Omni Reference
Transform your images using Omni Reference technology. Extract characters, objects, and styles from reference images for accurate AI image generation.
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Omni Reference Examples
Prompt: a giant rubber duck with a top hat and bow tie floating on a city river, European architecture in the background, sunset lighting, detailed reflections, photorealistic style.
Prompt: A side shot of a girl drinking.
Prompt: A vintage green sofa with wooden armrests, identical to the original design, placed in an abandoned scrapyard filled with rusty cars and scattered debris. The sofa is slightly worn and dusty, blending naturally into the environment. A golden retriever sits proudly on the sofa, looking directly at the viewer. The scene is illuminated by a warm, golden sunset, casting long shadows and giving the setting a nostalgic and cinematic atmosphere. The background features blurred details of the scrapyard, emphasizing depth and realism.
Frequently Asked Questions
Get answers to common questions about Omni Reference. If you have any other questions, please contact us at [email protected]
What is Omni Reference?
Omni Reference is an advanced AI feature that allows you to extract and preserve specific visual elements from your reference images. It helps maintain consistency in character appearance, object details, and artistic styles when generating new AI images.
How do I use Omni Reference?
Using Omni Reference is simple: 1) Upload your reference image(s), 2) Enter your prompt describing how you want to modify the image, 3) Click 'Generate' button to start the process. The generation typically takes about 3 minutes to complete.
What's the difference between Omni Reference and regular image generation?
Omni Reference specializes in preserving and transforming specific elements from your reference images while allowing creative modifications. Unlike regular image generation that creates images from scratch, Omni Reference ensures key visual features from your reference are maintained in the final output.
What are the best practices for reference images?
For best Omni Reference results: Use clear, high-quality images with simple backgrounds. Ensure your target elements are clearly visible. You can use multiple reference images for different elements. The reference images should have good lighting and resolution.
Why might my Omni Reference not work as expected?
Common issues include: unclear reference images, complex backgrounds interfering with element extraction, conflicting prompts, or trying to preserve too many elements at once. Try using simpler reference images or focusing on fewer specific elements per generation.
How can I improve my Omni Reference results?
To optimize results: 1) Use high-quality reference images with clear subjects, 2) Write specific prompts about which elements to preserve, 3) Combine with other parameters thoughtfully, 4) Start with single references before attempting multiple references, 5) Experiment with different prompt formulations to guide the AI's focus.