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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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import torch |
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from panna import Depth2Image, DepthAnythingV2 |
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model_depth = DepthAnythingV2("depth-anything/Depth-Anything-V2-Large-hf", torch_dtype=torch.float32) |
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model_image = Depth2Image("stabilityai/stable-diffusion-2-depth") |
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title = ("# [Depth2Image](https://huggingface.co/stabilityai/stable-diffusion-2-depth) with [DepthAnythingV2](https://huggingface.co/depth-anything/Depth-Anything-V2-Large-hf)\n" |
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"Depth2Image with depth map predicted by DepthAnything V2. 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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@spaces.GPU |
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def infer(init_image, prompt, negative_prompt, seed, width, height, guidance_scale, num_inference_steps): |
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depth = model_depth.image2depth([init_image]) |
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return model_image.text2image( |
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[init_image], |
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depth_maps=depth, |
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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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num_inference_steps=num_inference_steps, |
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height=height, |
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width=width, |
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seed=seed |
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)[0] |
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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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width = gr.Slider(label="Width", minimum=256, maximum=1344, step=64, value=1024) |
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height = gr.Slider(label="Height", minimum=256, maximum=1344, step=64, value=1024) |
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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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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, width, height, guidance_scale, num_inference_steps], |
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outputs=[result] |
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) |
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demo.launch() |
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