Update README.md

README.md

@@ -11,4 +11,71 @@ tags:
 - ComfyUI
 - Inpainting
 library_name: diffusers
----
+---
+
+<div style="display: flex; justify-content: center; align-items: center;">
+  <img src="images/alibaba.png" alt="alibaba" style="width: 20%; height: auto; margin-right: 5%;">
+  <img src="images/alimama.png" alt="alimama" style="width: 20%; height: auto;">
+</div>
+
+# FLUX.1-dev ControlNet Inpainting - Beta
+
+This repository hosts an improved Inpainting ControlNet checkpoint for the [FLUX.1-dev](https://huggingface.co/black-forest-labs/FLUX.1-dev) model, developed by the AlimamaCreative Team.
+
+## Key Enhancements
+
+Our latest inpainting model brings significant improvements compared to the previous version:
+
+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
+
+The following images were generated using a ComfyUI workflow with these settings (click here to download):
+`control-strength` = 1.0, `control-end-percent` = 1.0, `true_cfg` = 1.0
+
+| Image & Prompt Input | Alpha Version | Beta Version |
+|:---:|:---:|:---:|
+| ![Input Image](path/to/original_image.jpg) A > B | ![Alpha](path/to/old_model_result.jpg) | ![Beta](path/to/new_model_result.jpg) |
+
+### ComfyUI Usage Guidelines:
+
+Download example ComfyUI workflow [here](https://huggingface.co/alimama-creative/FLUX.1-dev-Controlnet-Inpainting-Alpha/resolve/main/images/alimama-flux-controlnet-inpaint.json).
+
+- Using `t5xxl-FP16` and `flux1-dev-fp8` models for 28-step inference:
+  - GPU memory usage: 27GB
+  - Inference time: 27 seconds (cfg=3.5), 15 seconds (cfg=1)
+- For optimal results, experiment with lower values for `control-strength`, `control-end-percent`, and `cfg
+
+| Parameter | Recommended Range | Effect |
+|-----------|------------------|--------|
+| control-strength | 0.0 - 1.0 | Controls how much influence the ControlNet has on the generation. Higher values result in stronger adherence to the control image. |
+| control-end-percent | 0.0 - 1.0 | Determines at which point in the denoising process the ControlNet influence ends. Lower values allow for more creative freedom in later steps. |
+| cfg (Classifier-Free Guidance Scale) | 1.0 - 30.0 | Influences how closely the generation follows the prompt. Higher values increase prompt adherence but may reduce image quality. |
+
+## Model Specifications
+
+- Training dataset: 15M images from LAION2B and proprietary sources
+- Optimal inference resolution: 1024x1024
+
+## Diffusers Integration
+
+1. Install the required diffusers version:
+```shell
+pip install diffusers==0.30.2
+```
+
+2. Clone this repository:
+````shell
+git clone https://github.com/alimama-creative/FLUX-Controlnet-Inpainting.git
+````
+
+3. Configure `image_path`, `mask_path`, and `prompt` in `main.py`, then execute:
+````shell
+python main.py
+````
+
+## License
+
+Our model weights are released under the [FLUX.1 [dev]](https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md) Non-Commercial License.