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README.md
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@@ -11,23 +11,18 @@ base_model: black-forest-labs/FLUX.1-dev
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# FLUX.1-dev
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<img src="./images/image_union.png" width = "1000" />
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## Release
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- [2024/08/
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Until the next Diffusers pypi release,
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please install Diffusers from source and use [this PR](https://github.com/huggingface/diffusers/pull/9175) to be able to use.
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Before merging into the official main branch of diffusers, you can use this [diffusers_flux](https://github.com/instantX-research/diffusers_flux).
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- [2024/08/14] Release the alpha version.
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@@ -56,63 +51,27 @@ However, as training progresses, the performance of the Union model will continu
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|6|lq|🟢high|
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# Demo
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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
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from diffusers.models.controlnet_flux import FluxControlNetModel
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# load
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base_model = 'black-forest-labs/FLUX.1-dev'
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controlnet_model = 'InstantX/FLUX.1-dev-Controlnet-Union'
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controlnet = FluxControlNetModel.from_pretrained(controlnet_model, torch_dtype=torch.bfloat16)
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pipe = FluxControlNetPipeline.from_pretrained(base_model, controlnet=controlnet, torch_dtype=torch.bfloat16)
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pipe.to("cuda")
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width, height = 1024, 1024
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controlnet_conditioning_scale = 0.5
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seed = 6666
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# canny
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control_image = load_image("https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Union-alpha/resolve/main/images/canny.jpg")
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prompt = "A girl in city, 25 years old, cool, futuristic."
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control_mode = 0
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prompt =
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# depth
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control_image = load_image("https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Union-alpha/resolve/main/images/depth.jpg")
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prompt = "A girl in city, 25 years old, cool, futuristic."
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control_mode = 2
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# blur
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control_image = load_image("https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Union-alpha/resolve/main/images/blur.jpg")
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prompt = "A girl, 25 years old."
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control_mode = 3
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# pose
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control_image = load_image("https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Union-alpha/resolve/main/images/pose.jpg")
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prompt = "A girl in city, 25 years old, cool, futuristic."
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control_mode = 4
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# gray
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control_image = load_image("https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Union-alpha/resolve/main/images/gray.jpg")
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prompt = "A girl, 25 years old."
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control_mode = 5
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# low quality
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control_image = load_image("https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Union-alpha/resolve/main/images/lq.jpg")
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prompt = "A girl in city"
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control_mode = 6
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# go go go
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image = pipe(
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prompt,
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control_image=control_image,
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width=width,
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height=height,
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controlnet_conditioning_scale=controlnet_conditioning_scale,
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num_inference_steps=
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guidance_scale=3.5,
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generator=torch.manual_seed(seed),
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).images[0]
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image.save("image.jpg")
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```
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# FLUX.1-dev-Controlnet-Union
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<img src="./images/image_union.png" width = "1000" />
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## Release
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- [2024/08/26] 🔥 Release [FLUX.1-dev-ControlNet-Union-Pro](https://huggingface.co/Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro). Please install from [the source](https://github.com/huggingface/diffusers) before the next release. We have supported CN-Union and Multi-ControlNets via [this PR](https://github.com/huggingface/diffusers/pull/9175).
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- [2024/08/20] Release the beta version.
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- [2024/08/14] Release the alpha version.
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|6|lq|🟢high|
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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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base_model = 'black-forest-labs/FLUX.1-dev'
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controlnet_model = 'InstantX/FLUX.1-dev-Controlnet-Union'
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controlnet = FluxControlNetModel.from_pretrained(controlnet_model, torch_dtype=torch.bfloat16)
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pipe = FluxControlNetPipeline.from_pretrained(base_model, controlnet=controlnet, torch_dtype=torch.bfloat16)
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pipe.to("cuda")
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control_image_canny = load_image("https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Union-alpha/resolve/main/images/canny.jpg")
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controlnet_conditioning_scale = 0.5
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control_mode = 0
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width, height = control_image.size
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prompt = 'A bohemian-style female travel blogger with sun-kissed skin and messy beach waves.'
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image = pipe(
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prompt,
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control_image=control_image,
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width=width,
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height=height,
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controlnet_conditioning_scale=controlnet_conditioning_scale,
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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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image.save("image.jpg")
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```
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# Multi-Controls 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, FluxMultiControlNetModel
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base_model = 'black-forest-labs/FLUX.1-dev'
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controlnet_model_union = './InstantX/FLUX.1-dev-Controlnet-Union'
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controlnet_union = FluxControlNetModel.from_pretrained(controlnet_model_union, torch_dtype=torch.bfloat16)
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controlnet = FluxMultiControlNetModel([controlnet_union]) # we always recommend loading via FluxMultiControlNetModel
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pipe = FluxControlNetPipeline.from_pretrained(base_model, controlnet=controlnet, torch_dtype=torch.bfloat16)
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pipe.to("cuda")
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prompt = 'A bohemian-style female travel blogger with sun-kissed skin and messy beach waves.'
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control_image_depth = load_image("https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Union/resolve/main/images/depth.jpg")
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control_mode_depth = 2
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control_image_canny = load_image("https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Union/resolve/main/images/canny.jpg")
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control_mode_canny = 0
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width, height = control_image.size
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image = pipe(
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prompt,
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control_image=[control_image_depth, control_image_canny],
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control_mode=[control_mode_depth, control_mode_canny],
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width=width,
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height=height,
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controlnet_conditioning_scale=[0.2, 0.4],
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num_inference_steps=24,
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guidance_scale=3.5,
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generator=torch.manual_seed(42),
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).images[0]
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```
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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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- [InstantX/FLUX.1-dev-Controlnet-Union](https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Union)
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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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Thanks [zzzzzero](https://github.com/zzzzzero) for help us pointing out some bugs in the training.
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