto the back wall and floor, as if a patterned screen were outside the existing left window. A single view cannot establish measurements or hidden construction. Check furniture count and window alignment.

Input advice and use cases are editorial guidance, not additional test results.

Notes from recorded tests.

These notes describe the named runs, which may use a different subject from the comparison above. They do not guarantee results on another input or a future model. See our testing method.