FLUX.1-dev ControlNet Inpainting - Beta

🔥News!

• [2024.10.16] We release a 8-step FLUX.1 distilled lora alimama-creative/FLUX.1-Turbo-Alpha, which is compatible with our Inpainting Controlnet.

Key Enhancements

1. 1024 Resolution Support: Capable of directly processing and generating 1024x1024 resolution images without additional upscaling steps, providing higher quality and more detailed output results.
2. Enhanced Detail Generation: Fine-tuned to capture and reproduce finer details in inpainted areas.
3. Improved Prompt Control: Offers more precise control over generated content through enhanced prompt interpretation.

Showcase

Prompt : 'Write a few lines of words "alimama creative" on the wooden board'

Prompt : "a girl with big beautiful white wing"

Prompt : "red hair"

Prompt : " "

Prompt : "Albert Einstein"

Prompt : "Ravello Outdoor Sectional Sofa Set with Coffee Table"

ComfyUI Usage Guidelines:

• Using t5xxl-FP16 and flux1-dev-fp8 models for 30-step inference @1024px & H20 GPU:
  • GPU memory usage: 27GB
  • Inference time: 48 seconds (true_cfg=3.5), 26 seconds (true_cfg=1)
• Different results can be achieved by adjusting the following parameters:

• More comprehensive full-image prompts can lead to better overall results. For example, in addition to describing the area to be repaired, you can also describe the background, atmosphere, and style of the entire image. This approach can make the generated results more harmonious and natural.

Diffusers Integration

1. Install the required diffusers version:

1. Clone this repository:

1. Configure image_path, mask_path, and prompt in main.py, then execute:

Model Specifications

• Training dataset: 15M images from LAION2B and proprietary sources
• Optimal inference resolution: 1024x1024

License