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import gradio as gr
import os
from diffusers.utils import load_image
import spaces
from panna import Depth2Image, DepthAnythingV2
model_image = Depth2Image("stabilityai/stable-diffusion-2-depth")
model_depth = DepthAnythingV2("depth-anything/Depth-Anything-V2-Large-hf")
title = ("# [Depth2Image](https://huggingface.co/stabilityai/stable-diffusion-2-depth) with [DepthAnythingV2](https://huggingface.co/depth-anything/Depth-Anything-V2-Large-hf)\n"
"Depth2Image with depth map predicted by DepthAnything V2. The demo is part of [panna](https://github.com/abacws-abacus/panna) project.")
example_files = []
for n in range(10):
url = f"https://huggingface.co/spaces/depth-anything/Depth-Anything-V2/resolve/main/assets/examples/demo{n:0>2}.jpg"
load_image(url).save(os.path.basename(url))
example_files += [os.path.basename(url)]
@spaces.GPU
def infer(init_image, prompt, negative_prompt, seed, width, height, guidance_scale, num_inference_steps):
depth = model_depth.image2depth([init_image])
return model_image.text2image(
[init_image],
depth_maps=depth,
prompt=[prompt],
negative_prompt=[negative_prompt],
guidance_scale=guidance_scale,
num_inference_steps=num_inference_steps,
height=height,
width=width,
seed=seed
)[0]
with gr.Blocks() as demo:
gr.Markdown(title)
with gr.Row():
prompt = gr.Text(label="Prompt", show_label=True, max_lines=1, placeholder="Enter your prompt", container=False)
run_button = gr.Button("Run", scale=0)
with gr.Row():
init_image = gr.Image(label="Input Image", type='pil')
result = gr.Image(label="Result")
with gr.Accordion("Advanced Settings", open=False):
negative_prompt = gr.Text(label="Negative Prompt", max_lines=1, placeholder="Enter a negative prompt")
seed = gr.Slider(label="Seed", minimum=0, maximum=1_000_000, step=1, value=0)
with gr.Row():
width = gr.Slider(label="Width", minimum=256, maximum=1344, step=64, value=1024)
height = gr.Slider(label="Height", minimum=256, maximum=1344, step=64, value=1024)
with gr.Row():
guidance_scale = gr.Slider(label="Guidance scale", minimum=0.0, maximum=10.0, step=0.1, value=7.5)
num_inference_steps = gr.Slider(label="Inference steps", minimum=1, maximum=50, step=1, value=50)
examples = gr.Examples(examples=example_files, inputs=[init_image])
gr.on(
triggers=[run_button.click, prompt.submit, negative_prompt.submit],
fn=infer,
inputs=[init_image, prompt, negative_prompt, seed, width, height, guidance_scale, num_inference_steps],
outputs=[result]
)
demo.launch()
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