Flux Depth Dev leverages state-of-the-art algorithms to generate highly realistic and creative visuals. By combining textual descriptions with optional image inputs, it adapts to a wide range of use cases, from artistic endeavors to professional applications.

Generative Framework: Utilizes a robust architecture optimized for image-guided generation.

High Customizability: Offers adjustable parameters like resolution, guidance scale, and output format to meet diverse requirements.

Higher resolution or multiple outputs significantly increase processing time.

Disabling the safety checker should only be done with caution, as it may generate unexpected results.

Extremely high values for guidance may limit the model's creative flexibility.

Legal Information

By using this model, you agree to:

• Black Forest Labs API agreement
• Black Forest Labs Terms of Service

Optimal guidance Values: Start with 7-10 for a balanced blend of creativity and adherence.

Seed Control: Randomize for exploration, then fix a seed for consistency.

Megapixels for Print: Choose higher values for projects needing physical prints.

Clarity in Prompts: Be concise and vivid when describing your desired output. Avoid ambiguous language.

Configuring steps: Start with moderate values like 20 and adjust upward for more intricate outputs.

Safety Checker: For experimental designs, disabling the safety checker may enable unrestricted creativity but review outputs for suitability.

Photo-realistic imagery.

Abstract designs and creative compositions.

Personalized visuals through image blending.

High-resolution outputs for print-quality projects.

Creating concept art and storyboards.

Generating unique visual assets for marketing and branding.

Experimenting with artistic styles for personal or professional projects.

Control the Degree of Guidance:

• Adjusting how much influence the model should give to the provided prompt can drastically alter the output. With higher guidance values, the model will focus more on the prompt details, producing more accurate depth maps based on the input description. Lower guidance values may yield softer, more interpretative results. Testing different levels of guidance will help find the perfect balance between control and creativity.

Quality vs. Speed Trade-off:

• If time is a factor, consider adjusting the quality of the output. Lower quality may produce faster results, while higher quality settings lead to more refined and detailed outputs but require more time to process. Experiment with different quality settings to find the optimal speed and accuracy for your needs.

Resolution and Detail:

• Experimenting with different resolution settings will allow you to control the level of detail in the depth map. Higher resolution outputs (larger megapixel settings) will generate more detailed depth maps but will also take more time. Try testing different resolutions to balance processing time and quality.

Use Control Images for Better Accuracy:

• If you're working with a particular scene or environment, uploading a reference or control image can greatly improve the accuracy of the depth map. The model will be able to better understand the context and generate depth information that aligns with the control image.

Adjusting Inference Steps for Detail:

• The number of inference steps plays a crucial role in determining how detailed the output will be. Increasing the number of inference steps typically results in a more refined depth map, while lower steps may produce faster but less detailed outputs. Experiment with this setting to find the ideal balance between speed and quality.

May struggle with extremely complex or abstract prompts.

Outputs can take longer to render due to resource intensity at high settings

Output Format: WEBP,JPG,PNG