Create app.py

app.py

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+import gradio as gr
+import os
+hf_token = os.environ.get("HF_TOKEN")
+import torch
+from diffusers import StableDiffusion3Pipeline
+from diffusers.models.controlnet_sd3 import ControlNetSD3Model
+from diffusers.utils.torch_utils import randn_tensor
+
+from pipeline_stable_diffusion_3_controlnet import StableDiffusion3CommonPipeline
+
+# load pipeline
+base_model = 'stabilityai/stable-diffusion-3-medium-diffusers'
+pipe = StableDiffusion3CommonPipeline.from_pretrained(
+    base_model, 
+    controlnet_list=['InstantX/SD3-Controlnet-Canny'],
+    hf_token=hf_token
+)
+pipe.to('cuda:0', torch.float16)
+
+def infer(image_in, prompt):
+    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'
+    n_prompt = 'NSFW, nude, naked, porn, ugly'
+    # controlnet config
+    controlnet_conditioning = [
+        dict(
+            control_index=0,
+            control_image=load_image('https://huggingface.co/InstantX/SD3-Controlnet-Canny/resolve/main/canny.jpg'),
+            control_weight=0.7,
+            control_pooled_projections='zeros'
+        )
+    ]
+    # infer
+    image = pipe(
+        prompt=prompt,
+        negative_prompt=n_prompt,
+        controlnet_conditioning=controlnet_conditioning,
+        num_inference_steps=28,
+        guidance_scale=7.0,
+        height=1024,
+        width=1024,
+        latents=latents,
+    ).images[0]
+
+    return image
+
+
+with gr.Blocks() as demo:
+    with gr.Column():
+        gr.Markdown("""
+        # SD3 ControlNet
+        """)
+        image_in = gr.Image(label="Image reference", sources=["upload"], type="filepath")
+        prompt = gr.Textbox(label="Prompt")
+        submit_btn = gr.Button("Submit")
+        result = gr.Image(label="Result")
+    
+    submit_btn.click(
+        fn = infer,
+        inputs = [image_in, prompt],
+        outputs = [result],
+        show_api=False
+    )
+demo.queue().launch()