Kvikontent commited on
Commit
bc7cf63
1 Parent(s): 22647d4

Update app.py

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Files changed (1) hide show
  1. app.py +6 -28
app.py CHANGED
@@ -5,9 +5,9 @@ from diffusers import DiffusionPipeline
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  # Load model and scheduler
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  ldm = DiffusionPipeline.from_pretrained("CompVis/ldm-text2im-large-256")
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- def generate_image(prompt, negative_prompt="Low quality", width=512, height=512, num_steps=50, eta=0.3, guidance_scale=6):
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  # Run pipeline in inference (sample random noise and denoise)
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- images = ldm([prompt], num_inference_steps=num_steps, eta=eta, guidance_scale=guidance_scale, negative_prompts=[negative_prompt]).images
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  # Resize image to desired width and height
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  resized_images = [image.resize((width, height)) for image in images]
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  # Save images
@@ -18,35 +18,13 @@ def generate_image(prompt, negative_prompt="Low quality", width=512, height=512,
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  # Define the interface
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  iface = gr.Interface(
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  fn=generate_image,
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- inputs=[
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- gr.inputs.Textbox(label="Prompt", lines=2),
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- gr.inputs.Textbox(label="Negative Prompt (optional)", lines=2),
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- gr.inputs.Number(label="Width (optional)", default=512),
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- gr.inputs.Number(label="Height (optional)", default=512),
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- gr.inputs.Number(label="Number of Inference Steps (optional)", default=50),
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- gr.inputs.Number(label="Eta (optional)", default=0.3),
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- gr.inputs.Number(label="Guidance Scale (optional)", default=6),
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- ],
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  outputs="text",
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  layout="vertical",
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  title="Image Generation",
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- description="Generate images based on prompts. Adjust the optional parameters for customization. The generated images will be resized to the specified width and height.",
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- article="Check out the documentation for more information: [link](https://docs.gradio.app/)",
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- examples=[
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- ["A painting of a squirrel eating a burger", "Low quality", 512, 512, 50, 0.3, 6],
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- ["A breathtaking landscape with mountains", "Blurry", 800, 600, 30, 0.5, 8],
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- ["An abstract artwork with vibrant colors", "Dull", 1024, 768, 70, 0.2, 10],
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- ],
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- )
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-
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- # Configure styling options
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- iface.configure(
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- label_font="Arial",
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- label_font_size=18,
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- border_width=2,
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- border_color="blue",
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- button_bg_color="lightblue",
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- button_text_color="black",
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  )
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  # Launch the interface
 
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  # Load model and scheduler
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  ldm = DiffusionPipeline.from_pretrained("CompVis/ldm-text2im-large-256")
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+ def generate_image(prompt, negative_prompt="Low quality", width=512, height=512):
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  # Run pipeline in inference (sample random noise and denoise)
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+ images = ldm([prompt], num_inference_steps=50, eta=0.3, guidance_scale=6, negative_prompts=[negative_prompt]).images
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  # Resize image to desired width and height
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  resized_images = [image.resize((width, height)) for image in images]
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  # Save images
 
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  # Define the interface
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  iface = gr.Interface(
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  fn=generate_image,
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+ inputs=["text", "text", "number", "number"],
 
 
 
 
 
 
 
 
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  outputs="text",
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  layout="vertical",
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  title="Image Generation",
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+ description="Generate images based on prompts.",
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+ article="For more information, visit the documentation: [link](https://docs.gradio.app/)",
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+ examples=[["A painting of a squirrel eating a burger", "Low quality", 512, 512]]
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  )
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  # Launch the interface