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Create app.py
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app.py
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import gradio as gr
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import os
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hf_token = os.environ.get("HF_TOKEN")
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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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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'],
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hf_token=hf_token
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)
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pipe.to('cuda:0', torch.float16)
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def infer(image_in, prompt):
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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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return image
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with gr.Blocks() as demo:
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with gr.Column():
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gr.Markdown("""
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# SD3 ControlNet
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""")
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image_in = gr.Image(label="Image reference", sources=["upload"], type="filepath")
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prompt = gr.Textbox(label="Prompt")
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submit_btn = gr.Button("Submit")
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result = gr.Image(label="Result")
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submit_btn.click(
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fn = infer,
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inputs = [image_in, prompt],
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outputs = [result],
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show_api=False
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)
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demo.queue().launch()
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