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+ # SD3 Controlnet
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+
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+
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+
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+
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+ | raw | control image | output |
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+ |:-------------------------:|:-------------------------:|:-------------------------:|
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+ |<img src="./raw.jpg" width = "400" /> | <img src="./canny.jpg" width = "400" /> | <img src="./demo_1.jpg" width = "400" /> |
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+
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+
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+ # Install Diffusers-SD3-Controlnet
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+
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+ The current [diffusers](https://github.com/instantX-research/diffusers_sd3_control.git) have not been merged into the official code yet.
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+
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+ ```cmd
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+ git clone -b sd3_control https://github.com/instantX-research/diffusers_sd3_control.git
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+ cd diffusers
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+ pip install -e .
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+ ```
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+
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+ # Demo
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+ ```python
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+ import torch
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+ from diffusers import StableDiffusion3Pipeline
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+ from diffusers.models.controlnet_sd3 import ControlNetSD3Model
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+ from diffusers.utils.torch_utils import randn_tensor
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+ import sys, os
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+ sys.path.append('/path/diffusers/examples/community')
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+ from pipeline_stable_diffusion_3_controlnet import StableDiffusion3CommonPipeline
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+ # load pipeline
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+ base_model = 'stabilityai/stable-diffusion-3-medium-diffusers'
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+ pipe = StableDiffusion3CommonPipeline.from_pretrained(
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+ base_model,
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+ controlnet_list=['InstantX/SD3-Controlnet-Canny_alpha_512']
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+ )
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+ pipe.to('cuda:0', torch.float16)
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+ prompt = 'Anime style illustration of a girl wearing a suit. A moon in sky. In the background we see a big rain approaching. text "InstantX" on image'
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+ n_prompt = 'NSFW, nude, naked, porn, ugly'
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+ # controlnet config
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+ controlnet_conditioning = [
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+ dict(
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+ control_index=0,
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+ control_image=load_image('https://huggingface.co/InstantX/SD3-Controlnet-Canny/resolve/main/canny.jpg'),
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+ control_weight=0.7,
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+ control_pooled_projections='zeros'
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+ )
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+ ]
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+ # infer
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+ image = pipe(
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+ prompt=prompt,
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+ negative_prompt=n_prompt,
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+ controlnet_conditioning=controlnet_conditioning,
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+ num_inference_steps=28,
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+ guidance_scale=7.0,
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+ height=1024,
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+ width=1024,
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+ latents=latents,
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+ ).images[0]
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+ ```