Create README.md
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README.md
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# SD3 Controlnet
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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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# Install Diffusers-SD3-Controlnet
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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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```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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# 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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```
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