Image-to-Image
Diffusers
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Update README.md

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by hlky HF staff - opened
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  1. README.md +46 -1
README.md CHANGED
@@ -36,9 +36,10 @@ Also, some generation results with input images are provided in "Files and versi
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  # Inference
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- To try our models, you have 2 options:
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  1. Use main.py from our [official repo](https://github.com/XLabs-AI/x-flux)
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  2. Use our custom nodes for ComfyUI and test it with provided workflows (check out folder /workflows)
 
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  ## Instruction for ComfyUI
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  1. Go to ComfyUI/custom_nodes
@@ -50,6 +51,50 @@ To try our models, you have 2 options:
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  7. Use `Flux Load IPAdapter` and `Apply Flux IPAdapter` nodes, choose right CLIP model and enjoy your genereations.
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  8. You can find example workflow in folder workflows in this repo.
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  If you get bad results, try to set to play with ip strength
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  ### Limitations
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  The IP Adapter is currently in beta.
 
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  # Inference
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+ To try our models, you have 3 options:
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  1. Use main.py from our [official repo](https://github.com/XLabs-AI/x-flux)
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  2. Use our custom nodes for ComfyUI and test it with provided workflows (check out folder /workflows)
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+ 3. Diffusers 🧨
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  ## Instruction for ComfyUI
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  1. Go to ComfyUI/custom_nodes
 
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  7. Use `Flux Load IPAdapter` and `Apply Flux IPAdapter` nodes, choose right CLIP model and enjoy your genereations.
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  8. You can find example workflow in folder workflows in this repo.
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+ ## Diffusers 🧨
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+ 1. Install Diffusers 🧨 `pip install -U diffusers`
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+ 2. Run the example
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+ ```python
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+ import torch
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+ from diffusers import FluxPipeline
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+ from diffusers.utils import load_image
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+
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+ pipe: FluxPipeline = FluxPipeline.from_pretrained(
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+ "black-forest-labs/FLUX.1-dev",
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+ torch_dtype=torch.bfloat16,
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+ ).to("cuda")
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+
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+ image = load_image("monalisa.jpg").resize((1024, 1024))
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+
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+ pipe.load_ip_adapter(
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+ "XLabs-AI/flux-ip-adapter-v2",
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+ weight_name="ip_adapter.safetensors",
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+ image_encoder_pretrained_model_name_or_path="openai/clip-vit-large-patch14"
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+ )
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+
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+ def LinearStrengthModel(start, finish, size):
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+ return [
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+ (start + (finish - start) * (i / (size - 1))) for i in range(size)
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+ ]
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+
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+ ip_strengths = LinearStrengthModel(0.4, 1.0, 19)
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+ pipe.set_ip_adapter_scale(ip_strengths)
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+
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+ image = pipe(
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+ width=1024,
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+ height=1024,
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+ prompt='wearing red sunglasses, golden chain and a green cap',
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+ negative_prompt="",
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+ true_cfg_scale=1.0,
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+ generator=torch.Generator().manual_seed(0),
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+ ip_adapter_image=image,
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+ ).images[0]
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+
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+ image.save('result.jpg')
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+ ```
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+
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+
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+
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  If you get bad results, try to set to play with ip strength
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  ### Limitations
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  The IP Adapter is currently in beta.