initialize zerogpu

#1
by linoyts HF staff - opened
Files changed (2) hide show
  1. app.py +8 -6
  2. style.css +16 -0
app.py CHANGED
@@ -6,7 +6,7 @@ from diffusers.pipelines.auto_pipeline import AutoPipelineForImage2Image
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  from src.sdxl_inversion_pipeline import SDXLDDIMPipeline
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  from src.config import RunConfig
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  from src.editor import ImageEditorDemo
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-
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  device = "cuda" if torch.cuda.is_available() else "cpu"
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  scheduler_class = MyEulerAncestralDiscreteScheduler
@@ -27,7 +27,7 @@ pipe_inversion.scheduler_inference = scheduler_class.from_config(pipe_inference.
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  # pipe = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo", use_safetensors=True)
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  # pipe = pipe.to(device)
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-
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  def infer(input_image, description_prompt, target_prompt, edit_guidance_scale, num_inference_steps=4,
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  num_inversion_steps=4,
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  inversion_max_step=0.6):
@@ -65,8 +65,8 @@ else:
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  power_device = "CPU"
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  # with gr.Blocks(css=css) as demo:
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- with gr.Blocks() as demo:
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- gr.Markdown(f"""
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  This is a demo for our [paper](https://arxiv.org/abs/2312.12540) **RNRI: Regularized Newton Raphson Inversion for Text-to-Image Diffusion Models**.
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  Image editing using our RNRI for inversion demonstrates significant speed-up and improved quality compared to previous state-of-the-art methods.
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  Take a look at our [project page](https://barakmam.github.io/rnri.github.io/).
@@ -79,18 +79,20 @@ with gr.Blocks() as demo:
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  with gr.Row():
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  description_prompt = gr.Text(
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  label="Image description",
 
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  show_label=False,
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  max_lines=1,
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- placeholder="Enter your image description",
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  container=False,
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  )
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  with gr.Row():
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  target_prompt = gr.Text(
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  label="Edit prompt",
 
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  show_label=False,
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  max_lines=1,
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- placeholder="Enter your edit prompt",
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  container=False,
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  )
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  from src.sdxl_inversion_pipeline import SDXLDDIMPipeline
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  from src.config import RunConfig
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  from src.editor import ImageEditorDemo
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+ import spaces
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  device = "cuda" if torch.cuda.is_available() else "cpu"
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  scheduler_class = MyEulerAncestralDiscreteScheduler
 
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  # pipe = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo", use_safetensors=True)
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  # pipe = pipe.to(device)
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+ @spaces.GPU
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  def infer(input_image, description_prompt, target_prompt, edit_guidance_scale, num_inference_steps=4,
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  num_inversion_steps=4,
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  inversion_max_step=0.6):
 
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  power_device = "CPU"
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  # with gr.Blocks(css=css) as demo:
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+ with gr.Blocks(css="style.css") as demo:
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+ gr.Markdown(f""" # Real Time Editing with RNRI Inversion 🍎⚡️
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  This is a demo for our [paper](https://arxiv.org/abs/2312.12540) **RNRI: Regularized Newton Raphson Inversion for Text-to-Image Diffusion Models**.
71
  Image editing using our RNRI for inversion demonstrates significant speed-up and improved quality compared to previous state-of-the-art methods.
72
  Take a look at our [project page](https://barakmam.github.io/rnri.github.io/).
 
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  with gr.Row():
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  description_prompt = gr.Text(
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  label="Image description",
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+ info = "Enter your image description ",
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  show_label=False,
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  max_lines=1,
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+ placeholder="a cake on a table",
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  container=False,
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  )
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  with gr.Row():
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  target_prompt = gr.Text(
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  label="Edit prompt",
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+ info = "Enter your edit prompt",
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  show_label=False,
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  max_lines=1,
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+ placeholder="an oreo cake on a table",
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  container=False,
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  )
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style.css ADDED
@@ -0,0 +1,16 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+
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+ #component-0{
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+ max-width: 900px;
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+ margin: 0 auto;
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+ }
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+
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+ #description, h1 {
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+ text-align: center;
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+ }
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+
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+ #duplicate-button {
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+ margin: auto;
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+ color: #fff;
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+ background: #1565c0;
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+ border-radius: 100vh;
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+ }