Flux Controlnet
Flux Controlnet provides precise adjustments for image generation tasks, enhancing creativity and control.
Official Partner
Avg Run Time: 39.000s
Model Slug: flux-dev-controlnet
Category: Image to Image
Input
Enter an URL or choose a file from your computer.
Click to upload or drag and drop
image/jpeg, image/png, image/jpg, image/webp (Max 50MB)
Output
Example Result
Preview and download your result.
Create a Prediction
Send a POST request to create a new prediction. This will return a prediction ID that you'll use to check the result. The request should include your model inputs and API key.
Get Prediction Result
Poll the prediction endpoint with the prediction ID until the result is ready. The API uses long-polling, so you'll need to repeatedly check until you receive a success status.
Overview
Flux Controlnet is a cutting-edge model designed for generating high-quality images with precision and customization. By utilizing various preprocessor settings, control types, and parameter adjustments, users can achieve detailed and creative outputs tailored to their specific needs. This document provides essential details to help users effectively interact with Flux Controlnet, understand its capabilities, and optimize their usage.
Technical Specifications
Control Types:
- Canny: Detects edges in images, focusing on clear outlines.
- Soft Edge: Captures smoother edges for a softer and more artistic style.
- Depth: Utilizes depth-based processing for a more realistic 3D-like rendering.
Preprocessors:
- Depth Preprocessors: Midas, Zoe, DepthAnything, Zoe-DepthAnything.
- Soft Edge Preprocessors: HED, TEED, PiDiNet.
Customizable Parameters for Flux Controlnet:
- Guidance Scale: Defines the adherence to the input prompt .
- Steps: Determines the number of iterations for image generation .
- Control Strength: Adjusts the effect strength of the control type.
- Image-to-Image Strength: Balances between original input image and generated transformations .
Key Considerations
Prompt Quality for Flux Controlnet: Ensure the prompt is descriptive and relevant to your desired output. Avoid vague descriptions for better results.
Control Image: When using control_image, provide high-quality images that match the control type (e.g., clear edges for canny).
Preprocessor Compatibility: Select preprocessors that align with your control type. For example, use HED or PiDiNet with Soft Edge.
Lora Parameters: Use lora_strength and lora_url to incorporate specific weights or styles for further customization.
Tips & Tricks
- Guidance Scale:
- Use lower values (e.g., 1-2) for more freedom in artistic creativity.
- Higher values (e.g., 4-5) ensure stronger adherence to the prompt but might limit flexibility.
- Steps:
- For quick drafts or initial ideas, set steps between 5-15.
- For detailed results, use higher values like 30-50, keeping in mind that processing time increases with higher steps.
- Control Strength:
- Set to 1 for a balanced effect.
- Use values closer to 3 for more pronounced control but avoid overuse as it may distort the image.
- Image-to-Image Strength:
- Keep values near 0.5 for a balanced blend between the input and generated image.
- Lower values (e.g., 0.2) prioritize the generated content, while higher values (e.g., 0.8) retain more of the original image.
- Depth Preprocessors:
- Use Midas for general depth mapping.
- Select Zoe or DepthAnything for scenes with complex layers.
- Soft Edge Preprocessors:
- Choose HED for clean and defined edges.
- Use TEED or PiDiNet for a softer, stylized edge effect.
- Lora Strength:
- Start with a value of 2 for balanced adjustments.
- Increase to 3 for stronger stylistic emphasis.
- Output Quality:
- For web usage, values between 70-85 are sufficient.
- For detailed prints or high-resolution purposes, set values closer to 100.
Capabilities
Flux Controlnet generates photorealistic images with enhanced depth and edge controls.
Stylized outputs by leveraging lora_url for external weight influences.
Balancing creativity and precision through a wide range of customizable inputs.
What Can I Use It For?
Creating customized artwork with precise depth and edge control.
Enhancing existing images by applying transformations and refinements.
Developing assets for creative projects, including visual storytelling and design with Flux Controlnet.
Things to Be Aware Of
Combine soft_edge with HED for a clean, comic-style effect.
Experiment with DepthAnything in complex landscapes to highlight depth details.
Use a high image_to_image_strength value (e.g., 0.9) for minor touch-ups on existing images.
Limitations
Excessively high steps or guidance_scale values may result in processing delays or unnatural outputs.
Compatibility between control_type and preprocessors must be carefully managed to avoid suboptimal results.
Lower quality control images may lead to poor image outputs, even with optimized parameters.
Output Format: WEBP,JPG,PNG
Pricing Detail
This model runs at a cost of $0.001540 per second.
The average execution time is 39 seconds, but this may vary depending on your input data.
The average cost per run is $0.060060
Pricing Type: Execution Time
Cost Per Second means the total cost is calculated based on how long the model runs. Instead of paying a fixed fee per run, you are charged for every second the model is actively processing. This pricing method provides flexibility, especially for models with variable execution times, because you only pay for the actual time used.
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