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--- |
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license: other |
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license_name: flux-1-dev-non-commercial-license |
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license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md |
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language: |
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- en |
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library_name: diffusers |
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pipeline_tag: text-to-image |
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tags: |
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- Text-to-Image |
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- ControlNet |
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- Diffusers |
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- Flux.1-dev |
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- image-generation |
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- Stable Diffusion |
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base_model: black-forest-labs/FLUX.1-dev |
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--- |
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# FLUX.1-dev-ControlNet-Depth |
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This repository contains a Depth ControlNet for FLUX.1-dev model jointly trained by researchers from [InstantX Team](https://huggingface.co/InstantX) and [Shakker Labs](https://huggingface.co/Shakker-Labs). |
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<div class="container"> |
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<img src="./assets/poster.png" width="1024"/> |
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</div> |
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# Model Cards |
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- The model consists of 4 FluxTransformerBlock and 1 FluxSingleTransformerBlock. |
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- This checkpoint is trained on both real and generated image datasets, with 16\*A800 for 70K steps. The batch size 16\*4=64 with resolution=1024. The learning rate is set to 5e-6. We use [Depth-Anything-V2](https://github.com/DepthAnything/Depth-Anything-V2) to extract depth maps. |
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- The recommended controlnet_conditioning_scale is 0.3-0.7. |
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# Showcases |
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<div class="container"> |
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<img src="./assets/teaser.png" width="1024"/> |
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</div> |
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# Inference |
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```python |
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import torch |
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from diffusers.utils import load_image |
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from diffusers import FluxControlNetPipeline, FluxControlNetModel |
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controlnet_model = "black-forest-labs/FLUX.1-dev" |
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base_model = "Shakker-Labs/FLUX.1-dev-ControlNet-Depth" |
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controlnet = FluxControlNetModel.from_pretrained(controlnet_model, torch_dtype=torch.bfloat16) |
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pipe = FluxControlNetPipeline.from_pretrained( |
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base_model, controlnet=controlnet, torch_dtype=torch.bfloat16 |
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) |
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pipe.to("cuda") |
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control_image = load_image("https://huggingface.co/Shakker-Labs/FLUX.1-dev-ControlNet-Depth/resolve/main/assets/cond1.png") |
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prompt = "an old man with white hair" |
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image = pipe(prompt, |
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control_image=control_image, |
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controlnet_conditioning_scale=0.5, |
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width=control_image.size[0], |
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height=control_image.size[1], |
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num_inference_steps=24, |
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guidance_scale=3.5, |
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).images[0] |
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``` |
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For multi-ControlNets support, please refer to [Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro](https://huggingface.co/Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro). |
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# Resources |
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- [InstantX/FLUX.1-dev-Controlnet-Canny](https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Canny) |
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- [Shakker-Labs/FLUX.1-dev-ControlNet-Depth](https://huggingface.co/Shakker-Labs/FLUX.1-dev-ControlNet-Depth) |
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- [Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro](https://huggingface.co/Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro) |
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# Acknowledgements |
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This project is sponsored and released by [Shakker AI](https://www.shakker.ai/). All copyright reserved. |
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