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Upload folder using huggingface_hub

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Files changed (3) hide show
  1. README.md +7 -6
  2. app.py +50 -0
  3. requirements.txt +4 -0
README.md CHANGED
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  ---
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- title: Controlnet Stable Diffusion 3 Pose
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- emoji: 😻
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- colorFrom: green
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- colorTo: green
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  sdk: gradio
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- sdk_version: 4.40.0
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  app_file: app.py
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  pinned: false
 
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  ---
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- Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
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  ---
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+ title: ControlNet SD3 (Pose)
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+ emoji: 💥
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+ colorFrom: purple
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+ colorTo: blue
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  sdk: gradio
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+ sdk_version: 4.36.0
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  app_file: app.py
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  pinned: false
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+ license: apache-2.0
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  ---
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+ Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
app.py ADDED
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+ import gradio as gr
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+ from diffusers.utils import load_image
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+ import spaces
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+ from panna import ControlNetSD3
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+
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+ model = ControlNetSD3(condition_type="pose")
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+ title = ("# [ControlNet SD3](https://huggingface.co/docs/diffusers/en/api/pipelines/controlnet_sd3) (Pose Conditioning)\n"
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+ "The demo is part of [panna](https://github.com/abacws-abacus/panna) project.")
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+ example_files = []
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+ for n in range(1, 10):
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+ load_image(f"https://huggingface.co/spaces/depth-anything/Depth-Anything-V2/resolve/main/assets/examples/demo{n:0>2}.jpg").save(f"demo{n:0>2}.jpg")
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+ example_files.append(f"demo{n:0>2}.jpg")
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+
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+
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+ @spaces.GPU()
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+ def infer(init_image, prompt, negative_prompt, seed, guidance_scale, controlnet_conditioning_scale, num_inference_steps):
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+ return model.text2image(
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+ image=[init_image],
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+ prompt=[prompt],
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+ negative_prompt=[negative_prompt],
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+ guidance_scale=guidance_scale,
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+ controlnet_conditioning_scale=controlnet_conditioning_scale,
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+ num_inference_steps=num_inference_steps,
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+ seed=seed
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+ )[0]
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+
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+
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+ with gr.Blocks() as demo:
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+ gr.Markdown(title)
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+ with gr.Row():
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+ prompt = gr.Text(label="Prompt", show_label=True, max_lines=1, placeholder="Enter your prompt", container=False)
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+ run_button = gr.Button("Run", scale=0)
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+ with gr.Row():
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+ init_image = gr.Image(label="Input Image", type='pil')
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+ result = gr.Image(label="Result")
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+ with gr.Accordion("Advanced Settings", open=False):
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+ negative_prompt = gr.Text(label="Negative Prompt", max_lines=1, placeholder="Enter a negative prompt")
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+ seed = gr.Slider(label="Seed", minimum=0, maximum=1_000_000, step=1, value=0)
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+ with gr.Row():
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+ guidance_scale = gr.Slider(label="Guidance scale", minimum=0.0, maximum=10.0, step=0.1, value=7.5)
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+ controlnet_conditioning_scale = gr.Slider(label="Controlnet conditioning scale", minimum=0.0, maximum=1.0, step=0.05, value=0.5)
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+ num_inference_steps = gr.Slider(label="Inference steps", minimum=1, maximum=50, step=1, value=50)
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+ examples = gr.Examples(examples=example_files, inputs=[init_image])
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+ gr.on(
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+ triggers=[run_button.click, prompt.submit, negative_prompt.submit],
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+ fn=infer,
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+ inputs=[init_image, prompt, negative_prompt, seed, guidance_scale, controlnet_conditioning_scale, num_inference_steps],
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+ outputs=[result]
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+ )
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+ demo.launch(server_name="0.0.0.0")
requirements.txt ADDED
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+ git+https://github.com/huggingface/diffusers.git
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+ accelerate
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+ sentencepiece
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+ panna>=0.0.9